multi-scale characterization studies of aged li-ion large ... · the performance of these batteries...

Journal of The Electrochemical Society, 160 (11) A2111-A2154 (2013) A21110013-4651/2013/160(11)/A2111/44/$31.00 © The Electrochemical Society

Multi-Scale Characterization Studies of Aged Li-Ion Large FormatCells for Improved Performance: An OverviewShrikant C. Nagpure,a,∗ Bharat Bhushan,a,z and S. S. Babub

aNanoprobe Laboratory for Bio-& Nanotechnology and Biomimetics (NLBB), Ohio State University, Columbus,Ohio 43210, USAbDepartment of Material Science and Engineering, Ohio State University, Columbus, Ohio 43210, USA

Among various electrical energy storage devices the recent advances in Li-ion battery technology has made this technology verypromising for the electric vehicles. The advantage of these batteries is high energy and power density. Understanding the agingmechanisms of these batteries to improve the cycle life is critical for electrification of vehicles. Aging of the cells at the system levelis quantified by the increase in internal resistance and drop in capacity. It is imperative to understand the degradation of the electrodematerials of the battery related to these system level parameters. The degradation of the material is caused by several simultaneousphysiochemical processes that occur within the batteries, which makes material characterization of the electrodes challenging. Thisreview provides results of a systematic multi-scale characterization study to understand the degradation mechanisms in LiFePO4cathode material. The study includes various techniques to understand the physical, morphological, electrical, chemical and structuralchanges in the cathode material. The review also presents an overview of the various modeling techniques used for Li-ion batteries.Simulation results of one of the models are presented using results of multi-scale characterization studies of the cathode material.© 2013 The Electrochemical Society. [DOI: 10.1149/2.001311jes] All rights reserved.

Manuscript submitted January 29, 2013; revised manuscript received August 22, 2013. Published October 3, 2013.

The world energy consumption is expected to double in the next50 years.1 Increased environmental awareness has renewed our inter-est in low or zero emission energy sources to meet this ever-growingdemand for energy. One of the major sources of energy consumptionis for our daily transportation needs. So far, we have heavily relied onhydrocarbon-fueled internal combustion engines for our daily trans-portation needs. Vehicles powered by hydrocarbon fuels are one ofthe major sources of green house gases, such as CO2, causing air pol-lution and damaging the ecosystem. Electrochemical energy storagesystems such as batteries, fuel cells and supercapacitors can play avital role in electrification of personal transportation systems by pro-viding a sustainable clean energy source and subsequently reducinggreen house gas emissions.2–4

Winter and Brodd5 have presented a detailed review of these var-ious electrochemical energy storage systems. A brief comparison ofprominent battery chemistries for automobile applications is given inAppendix A1. The Ragone plot (Fig. 1), explains the use of hydro-carbon fuel over these clean electrochemical energy storage systems.As seen in Fig. 1, Li-ion battery technology has higher energy density(electric range) and power density (acceleration) compared to otherchemistries and already meets the United States Battery Consortium’s(USABC) hybrid electric vehicle (HEV) and plug-in HEV (PHEV)goals enabling the commercialization of electric vehicle models.6–8

Figure 2 shows the technological advances of Li-ion battery technol-ogy for PHEV application, though a similar chart can be generated forbattery EV (BEV) and HEV.9–11 As seen in this plot, the life and costof Li-ion battery technology needs to be considerably improved forsuccessful use of this technology in vehicle electrification. USABChas also set goals for battery life. According to USABC, a 42 V batteryin a HEV should have a calendar life of 15 years.12 Electric vehicles(EV) should have a battery system that can last for 10 years.13 In termsof cycles, 1000 cycles at 80% depth-of-discharge are expected in EV,13

and 300,000 cycles at 50 Wh are expected in a plug-in HEV.14 Also,the DOE in its EV Everywhere Grand Challenge initiative targets a4X reduction in cost ($500/kWH to $125/kWh), 2X reduction in sizeand 2X+ reduction in weight (100 Wh/kg to 250 Wh/kg, 200 Wh/l to400 Wh/l and 400 W/kg to 2000 W/kg) by 2022.15,16

A scientific fundamental understanding of the phenomena gov-erning the degradation of life is necessary in achieving sustainableimprovements in cost, as well as calendar and cycle life. When a cellis formed and put in operation the operating current and temperatureof the cell, which can affect the cell kinetics and transport phenomena

∗Electrochemical Society Student Member.zE-mail: [email protected]

Figure 1. Ragone chart showing the comparison of the power density andenergy density for batteries, capacitors, and fuel cells and internal combustionengine. Energy density represents the capacity while power density representsthe rate of the charging/discharging of EES device.9,11

can be controlled to optimize its performance. The evolution of designparameters such as active material particle size, electrode thickness,porosity, and active surface area during operation, will also affecttransport and kinetic phenomena within the cell resulting in perfor-mance degradation and loss of cycle life. A scientific understanding

Figure 2. Star chart showing the state of the art for the performance comparedwith USABC goals.9–11

ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP ecsdl.org/site/terms_use address. Redistribution subject to ECS license or copyright; see 140.254.87.149Downloaded on 2013-11-05 to IP

http://dx.doi.org/10.1149/2.001311jes

mailto:[email protected]

http://ecsdl.org/site/terms_use












































A2112 Journal of The Electrochemical Society, 160 (11) A2111-A2154 (2013)

of the phenomena governing the degradation of these parameters andits effect on transport and kinetic phenomena will be different in largeformat cells that are used in building packs and modules for EV’s thanin the traditional coin cells used in laboratory studies.

It is generally difficult to analyze all the aging mechanisms in asingle article due to the various different chemistries of the lithium-ioncells. Even within particular cell chemistry the aging mechanisms willbe greatly affected by the nature of the different components such asthe synthesis process of the active material, electrode design, manu-facturing and assembly process, etc. In this overview article we presenta methodology to systematically study this degradation of life in largeformat LiFePO4 cells. We will first briefly discuss the fundamentaloperation of a standard Li-ion cell along with the different materials,structure and fabrication processes used in building the large formatLi-ion cells. We then discuss the most commonly observed agingmechanisms across different lithium-ion cell chemistries. This will befollowed by the main topic of this article, a multi-scale characteriza-tion methodology that analyzes the evolution of various parameters,which affect the fundamental kinetic and transport phenomena overthe life of the large format cell causing degradation in performanceand life of the cell. We will cover some of the modeling efforts usedin predicting the performance and simulating the life of large formatLi-ion cells. The overview concludes with a brief summary of thedamage mechanisms identified at various length scales, the summaryof the modeling techniques, and the scope for future studies.

Li-Ion Batteries

Like any typical electrochemical cell, a Li-ion cell has two elec-trodes, an anode and a cathode separated by an electrically insulatingseparator. The cell is filled with electrolyte that is a solvent contain-ing lithium salt. Figure 3 shows a schematic of a Li-ion cell with agraphite anode, LiFePO4 cathode, separator and an electrolyte. Thecell stores the electrical energy in the form of chemical energy dur-ing charging and delivers this stored energy back as electrical energyduring discharging. This energy conversion takes place within the cellthrough a redox reaction. This redox reaction is a combination of twoseparate half-cell reactions taking place at the two electrodes. Duringdischarging, the anode undergoes an oxidation reaction as seen inEq. 2.1.

Lix C6 ↔ Li+ + e− + C6 [2.1]

The 0 ≤ x ≤ 1 denotes the degree of lithiation of the anode. Corre-spondingly, the cathode undergoes the reduction reaction as given byEq. 2.2

FeP O4 + Li+ + e− ↔ Liy FeP O4 [2.2]

Figure 3. Schematic of Li-ion cell operstion. During charging Li+ ions areinserted in the anode structure by virtue of intercalation and during discharging,these Li+ ions are removed from the anode structure by virtue of deintercalationand transferred to the cathode (adapted from Srinivasan9).

Similarly, 0 ≤ y ≤ 1 denotes the degree of lithiation of the cathode.During these reactions the Li+ ions from the anode diffuse throughthe liquid electrolyte and through the separator and intercalate intothe cathode material. The electrons flow through the external circuitproviding the necessary electrical energy. The same reactions occur inthe reverse direction when the cell is charged with an external sourceof energy. Li+ ions deintercalate from the cathode and intercalate intothe anode during the charging of the cell. The two half-cell reactionscombined together give the following complete reaction for the cell,

Li(1−x) FeP O4 + Lix C6 ↔ Lix FeP O4 + Li1−x C6 [2.3]

The performance of these batteries is highly dependent on thethermal, mechanical and physical stability of its materials. The maincomponents of the lithium ion battery are the anode, cathode, sep-arator and the electrolyte. The combination of the anode, cathode,electrolyte and separator materials will dictate the performance ofthe cell, the energy and power capacity, life, safety characteristics,operating temperatures, etc. The electrodes are a composite structurecomprising of active material, binders, and additives.17–21 The sepa-rator is made up of a polymer that prevents the contact between theanode and cathode but allows lithium ions to pass through it. Theelectrolyte provides the path for the lithium ions to travel between theelectrodes during the cycling of the cell. Due to the potential applica-tion of these batteries in the transportation industry, there has been agreat deal of effort to develop cheaper, reliable and stable materials.In doing so, often extraordinary claims are made about the long termelectrochemical performance of the system while the intrinsic limita-tions are overlooked. Here certain active materials for anode, cathode,and electrolytes have been discussed. These materials have been testedby several researchers and they have shown certain potential in fur-thering lithium ion battery technology. We will now briefly discussthe various materials of the cell, and the manufacturing and assemblyprocesses of large format cells for completeness of this overview.

Electrodes.— Electrodes are the active material within the cell thatundergo the intercalation and deintercalation process during chargingand discharging cycles. The combination of the electrode materialfor the cell decides the operating voltage, the specific energy and thespecific power capacity of the cell. The electrode materials shouldhave these key features:17,22

� The anode material should have a high lithium chemical po-tential and the cathode material should have low lithium chemicalpotential to maximize the operating voltage.

� The electrode material should be able to hold a large amountof lithium ions per unit formula of the material to maximize the cellcapacity.

� The electrode material should have good structural integrityand should be able to withstand the cyclic volume change for a largenumber of charge-discharge cycles to maximize the cell life.

� The electrode material should have good ionic and electronicconductivity to minimize the polarization losses and maximize thepower capability of the cell.

� The redox voltages of the electrode material should lie withinthe stable operating voltages of the electrolyte.

� The electrode material should be inexpensive, environmentallybenign, and thermally and chemically stable within the required op-erating conditions.

Anode.—Lithium is an ideal anode material for Li-ion batteries, butbecause of the plating out of lithium during the charge/dischargecycle and subsequent formation of dendrites, there is a risk of thecell being short-circuited. Instead, carbonaceous materials are pre-ferred for anodes in current commercial Li-ion batteries.23 Studieshave been conducted on graphite,24 C-C composite, mesocarbon mi-crobeads (MCMB),25 carbon nanotubes26,27 and carbon films. Theseanodes have a very good rate of lithium insertion/removal and thusimprove the charge/discharge rate (power rating) of the battery, butthe performance of the cell is limited due to the formation of a solid

Journal of The Electrochemical Society, 160 (11) A2111-A2154 (2013) A2113

Table I. Properties of certain anode materials suitable for lithium-ion batteries (adapted from Mantia282).

Reduced form Oxidized formEeq

(Li/Li+) (V)aQmax /

(mAh g-1)b

MetalsLi Li+c 0 3861

Graphite based compoundsLiC6 Graphite 0.1 372Li1/2C6 Graphite 0.13 186Li1/3C6 Graphite 0.22 124

AlloysLiAl Al 0.35 993Li22Sn5 Sn 0.42–0.66 994Li3Sb Sb 0.9 660Li21Si5 Si 0.3 4000

TitanatesLixTiO2 TiO2 1.8 170Li4+xTi5O12 Li4Ti5O12 1.5 160

aThe electrochemical activity can be observed in a range of potentials.bThe specific charge is relative to the weight of the pristine activematerial.cLi+ is in solution.18,19,283

electrolyte interphase (SEI) during cycling of the cell.23,28,29 The SEIis formed from the electrolyte decomposition products.30 This SEIlayer prevents the graphite surface from further exfoliation and alsoprevents further reduction of the electrolyte and consumption of activelithium. In the case of nanoparticulate graphite, the consumption ofactive lithium would be even higher, and the excessive charge devel-oped between the graphite surface and the SEI would result in a lossof overall cell voltage. The SEI layer also reduces the active surfacearea and the porosity affecting the performance of the cell. Also, itis important to note that the lithium is intercalated into graphite atpotentials less than 100 mV versus Li/Li+. There is always a risk oflithium depositing on the graphite surface resulting in dendrite for-mation and fatal short-circuiting of the cell.24 The other classes ofmaterials that are being pursued are the materials that can reversiblyform alloys with lithium. As shown in Table I these alloys have muchhigher capacity than graphite. Since the equilibrium potential of thesealloys with Li/Li+ is higher the possibility of plating and the reductionof electrolyte solvent is minimized. The drawback of these materialsis the large volume change during the charging and discharging cy-cles that leads to cracking and mechanical disintegration of the anodestructure. The last groups of materials that can be used as anode arecertain lithium oxides that have low lithium equilibrium potential.TiO2 is an example of such a material.31 These materials have theleast risk of lithium plating and electrolyte reduction, but have verylow energy capacity due to the low operating voltage when coupledwith other cathode material.Cathode.—The most common cathode materials are layered oxidesLiMO2, the spinels Li[M2]O4 and olivines LiMPO4 where M is atransition metal atom.7

Layered oxide LiCoO2, was developed as the cathode mate-rial for commercial Li-ion batteries,7,24 but due to expensive andtoxic cobalt they were later replaced by other layered oxidessuch as LiNi0.8Co0.15Al0.05O2, LiNi0.8Co0.2O2, Li1−xNi1−yCoyO2, andLiMn0.5Ni0.5O2 in commercial batteries.7,32,33 These oxides have ahigh operating voltage, in the range of 2.75 V to 4.3 V.7 They havevery high energy density and power density but they lack the necessarystructural stability for deep discharge cycles, during which the host ox-ide structure collapses upon removal of more than 50% of the Li. Thespinel structured LiMn2O4 has good structural stability.24 They alsohave higher operating voltage and high charge/discharge rate but lowenergy density. The most recent among these cathode materials havebeen olivine-structured materials such as LiFePO4. LiFePO4 has a

Table II. Properties of certain cathode materials suitable forlithium-ion batteries (adapted from Mantia282).

Reduced form Oxidized formEeq

(Li/Li+) (V)aQmax

(mAh g-1)b

Layered compoundsLiTiS2 TiS2 1.5–2.4 239Li3V2O5 V2O5 2–3.5 442LiCoO2 LixCoO2 3.5–4.2 274LiNiO2 LixNiO2 3.5–4.2 274LiMnO2 LixMnO2 3.5–4.2 285Li(NiMnCo)O2 Lix(NiMnCo)O2 3–4.5c 274(c)

OlivinesLiMnO4 LixMnO4 3 –4 213

SpinelLiFePO4 FePO4 3.4 170

aThe electrochemical activity can be observed in a range of potentials.bThe specific charge is relative to the weight of the pristine activematerial and all lithium m ions removed.cThe mixed oxides can show very different behavior depending on theexact composition.20

lower operating voltage of ∼3.3 V but demonstrates higher power andenergy density along with good structural stability. Using nanosizedparticles helps mitigate the lower conductivity of LiFePO4. Table IIlists the properties of certain cathode materials. Battery manufactur-ers have also developed cathodes with multiple materials such as amixed cathode with Li Ni1/3Mn1/3Co1/3O2 layered oxide and LiMn2O4

spinel.34–40 They have high specific capacity and thermal stability, andthey limit the dissolution of Mn that limits the cycle life.11,37–39,41,42

This review focuses on the characterization of LiFePO4 cathodematerial used in commercial cells. This material is extensively dis-cussed in literature and it is preferred by some automobile makers dueto its low cost and environmentally benign nature. The oxygen atomsin the phosphate have strong bonds and are not easily released, mak-ing the material incombustible in the event of overcharging. Thus thematerial is thermally and chemically stable and can provide thousandsof charge/discharge cycles.43–46

Separators.—A separator is porous membrane with good ionic con-ductivity and good electronic insulation. The separator should allowa rapid flow of ions while preventing any electrical contact betweenthe two electrodes of the cell. Until recently very little research anddevelopment has done to develop new separators as compared toother battery components. The separators should have the followingfeatures:47

� Good electronic insulator� Minimum electrolyte and ionic resistance� Good mechanical, dimensional and physical stability� Uniform thickness, and tortuosity� Chemically stable and resistant to degradation by electrolyte,

impurities and electrode reactants and products.� Thermally stable� Prevent migration of species between the two electrodes� Easily wetted by the electrolyte

The most common type of separators in nonaqueous Li-ion batteriesis microporous polyolefins. They can be a single layer of polyethylene(PE), polypropylene (PP) or laminates of PE and PP (Fig. 4).47,48

Electrolytes.—The function of the electrolyte is to provide a path forthe ions while blocking any electronic charge flow. An electrolyteshould have the following keys features49

� Good ionic conductor and electronic insulator, to have betterion transport and minimum self-discharge


Figure 4. SEM micrographs of (a) uni-layer and (b) tri-layer microporousseparator. [Picture courtesy Celgrad]

� Electrochemically inert with both, the oxidizing or reducingelectrode surfaces within the operating range of the cell

� Should not react with other cell components such as cell sepa-rators, current collectors, etc.

� Environmentally benign

The combination of electrolyte and the electrode materials is respon-sible for the formation of the SEI that limits the life of the cell. Thestability and quality of the film depends on the electrolyte composi-tion, additives and impurities. Usually the electrolyte is composed ofone or more liquid solvents and one or more salts. The most commonelectrolytes used in current generation lithium ion batteries are non-aqueous. The preferred solvent for the electrolyte in lithium-ion batter-ies is a combination of ethylene carbonate (EC) and dimethyl carbon-ate (DMC). EC is solid at room temperature and has low viscosity.49

The EC:DMC mixture is liquid for range of compositions. The mostcommon salt is LiPF6. A 1 M LiPF6 solution of EC:DMC 1:1 (wt)has a conductivity of 107 mS cm−1, and it is stable and safe in thetemperature range between −20 and 50◦C. The conductivity is quitehigh for a nonaqueous electrolyte, but is still too low to avoid non-homogeneous usage of thick electrodes when high power is required.Certain polymers and ionic liquids are being developed for futuregenerations of lithium ion batteries.49 Solid polymer electrolytes havevery poor conductivity (<1 mS cm−1).50 Ionic liquids also need to betested before they can be used in lithium ion batteries.49 Table III liststhe properties of certain solutes and solvent for lithium-ion batteryelectrolytes.

Table III. Properties of certain solvent and solutes for lithium-ionbattery electrolytes (adapted from Mantia282).

SolventsSolvent Tm (◦C) Tb (◦C) η (cPa) εa

Cyclic carbonatesEC 36.4 248 1.9b 89.8PC −48.8 242 2.5 64.9

Linear carbonatesDMC 4.6 91 0.59 3.1DEC −74.3 126 0.75 2.8EMC −53 110 0.65 2.9

Saltsσ (mS cm−1)

Salt T (◦C) PC EC:DMCLiBF4 >100 3.4 4.9LiPF6 ∼80 5.8 10.7LiAsF6 >100 5.7 11.1LiClO4 >100 5.6 8.4

aMeasured at 25 ◦C.bMeasured at 40 ◦C.49

Construction and assembly of large format cells.— The manufac-turing technology for large format cells includes chemical synthesis,film casting, joining, polymer manufacturing, etc. Some of the keychallenges for lithium-ion battery manufacturing are the scaling up ofthe processes, quality control, advanced materials processing, cost ofthe equipment and dry room environment.

The active electrode materials is synthesized as spherical or el-lipsoidal particles. The nanoparticles of these lithium compoundsare made by grinding, by synthesis from solution, or by solgelapproaches.24 The particle size is very critical in cell operation. Asseen in the equation below the time for diffusion (t) is directly pro-portional to the size of the particle,

t ∝ d2

πD[2.4]

where 2d is the diameter of the particle and D is the diffusion coef-ficient. Hence the primary particles have a radius in a nanometer tomicrometer range to reduce the diffusion time and length, to providea higher electrolyte/electrode contact area, and thus to improve thecharge/discharge kinetics of the Li-ion batteries.51

The active material particles are mixed with a carbon filler materialand polyvinylidene fluoride (PVDF) binder material to form thickslurry that does not flow but is conformable. This thick slurry is then“painted” onto a metal substrate that acts as a current collector duringcell operation. Typically the current collector for the anode side iscopper while for the cathode side it is aluminum. The compositeelectrodes are porous in structure, so that the electrolyte can percolatethrough the pores and provide the transport mechanisms for the lithiumion produced from electrode reactions. Table IV shows the typicalparameters of the two electrodes. Since the cathode material has lesscapacity than the anode material the thickness of the cathode is usuallyhigher to achieve uniform utilization of the active material.

Table IV. Typical values of different properties of designparameter of porous electrodes for large format Li-ion cell.11

Property name Value

Binder volume fraction 5–10%Porosity 30–40%Average active material particle radius (nm) 1–1000Thickness (μm) 50–100


Table V. Typical properties of commercially available separatorsfor large format Li-ion cells.11,47,48

Property name Value

Structure Single TrilayerComposition PE or PP PP/PE/PPThickness (μm) 20–25 20–25Gurley (s) 22–26 20–23Porosity 40–43% 42Ionic resistivitya (� cm2) 2.23–2.66 1.36–1.85Melting temperatre (◦C) 137–165 135/165

aIn 1 M LiPF6 EC:EMC (30:70 by volume)

The electrodes are then assembled in a sandwich pattern withalternate layers of separator material in between. The properties ofcommon commercial separators are shown in Table V. The sandwichof the anode, separator and cathode material is then assembled in cas-ing of different shape and size (Fig. 5) by rolling, folding or stackingprocess. The casing structure is filled with just enough electrolyte tofill the pores of the solid matrix and then it is hermetically sealed.

Commercial batteries vary in size and shape from the coin cellsas shown in Fig. 5. Cylindrical cells (Fig. 5a) were initially preferreddue to ease of manufacturing and better protection from environmentalcontaminants.

The prismatic cell (Fig. 5b) and pouch cell (Fig. 5c) have nowbecome more common due to better stacking efficiency in packs.The prismatic and pouch cells have higher volumetric density whenassembled in a pack. The drawbacks of the pouch cell are swellingdue to the evolution of gases and high sensitivity to twist.52

Critical issue in aging studies of large format cells.— First prin-ciples electrochemical models can adequately describe the electro-chemical operation of the Li-ion cell, but the scientific understandingof the phenomena that governs the degradation in large format cellslimiting its performance and calendar and cycle life are not yet fullyunderstood30,53,54 When a cell is formed and put in operation the op-erating current and temperature of the cell, which can affect the cellkinetics and transport phenomena, can be controlled to optimize itsperformance. In large format cells the evolution of design parameterssuch as active material particle size, electrode thickness, porosity, andactive surface area will also affect the transport and kinetic phenom-ena within the cell, resulting in performance degradation and loss

of cycle life. A scientific understanding of the phenomena govern-ing the degradation of these parameters and their effect on transportand kinetic phenomena in large format cells is necessary in achiev-ing sustainable improvements in robustness, manufacturing cost, andcalendar and cycle life.

Several material characterization techniques such as scanningprobe microscopy, electron microscopy, X-ray diffraction andneutron-scattering and imaging have been used to study degrada-tion in the battery materials.33,55–60 However, these studies are oftenfocused on small and inappropriate formats such as coin-cells, givingaccess to analyze individual electrodes of the cell.61 Also, these tech-niques are used separately, and the results are not well coordinated.Such studies are very useful in addressing the intrinsic behavior ofthe active material, but the results of such studies cannot be directlyscaled to the large format cells used in vehicle electrification.

Coin-cells have very low capacity and high area specific impedanceand cannot be subjected to the levels of current and number of cy-cles common for large format cells. Electrode tortuosity, thickness,adhesion between the active material and current collector, amountof electrolyte, gas formation, etc. are different between coin-cells andlarge format cells, so the degradation mechanisms will not be exactlythe same in the two systems. Thus, in large format cells the hard-ware including the design, geometry, and manufacturing processeswill dominate performance, hence a detailed experimental frameworkis needed to comprehend the complex degradation mechanisms inlarge format Li-ion cells. Multi-scale characterization will help to un-derstand the cause-and-effect relationship between the observed phe-nomena and the degradation pathways due to the design, geometry,manufacturing processes, materials and operating conditions.

As shown in Fig. 6a and Fig. 6b when a LiFePO4 based commer-cial cylindrical cell is disassembled and the jellyroll is unrolled, thelength of each individual electrode is ∼1.5 m. As discussed earlier,in the LiFePO4 battery the active LiFePO4 material is synthesizedas a nanomaterial. One cannot randomly pick an area on the longcathode strip and hope to see the effects of the aging mechanismson the LiFePO4 nanoparticles. Exhaustive search over the entire elec-trode strips will be physically impossible with available microscopiccharacterization techniques. Thus to address this issue and still in-vestigate the cascading effects of various physiochemical process onthe electrode structure a multi-scale characterization plan is neces-sary for understanding the degradation mechanisms in commercialbatteries. Techniques such as SEM, TEM, XRD etc., are used hereto study various properties such as the morphology, phase transfor-mation, electronic properties, etc. Results of these characterizations

Figure 5. (a) Schematic of a cylindrical lithium-ion battery. The components are rolled and packed in a cylindrical case. (b) Schematic of a prismatic lithium-ionbattery. The components are stacked in layers and enclosed in a rectangular casing. (c) Schematic of a pouch cell. The components are stacked in layers andenclosed in a foil envelope.156,284


Figure 6. (a) A picture of a typical cylindrical cell. The cell is typicallyreferred to as 26650 where the diameter of the cell is 26 mm and the length is650 mm. The jelly roll of the cell components is also seen here. (b) A pictureof the dissembled and unrolled components of the cell. The strip on the left isthe cathode and the strip on the right is anode. The length of each electrode is∼1.5 m long and 25 mm wide.

are coordinated to focus on a specific location on the electrode sur-face. Thus the results are analyzed in conjunction with each other andat different length scales based on the technique. As a result, thesestudies provide a comprehensive understanding of material degrada-tion with spatial resolution.

Several experimental techniques shown in Fig. 7 were chosen toaddress physical/morphological changes, electrical changes as wellas chemical and structural changes in the cathode material. The tech-niques were spanned over different length scales to understand theeffects of aging on these cathode design parameters. Thermographywas chosen as the starting technique to scan the entire length of the

cathode strip and identify the potential areas of degradation. It isassumed that changes in the thermal properties also affect the elec-trical properties of the material. Based on the thermal maps the sam-ples were prepared for further analysis with SEM, AFM and TEM.The capacity curves and the internal resistance are the aging metricsat the system level. But to understand the effects of morphologi-cal changes on electrical properties of the material at micro/nanoscale, characterization techniques such as SSRM and KPM availablewith AFM were included. Chemical and structural analyzes tech-niques were chosen to investigate the local chemical changes, thelocal Li environment and its bonding with neighboring elements inthe LiFePO4 crystal structure, as well as to identify the effect of ag-ing on the Li concentration profiles within the electrodes. The resultsof these characterization studies are discussed in section 4, 5, and 6.But before we present these results, in the next section we will dis-cuss the preparation of aged cells for characterizing the degradationmechanisms.

Aging Cycles for Li-Ion Batteries

Aging or cycling of the batteries for aging studies is very critical formaterial characterization. The aging cycles should be representativeof an actual charge/discharge cycle a battery would experience in thevehicle. The operating temperature, SOC, DOD and the C-rate aregenerally considered to be the main factors affecting the aging ofbatteries. The general terminology for Li-ion battery packaging andoperating parameters is given in Appendix A2. As such these factorsneed to be included in the aging cycles. Thus designing the agingcycles based on actual cycle is a daunting task.

Typical driving cycles have been developed to represent the drivingconditions experienced in the real world usage of the vehicle. Thesedriving cycles are developed to quantify the fuel consumption andgreenhouse gas emissions for different driving conditions. The typicaldriving cycles developed for the US are FTP-72 or Federal urbandriving cycle (FUDS), FTP-75, US06, SC03, NYCC, and HWFET.Among these driving cycles the FUDS and US06 driving cycles areused to simulate driving in different routes. The FUDS representsdriving on an urban route while US06 represents a more aggressivehighway driving. Using these various cycles the fuel consumptionand the greenhouse gas emissions can be measured for various typesof trips. These driving cycles represent certain energy demand at thewheel. Thus it gives energy demanded from the primary source on thevehicle.

There are several different types of electric vehicles based onthe primary and the secondary source on the power. In a purely EVthe primary and the only source of energy is a battery. The batteryoperates in the charge-depleting mode and can only be charged byplugging into an external power source. Hybrid vehicles have two ormore sources of power that are directly or indirectly coupled with thedrive train. The primary source in hybrid vehicles is usually internalcombustion engines (ICE) and the secondary source is the battery.In HEV the primary source is the ICE and the secondary batterysource is used intermittently and is used in the charge-depleting andthen charge-sustaining mode and the control strategy determines therange of operation of the battery. The PHEV combines the advan-tages of the EV and HEV. The battery can be used over a largerrange and it can be charged directly by plugging into the externalpower source. The ability to charge the batteries through an externalpower source adds to the complexity of reproducing the aging cy-cle of the battery as the external charging would depend on severalfactors such as users choice of charging time, duration and loca-tion. Since the operating currents and the SOC ranges for the batterysystems are different in these different types of battery electric vehi-cles, the performance requirements are also different as discussed insection 1.

A synthetic driving cycle for HEV application was developed by.62

The temperature and the SOC were obtained from the operating con-dition and the initial charge. The DOD and the C-rates were extracted


Figure 7. A chart displaying the various techniques used at different length scales for multi-scale characterization of the materials.

from the real data. Figure 8a shows the real driving data in HEV ap-plication that was used in this study. The real current profile (I) in theactual cycle is normalized with the nominal capacity of the pack (Sc):

Crate = 1

Sc[3.1]

This normalized current profile is shown in Fig. 8b. This currentprofile is then discretized into 2-C length bins and the histogram isgenerated as shown in Fig. 8c. The number of bins is chosen to beas small as possible but also to capture the main aging effects. Thenusing the heuristic design based on the statistical distribution approacha synthetic aging cycle as shown in Fig. 8d, which is easy to implementin the laboratory, is generated.

As stated earlier the batteries in EV are operated in charge depletingmode while batteries in the HEV and PHEV are operated in chargesustaining mode. Using this control and the synthetic aging cycledesign Marano et al.63 were able to generalize the operating range forthe batteries in various EVs. As batteries are the only source of energyin EV they operate at a much lower C-rate and a higher range of SOC.While in HEV the SOC range is smaller but the C-rate is high. PHEVoperate within these two extremes with moderate SOC and C-rate.Thus aging cycles in these types of studies are carefully designedbased on the vehicle applications. Also as temperature affects theoperation of the batteries, it can be included as one of the parametersin the aging cycle.

Nagpure et al.64–69 have demonstrated multi-scale characterizationstudies on commercial LiFePO4 cells in their various published work.

The cells that have been used in these studies were cylindrical cells.Though more recently prismatic cells have been used for electrificationof automobile, these cylindrical cells were used in a replacement kit forToyota Prius. The cells were cycled at a lower SOC and lower C-rate.Commercial lithium ion cells used in these experiments had a graphiteanode and a cathode comprised of LiFePO4 nanoparticles (40 nm–50 nm). Graphite is bonded onto a copper substrate, and layers ofLiFePO4 nanoparticles are bonded onto an aluminum substrate usinga polyvinylidene difluoride (PVDF) binder. The anode and cathodestrips, with a separator in between, are rolled and then packed intoa can to form a cylindrical cell. The electrolyte used in this cell isa lithium hexafluorophosphate (LiPF6) salt in 1:1 ethylene carbonateand dimethyl carbonate. The cell has an operating voltage of 3.3 V anda nominal discharge capacity of 2.3 Ah. LiFePO4 has poor electronicconductivity (σ = 2 × 109 S cm−1).70 To improve the conductivity,the nanoparticles are coated with carbon.71

Table VI describes the condition of the cells, which were used intheir study. The effect of charging or discharging current rate (C-rate)was studied with cells # C1, C3, and C4 cycled from 0% to 10% stateof charge (SOC) with a C-rate of 1C, 3C, and 4C, respectively(1C = 2.3 Ah). Two cells were cycled with higher C-rates and athigher SOC to study the effect of the SOC on the lithium concentra-tion profiles. Cell C6 was cycled from 60% to 70% SOC with 6C rate.Cell C16 was cycled with the highest C-rate of 16C from 45% to 55%SOC. All the cells were cycled at 45◦C. A cell that underwent only onecomplete charge-discharge cycle was established as the baseline cellin these studies (C0). The cycling of the cells was terminated when the


Figure 8. Synthesis of aging cycle from real life driving cycle. (a) Current profile for a battery pack during a real HEV driving cycle. (b) Current profile expressedin the terms of C-rate for a cell during a HEV driving cycle. (c) Current distribution histogram for the cell during a HEV driving cycle. (d) Synthesized currentprofile designed for aging the cell in the lab. This profile has same current distribution histogram as in (b) (adapted from Spagnol et al.62).

cells reached ∼80% of their rated capacity. This protocol was found tobe consistent with the automotive industry standard, which considersa cell to be dead when its capacity drops below 80% of the originalrating.14

The cells were completely discharged after they had reached the∼80% of their rated capacity. The cylindrical cells, C0, C1, C3, C4,and C6 were opened in a glove box filled with Argon atmosphere.The oxygen level was maintained at ∼88 ppm and the dew pointwas ∼−34◦C. The cell was unrolled, and the long anode and cathodestrips were separated. Each electrode strip was then divided into sixsections. Section # 1 is near the outer circumference and section# 6 is near the center of the cylindrical cell. Cell, C16 was opened inan ambient environment and the cathode and anode strip was dividedinto five sections.

Wang et al.,72 has also reported an on-going extensive acceleratedcycle life study for graphite-LiFePO4 cells. Their test matrix includesthree parameter, C-rate, DOD and temperature. The C-rate valueschosen for the tests are C/2, 2C 6C and 10 C with 1C = 2Ah. At eachC-rate the DOD values are 90, 80, 50, 20 and 10%. Two cells per C-rate and DOD combination are being cycled at temperatures −30◦C,0◦C, 15◦C, 25◦C, 45◦C, and 60◦C. They have reported an empirical

Table VI. Aging cycles.

Sample Aging Condition Residual Capacity

C0 New- No aging 100%C1 1C, 0–10% SOC, 45◦C ∼80%C3 3C, 0–10% SOC, 45◦C ∼80%C4 4C, 0–10% SOC, 45◦C ∼80%C6 ∼6C, 60–70%, SOC 45◦C ∼80%C16 16C, 45–55%, SOC 45◦C ∼80%

SOC - State of charge

model for cycle-life based on the cycle life data obtained from theseaccelerated aging experiments. We will briefly discuss this model insection 7.

Safari and Delacourt73,74 have also used a cycling protocol typicalof an EV application. In this profile the cell was first charged to 3.6 Vwith C/2 rate followed by a 30 min rest period and then dischargedwith a repeating power profile for 985 s and 10 min rest period in-between till the cell voltage dropped to 3 V. The power profile had 38charging and 159 discharging peaks of 5 s each resulting in an averageC-rate of ∼C/3.

Typical Aging Mechanisms in Li-Ion Batteries

The following is a review of the most commonly observed agingmechanisms across different lithium-ion cell chemistries. It is gen-erally understood that the aging mechanisms causing performancedegradation differ significantly for the anode and the cathode, whichis the topic of active research. These effects together cause the degra-dation in performance of the cell. Each aging mechanisms has a vary-ing degree of influence on the overall cell performance and it hasbeen a challenge to isolate the contribution of individual effects onoverall performance degradation. However, most capacity fade andimpedance rise is attributed to the formation and growth of a solidelectrolyte interphase (SEI).

Anode.— Solid-electrolyte interphase.— A side reaction thatcauses the decomposition of the reductive electrolyte and consumptionof lithium ions takes place between the electrode and the electrolytesurface in the lithium-ion battery systems.30 The decomposition prod-ucts are deposited on the electrode surface. This deposited layer istermed as a solid electrolyte interphase (SEI). The SEI layer consumesthe active lithium, and increases the impedance of the anode causingthe capacity and power fade of the cell at the system level. Though SEIcan be formed at both the anode and the cathode, it is more prominentat the anode surface due to the low potentials (vs Li/Li+) reached


during the charging of the cell that are beyond the electrochemicalstability window of most electrolyte solvents. As SEI is composed ofthe electrolyte decomposition products, it is understood that the chem-ical composition and properties of the SEI layer are dependent on theanode surface and the electrolyte solvents. Several electrolyte decom-position reactions have been reported in literature.75 Since carbonatesolvents are most common for the lithium-ion battery systems thereexists several studies related to the reduction reactions and subsequentformation of the SEI layer for solvents such as propylene carbonate(PC), dimethyl carbonate (DMC), and diethyl carbonate (DEC) andethylene carbonate (EC).74–79

SEI once formed during the initial cycling of the cell is consideredto limit the further reduction of the electrolyte and the corrosion of theanode surface. But the SEI layer conversion, stabilization and growthtakes place steadily throughout the life of the battery although at alower rate than at the initial stages.30 The rate of the SEI growth islimited by the kinetics of the decomposition reaction or the diffusionof the solvent molecules through the SEI layer.11 In general the growthof the SEI layer is accelerated at the elevated temperatures and thelower potentials of the anode.

The SEI formation, and growth is generally viewed as the primaryreason behind the performance degradation of the lithium-ion cell bycausing the capacity fade and the rise in the internal resistance. Severalmodeling efforts have demonstrated the loss of capacity due the SEIgrowth during the operation of the cell under various conditions.76,80,81

Lithium plating.— Lithium plating i.e. the process of depositionof the lithium metal occurs, at the anode surface as the anode poten-tial crosses the threshold of the 0 V (vs Li/Li+).30,82–84 Apart fromconsumption of active lithium leading to loss of capacity, the lithiumdendrites formed during the plating process can tear through the sep-arator and cause a short circuit and immediate failure of the battery.

The lithium plating in case of the carbonaceous electrodes is causedwhen the rate of intercalation of the lithium ions into the carbonaceouselectrode is too slow and/or the transport of the lithium ions to the elec-trode surface is very high. At temperatures lower than room tempera-ture the diffusion of the lithium ions into the carbonaceous electrodeis slow requiring a higher overpotential to maintain the given net cur-rent, and thus causing the lithium plating at the surface. Fang et al.,85

have demonstrated the temperature dependence of the overpotential inthe negative electrode. Furthermore the lithium plating can also occurdue to debalancing of the cell (e.g., excess of cathode material),86

geometric misfits30 and local polarization of the electrode.11,30,87,88

Cathode.— Structural changes and mechanical stress.— Lithia-tion and delithiation of the host structure during each cycle of the cellcauses the molar volume change of the host structure. This volumechange in the crystal structure leads to the structural changes of theanode and cathode. Such a structural change affects the performanceof the cathode more than the regular carbonaceous type anode. Thestructural changes can induce mechanical stresses and strains in thenanoparticles of the active cathode material, which subsequently acton the composite cathode structure.30

During the lithiation and delithiation process some cathode oxidesalso undergo phase change. This phase change can cause the distortionof the crystal lattice further inducing mechanical stresses.30 The misfitstrains at the phase boundaries lead to discontinuities causing thecracking of the nanoparticles.30 There have been several modelingefforts to understand the crack formation and propagation due to themechanical stresses and strains in the cathode nanoparticles.89–96

Dissolution of active material.— Aging due to dissolution of activematerial is mostly observed in the Mn based cathode material. Thoughit has been reported in Mn layered oxide and olivine structured cathodematerials, it is most serious in the spinel structured Mn cathode,especially at elevated charged states and temperatures.30,97–108 Thedissolution reactions proceeds as:

2Mn3+ → Mn4+ + Mn2+ [4.1]

The divalent manganese ions dissolve in the electrolyte while thetetravalent manganese ions remain in the solid structure. The disso-lution of Mn in the electrolyte has two-fold effect on the aging ofthe cell. First, the dissolution of Mn leads to capacity fade associ-ated with the loss of active material. Second, the dissolved Mn ionsmigrate to the negative electrode and are deposited on the surfaceof the electrode and/or incorporated in the SEI. This enhances theelectrolyte decomposition process causing the loss of charge in thelithiated carbonaceous anode.109,110 Vetter et al.,30 also mention theprecipitation of Mn species such as MnF2, MnCO3 and various oxideson the cathode surface increasing the impedance of the electrode.

So far, only Park et al.111 and Cai et al.112 have modeled the dis-solution process, but these studies accounted only for the loss of theactive volume and neglected the effect of the dissolved Mn ions onthe negative electrode. As interest in mixed electrodes containing Mnincreases, more efforts to understand the effect of the Mn dissolutionon the aging process will be needed.34–40

Multi-Scale Characterization of Cathode - Physicaland Morphological

In this section the various techniques used to characterize thephysical and morphological structure of the aged cathode materialsare discussed. Physical and morphological studies will reveal anydamage to the LiFePO4 cathode during the aging process. The char-acterization of evolution of main design parameters such as porosity,and particle size are discussed in this section. Thermography is usedto scan the long cathode strips for any physical damage and bridgethe gap between the millimeter to micro-nanometer length scales. Theporosity analysis has been done with X-ray micro-computed tomog-raphy and finally the aging effect on particle size is analyzed down toits fundamental length scale.

Physical damage.— Physical damage to the composite cathodestructure can cause degradation in its performance. Stresses due tothe packaging of the cell, cycling of the cell during operation, andheat generation can lead to physical damage such as delamination ofthe active material from the current collector. The areas with physicaldamage will be sources of inhomogeneities within the cell and lead torapid degradation in performance.

Also, as discussed earlier one cannot randomly pick an area on thelong cathode strip and hope to see the effects of the aging mechanismson the LiFePO4 nanoparticles. Exhaustive search over the entire elec-trode strip will be physically impossible with available microscopiccharacterization techniques.

The physical damage of the long cathode strip can be analyzed withan imaging technique such as Thermography and Optical microscopy.Thermography (mm).—Thermography is used to measure the vari-ations in temperatures through thermal imaging of the object. Herethermography by flash method is used as the first step in the multi-scalecharacterization of the LiFePO4 cathode material. The flash method,which was introduced by Parker et al.,113 has been used extensively inthe measurement of thermal characteristics such as thermal diffusiv-ity, and thermal conductivity of various different kinds of materials. Inthis simple technique the front face of the sample with slab geometryreceives a pulse of radiant energy coming from a laser or a flash lamp.The temperature rise of the opposite face is captured through highresolution, high frequency thermal imaging by an infrared (IR) cam-era. The average temperature rise in the sample is only few degreesabove the initial value. This temperature rise curve is used for thermalcharacterization of the samples.114,115

Several authors have successfully applied this technique forseveral different materials. Lafond-Huot and Bransier,116 Luc andBalageas,117 Philippi et al.,118 Degiovanni et al.,119 and Krapez120

used it to study anisotropic materials. Batsale et al.121 and Ramondet al.122,123 used it to study complex heterogeneous media. Moyneet al.124,125 and Azizi et al.126 studied porous materials. Andre andDegiovanni,127 Hahn et al.,128 and Lazard et al.129 applied it to study


Figure 9. Schematic of thermal diffusivity measurement by Flash Method(adapted from Anonymous140 and Nagpure et al.65).

semi-transparent materials. Coquard and Panel130 used it to study liq-uids or pasty materials. There are also several reviews published aboutthe theoretical and practical applications of this technique by Righiniand Cezairliyan,131 Degiovanni,132 Taylor,133 Balageas,134 Taylor andMaglic,135 Maglic and Taylor,136 Sheindlin et al.,137 Baba and Ono,138

and Vozar and Hohenauer.115,139

As large areas can be easily scanned with this technique, it be-comes an ideal choice to scan the long cathode strips for any physicaland/or morphological damages. Nagpure et al.65 have demonstratedthe application of this technique in battery research by capturing 2Dthermographs of the cathode strips harvested from unaged and agedcommercial cells. The setup to capture the thermal maps of the sam-ples is discussed in ASTM 1461 92 standard140 and is shown in Fig. 9.The main features of this setup are the flash lamp, sample mount, high-resolution IR camera, and data acquisition system. The high energypulse required in this experiment was generated by Profoto, Acute 2,flash lamp with a 2400 W-s capacity. The flash lamp was operated todeliver a finite pulse of energy at 300 W-s. The sample mount was acustom made hollow box with a square slot of approximately 63.5 mm× 63.5 mm on one face. The flash lamp was centered over this slot. Acircular hole of approximately 90 mm was cut on the opposite face.The IR camera lens was inserted through this hole and focused on thesample. The thermal maps were taken with an IR camera from IndigoSystems, Phoenix Mid-wave IR Camera, with a 320 × 256 pixel res-olution and InSb focal plane array. The frequency of the camera is setat 346 Hz. The data acquisition system was built into the IR cameraequipment.

The long cathode strip was divided into five equally spaced sectionseach ∼65 mm (2.5 in) wide. The sample was mounted flushed on theface with the square slot on the sample mount. The center of the flashlamp coincides approximately with the center of the sample so that theheat pulse is uniformly incident on the sample. The IR camera lens wasfocused on the opposite face of the sample with the center of the lensaligned approximately with the center of the sample. The finite heatpulse from the flash lamp was incident on the front face of the sample.The heat gained by the sample from this pulse is conducted throughits thickness to the rear face. As such the rear face of the sample isheated and its temperature increases. The IR camera captures this heatgained by the rear face at a frequency of 346 frames per second. Theexperimental setup was under ambient conditions and as such all thethermal maps were obtained under ambient conditions.

The thermal maps of the aged and unaged sample for all fivesections (Fig. 10a), shown in Fig. 10, were taken when the temperatureof the rear face of the sample reached the maximum value. In thesethermal maps the dark spots represent the cold areas while the brightspots represent the hot areas. The dark spots are more prominent inthe aged sample (right side) as compared to the unaged sample (leftside).

Figure 10. (a) Sectioning of the cathode for the thermal imaging. Section# 1 is near the core of the cylinder and section # 5 is near the out edge of thecylinder. (b) Thermal maps of unaged and aged cathode samples for all fivesections.65

The dark spots are mostly in areas where the spalling of the cathodematerial from the current collector was observed. The spalling couldbe attributed to the disbonding, cracking or buildup of residual stressand strain between the current collector and the cathode materialinterface. The spalling could also be attributed to the shocks andvibrations during disassembling of cells and/or handling of the longcathode strip. Thus the reason for spalling could not be conclusivelyattributed to any specific damage mechanism. Since spalling was aresult or effect of certain underlying damage mechanism the agingstudies were focused on areas without any visible damage.

Thermal diffusivity was used as a damage metric in the areaswithout any visible damage (no spalling). Figure 11a shows the tem-perature rise of the rear face of the sample in terms of IR counts. Thetemperature rise shown here is for section # 4 of the aged and theunaged cathode samples shown in Fig. 11b. An area with a uniformIR intensity was randomly chosen in the thermal map of the aged andunaged sample for thermal diffusivity analyzes. The IR counts areobtained over this area from the instant the heat pulse was incidenton the sample until the temperature of the sample reaches a steadystate value. A baseline temperature was identified in these plots as thetemperature just before the pulse is incident on the sample (Tini). Thenthe maximum temperature was measured as the steady state temper-ature of the rear face of the sample (Tmax). The half rise time (t1/2),i.e. the time required from the initiation of the pulse on the front face


Figure 11. (a) Temperature rise curves for unaged and aged samples (section# 4). (b) Comparison of thermal diffusivity between unaged and agedsamples.65

of the sample to the time at which the temperature of the rear faceof the sample reached half the difference between Tini and Tmax, wascalculated. The thermal diffusivity for the sample was then calculatedusing the following formula:140

α = 0.13879L2

t1/2[5.1]

where α is the thermal diffusivity (m/s), L is the thickness of the sample(m), and t1/2 is the half rise time (s). It is important to note that theEq. 5.1 is not dependent on the absolute value of Tmax. Therefore, theobserved differences in maximum IR counts between aged and unagedsamples as seen in Fig. 11a are not important in these analyzes.

Figure 11b shows a comparison of the thermal diffusivity betweenthe unaged and the aged sample over all 5 sections. As can be seen inthis figure the thermal diffusivity of the aged sample was more thanthe unaged sample in all 5 sections. This indicates that the rate of heatconduction in aged samples is higher than the unaged sample, whichcan be attributed to the change in the porosity of the cathode mate-rial. The differences in the thermal diffusivity values between agedand unaged samples are significantly less in sections 1 and 5. Thesesections are near the core of the cylinder and near the outer edge ofthe cylinder, respectively. The differences in the thermal diffusivityare more prominent in sections 2, 3, and 4 of the samples. Nagpureet al.65 believed that the different rate of change in the porosity in vari-ous sections leads to the non-uniform change in the thermal diffusivityacross the sections.

Theoretically, thermal diffusivity is given as the ratio of the thermalconductivity to volumetric heat capacity as follows:

α = k

ρCp[5.2]

where α is the thermal diffusivity (m2/s), k is the thermal conductiv-ity (W/m-K), and ρCp is the volumetric heat capacity (J/m3K). The

Figure 12. Schematic of a proposed mechanism explaining increase in thethermal diffusivity of a LiFePO4 cathode due to aging.65

Eq. 5.2 is strictly applicable only to monolithic material. Since, thecathode material is a composite, Nagpure et al.65 associated the in-crease in thermal diffusivity with a change in k, ρ and/or Cp .

Figure 12 shows the schematic of a proposed mechanism explain-ing the increase in the thermal diffusivity of a LiFePO4 cathode due toaging.65 As a first order approximation the cathode can be consideredas a porous medium. Also, it can be assumed here that the heat diffusesthrough the cathode only due to conduction. As the cathode ages thenanoparticles tend to coarsen by sintering. Due to this sintering of thenanoparticles, the effective surface area per unit volume decreases,141

with an associated decrease in the porosity of the cathode. The de-crease in the porosity can also expose a larger area of the aluminumcurrent collector. Since aluminum has high thermal diffusivity (8.418× 10−5 m2s−1), the overall thermal diffusivity of the aged samplemay show an apparent increase.142–144 It is interesting to note thatthe sintering of oxide particles takes place at high temperatures. Theonset of sintering in the cathode material may be attributed to the highsurface energy of the LiFePO4 nanoparticles Zhang and Miser145 hasobserved coalescence of oxide particles with no external heating. Ingeneral, as the porosity of the medium decreases, the thermal conduc-tivity increases, and hence, the aged sample shows increase in thermaldiffusivity.146,147

In summary thermography bridges the gap between different lengthscales and proves to be an effective technique to relate the damagemechanisms of the cathode at mm length scale to micro/nanoscale. Thethermal diffusivity increases as the cathode ages during the cycling ofthe batteries. The increase in the thermal diffusivity was attributed tothe decreased porosity of the cathode samples due to the coarseningof the LiFePO4 nanoparticles. The 2D thermal maps and the thermaldiffusivity calculations help in making samples for further micro/nanolevel characterization studies.Digital microscopy (microns).—Advances in the lens design and man-ufacturing has helped the development of the high-resolution opticalmicroscope. Issues such as optical aberrations, and blurring of theimages have been overcome in modern optical microscopes. Coupledwith these advances, the advances in digital imaging have led to thedevelopment of the digital microscope. In digital microscopes theeyepiece of an optical microscope is replaced with a charged coupleddevice camera. Digital microscopes provide added advantages of pre-cise computer control and greater flexibility in image analysis andprocessing. They have been used regularly in the fields of biologicalsciences, nanotechnology, as well as material science and metallog-raphy. They are very useful in imaging the texture of samples formetallographic analysis.

Digital microscopy has not been used as widely as other techniquesin the study of battery materials. Figure 13 shows the digital micro-graphs of the unaged and aged anode and cathode taken along the


Figure 13. (a) Digital micrographs of unaged and aged graphitic anode acrossthe thickness. (b) Analogous images of LiFePO4 cathode.

cross-section (thickness) of the electrode strips. They are very usefulin understanding the basic construction and layout of the electrodestrips. In Fig. 13a the middle vertical region represents the coppercurrent collector. The graphite coating is seen on either side of thiscurrent collector. Similarly, in the case of Fig. 13b the middle shinyvertical region in the images is the aluminum current collector. Theactive material (LiFePO4) is coated on either side of this current col-lector substrate. Due to the dense packing of the active material thenanoparticles structure is not visible at the resolution available inthese images. The edges of the current collector have been smearedoff and the coating of the active material is not uniform on either sidein the case of the aged sample. Using the digital image processingtechnique on these micrographs the thickness of the current collectorand the coatings on each side is measured as ∼10 μm and ∼75 μm

respectively. This data is a very useful input to the battery performanceelectrochemical models.148

When lithium intercalates into the graphite anode it changes color,and this behavior has been used to characterize the graphite anodewith optical microscopy. Maire et al.149 have used calorimetery incombination with optical microscopy to determine the local state ofcharge and lithium distribution with the anodes of the Li-ion cell.Harris et al.83 have used optical microscopy to study lithium transportin the anodes and have suggested that the transport phenomena couldbe controlled by liquid-phase diffusion. Qi and Harris150 have usedoptical microscopy to study the strains in the graphite anode duringthe lithiation process and explained the stiffening of the graphite uponlithiation.

In summary, digital microscopy contributes very little toward iden-tifying the degradation mechanisms of the cathode material. It is un-clear if the uneven active material coating thickness is a manufacturingdefect or an aging effect. Nonetheless these studies provide importantinformation about the physical dimension of the cathode and an-ode, which are useful in the electrochemical modeling of the batteryperformance.

Porosity analysis.— The cathode is a porous structure to assistthe percolation of electrolyte and to increase the surface area for theelectrochemical processes. The change in porosity during the cyclingof the battery can disrupt the ionic and electronic conductivity ofthe cathode structure. The change in porosity leads to change in theinterface carbon coated nanoparticles and the electrolyte percolatingthrough the pores of the composite cathode affecting lithium intercala-tion efficiency during cycling. Hence, characterizing and quantifyingporosity becomes important in understanding battery performance andto improve the design of large format cells.

X-Ray tomography has been used to characterize battery graphiteanodes of Lithium cobalt oxide batteries harvested from a Lishen18650 cylindrical cell151 to study pore size distribution, pore intercon-nectivity and tortuosity. Channagiri et al.152 have used X-ray microcomputed tomography (X-ray microCT) to characterize the evolutionof porosity with aging in large format cells. Since the pores are inthe nanometer to micrometer range and beyond the resolution of theirX-ray microCT instrument they have used an indirect method to cal-culate the porosity within the samples. Grayscale values for each pixelon X-ray micro-CT images are proportional to the linear attenuationcoefficient at that point of the object being scanned. The gray scale ofthe X-ray microCT images were calibrated based on the attenuationcoefficient of air and LiFePO4 and FePO4 and the weight fraction ofthe pores (wP ) within the sample was calculated using the followingrelation

wP = (GS − GSL )

(GSP − GSL )[5.3]

where GS is the gray scale value in the image, GSL is the gray scalevalue for LiFePO4 and FePO4 and GSP is gray scale value of air.

In Fig. 14a–14d, the first four plots (a, b, c &d) are normalizedintegrated histograms representing porosity distribution at location 1and location 5 for a given aging condition, while plots in Fig. 14e–14fare normalized integrated histograms representing the porosity varia-tion at location 1 and location 5 with different aging conditions. Thedifferent porosity in location 1 and location 5 of the new unaged cellindicates the influence of packaging and building of the cell. Suchvariation can lead to inhomogeneities within the cell causing perfor-mance degradation. Channagiri et al.152 have attributed this variationwithin the new unaged cell to the stresses built during packaging ofthe cylindrical cell. They have attributed the change in the porosity incells aged at a higher C-rate to the rapid cyclic volume changes at ahigher C-rate that cause loss of contact between cathode nanoparticlesand the carbon matrix during the cell aging process.

Particle size.— The diffusion length and diffusion time dependson the particle size of the active LiFePO4 cathode samples. Changein the particle size during the aging can cause change in the diffusion


Figure 14. Normalized integrated histograms showing variation in porosity between location 1 and location 5 within a battery sample, demonstrating an increasein porosity away from the center of the battery (except in the unaged battery case) (a) C0, (b) C2, (c) C4 and (d) C7; Normalized integrated histograms showingvariation at different locations for the set of batteries (e) location 1 and (f) location 5. No change in porosity is observed at location 1 while the porosity increasesat location 5 with aging at different C-rates.152

kinetics affecting the rate performance of the cell. The particle size hasbeen analyzed using micro and nanographs generated with electronmicroscopy and scanning probe microscopy.

The samples for the particle size analysis were made usingthe thermal images obtained in the thermography study. The areaswhere thermal conductivity changed but no visual damage to the

cathode structure was shown are the areas of interest for particlesize.Scanning electron microscopy (SEM) (microns).—SEM is widely usedas a non-destructive tool for characterization and analysis of materi-als. The focused high-energy electron beam incident on the samplegenerates signals that are analyzed for the morphology. A SEM with


Figure 15. SEM micrographs of unaged and aged LiFePO4 cathode samplesextracted from section # 4 [Nagpure et al., 2010].

electron back scattering detector can also be applied to study thecrystal structure, chemical composition, and material orientation.SEM is widely used in lithium ion battery research to produce highmagnification images of the nanostructured active materials. It is of-ten used to understand the morphology of the synthesized cathodematerial and to verify the nanostructure of the material.71 SEM can beused to identify the major physical and or morphological structuresin the active materials. Such studies can reveal any particle cracking,particle separation, and particle agglomeration.153

Figure 15 shows the SEM micrographs of the samples harvestedfrom the unaged and aged cells obtained by Nagpure et al.65 TheSEM micrographs reveal the coarsening of the nanoparticles in theaged samples as compared to the unaged sample. The particles in theunaged sample are of the order 40–50 nm while in the aged samplethe particles are of the order 240–350 nm. As can be seen in theFig. 15, in commercial batteries the active material is densely packedon the current collector. Thus higher resolution and magnificationSEM images would be necessary to analyze the particle size and itsdistribution on the cathode surface to study the effect of the coarseningon the overall performance characteristics of the battery.

The coarsening of the particles leads to a decrease in the effectivesurface area of the particles affecting the rate of the reaction. Thechange in the particle size would also affect the diffusion kinetics of thelithium ions during charging and discharging cycles. The coarseningphenomenon can also lead to the disbonding of these particles fromthe aluminum substrate causing physical failure or cracking of theactive material and to the increase in the internal resistance due to lossof contact. The coarsening can also lead to the separation of particles,leading to the loss of contact between particles.Atomic force microscopy (AFM) (μm-nm).—Since its development byBinnig et al.,154 AFM has played a vital role in surface characterizationof various different materials such as semiconductors, insulators, bio-materials, etc. A sharp tip at the free end of a flexible cantilever scansthe surface of the sample to measure the surface topography of thesample.155

A brief review of the AFM techniques used in Li-ion battery re-search has been pro- vided by Nagpure and Bhushan.156 This techniqueprovides surface morphology maps of the cathode samples with mi-cron to nm resolution. These maps are useful in studying the graincoarsening phenomena.66,157 Figure 16 shows the AFM surface heightimage of the LiFePO4 cathode sample harvested from the unaged andaged cells. As can be seen from the images, the LiFePO4 nanoparticlestend to coarsen in the aged samples as compared to the unaged sam-ples. The same phenomenon was observed with SEM micrographs atmicron length scales. The AFM surface height images have higherspatial resolution than the SEM micrographs. Hence they might bemore useful in statistical quantification of the particle size distribu-tion. Along with this standard measurement, AFM modules are alsohelpful in measuring surface electrical properties.Transmission electron microscopy (TEM) (nm).—TEM is a highlyeffective and versatile electron microscope technique to image, an-

Figure 16. Surface height maps of a LiFePO4 cathode sample harvested fromunaged and aged cells (adapted from Nagpure et al.64).

alyze and characterize the materials at length scales of the order ofnanometers.158 Some of the application of TEM in lithium ion batteryresearch has been for studying nanoparticle morphology, and phasechange in the nano particles.159–161 In a multi-scale characterizationplan TEM is used to provide high-resolution images of the cath-ode samples for understanding the particle morphology at nanometerlength scale.

TEM, though very useful for high-resolution imaging, requires avery careful sample preparation, which should be thin so that theyare electron transparent. The TEM samples were prepared on a FEIHelios 600 -Dual beam, focused ion beam system (FIB). The TEMsamples were extracted from the surface through the thickness of thesample using lift-out technique. The lift-out technique used here hasbeen discussed in Giannuzzi et al.162 and Giannuzzi and Stevie.163

The steps followed in the lift-out technique used by Nagpure et al.68

are shown in Fig. 17 and briefly discussed here. A clean area is foundon the sample and imaged with the ion beam (1). Then Pt is depositedon the surface using a very small current of 2.8 nA (2). The sample isturned by 20deg in one direction, and the area around the Pt depositis milled away using a milling current of 9.3 nA. A similar step isrepeated to mill the area on the other side of the Pt deposit (3). Thesample is then turned by 7◦, and a trench is cut along the depth of thesample (4) to extract the TEM foil. In step 5 the omniprobe is attachedto the foil, and the foil is pulled from the rest of the sample. The foilis then welded onto a TEM Cu grid (GRD-0001.01.01) using Pt (6)and detached from the omniprobe. Finally, the foil is further thinnedto approximately ∼200 nm using the ion beam to make it electrontransparent.

Morphologies and nanostructures of the LiFePO4 samples areshown in the TEM images (Fig. 18). They have the same global mor-phologies. Particles of the aged sample were bigger than the particlesof the unaged samples. The samples have several layers of nanoparti-cles and, as such, contrast exists among the overlapping particles. Thismakes particle size analysis difficult, but the coarsening phenomenonis clearly visible in Figure 18b. Good statistical analysis of the coars-ening and the particle size variation can only be achieved with a moresubtle TEM sample extraction process that would allow quantitativemeasurement of the relative fractions of agglomeration and sintering,without destroying the configurations observed in the Figure 18.

Recently, in situ TEM methodology was developed for studying theprocesses and aging effects that cannot be captured by ex-situ studies.The critical part of such studies was to operate the LI-ion systeminside the ultra-high vacuum column of a TEM. To mitigate thissituation, the liquid electrolytes are replaced with either the ceramicor polymer electrolytes to construct an all solid-state “nano-battery”.The electrode/electrolyte interface can then be easily probed withTEM. Significant research efforts are underway for developing suchin situ TEM techniques to probe the electrochemical behavior of the


Figure 17. Steps showing TEM sample preparation using FEI Helios 600 dualbeam focused ion beam system (FIB).68

materials at nanoscale. Some of the earlier work in this area has beenpublished by Brazier et al.,164 Huang et al.,165 Wang et al.,166,167 andYamamoto et al.168 But these studies were focused on anode materialsfor lithium batteries. As such authors would leave this up to the readerto investigate it further, but would point out that such a study is alsoviable and important for the cathode materials within the lithium ionbatteries.

Summary.— The electrodes within the commercial battery havebeen characterized by several different techniques for physical andmorphological changes with resolutions ranging from mm to nm.Techniques including thermography, SEM, AFM and TEM prove veryhelpful in characterizing the long cathode strip from mm to nm lengthscales.

The thermal maps along with the thermal diffusivity measurementbridges the gap between different length scales and proves to be aneffective technique to relate the damage mechanisms of the cathodeat mm length scale to micro/nanoscale. The samples for micro/nanostudies are extracted based on the degradation observed on 2D thermo-graphs. The thermal diffusivity increased as the cathode ages duringthe cycling of the batteries. The increase in the thermal diffusivity wasattributed to the decreased porosity of the cathode samples due to thecoarsening of the LiFePO4 nanoparticles.

The physical/morphological studies reveal the main aging effectas the coarsening of the LiFePO4 nanoparticles. A schematic of thecoarsening phenomena is shown in Fig. 19. The average particle size

Figure 18. (a) TEM images of unaged and aged LiFePO4 cathode samples atlower magnification (b) TEM images of unaged and aged LiFePO4 cathodesamples at higher magnification. The images are from the central area in (a).68

increases during aging of the battery. The coarsening of the nanopar-ticles is visible in the SEM micrographs, AFM surface height images,as well as high-resolution TEM images.

The coarsening has several effects on the performance of thebattery. The coarsening of the particles leads to a decrease in theeffective surface area of the particles affecting the rate of the re-action. Change in the particle size would also affect the diffusionkinetics of the lithium ions during charging and discharging cy-cles. The coarsening phenomenon can also lead to the disbondingof these particles from the aluminum substrate, causing physical fail-ure or cracking of the active material and an increase in the inter-nal resistance due to loss of contact. The coarsening can also leadto separation of particles, leading to loss of contact between theparticles.

Figure 19. A schematic showing coarsening of the LiFePO4 nanoparticlesduring aging of the battery (adapted from Nagpure et al.64).


Figure 20. (a) A typical set of discharge curves (voltage versus time) is shown.The knee of the voltage curve is approached faster as the capacity of the celldecreases. (b) Internal resistance increases with aging of the cells."

Multi-Scale Characterization of Cathode – Electricaland Electrochemical

In this section the various techniques used to characterize theelectrical performance of the aged cathode materials are discussed.The physical/morphological characterization showed the coarseningof the LiFePO4 nanoparticles in the aged cathode samples. The effectsof this coarsening phenomenon on the electrical properties of the cath-ode material are studied through different scanning probe techniques.At the system level the charge/discharge curves and the change in theinternal resistance are used as the metrics to characterize the electricalperformance of the batteries.

Capacity fade and resistance increase.— At the system level theperformance of the cell can be directly measured by comparing thecapacity and the internal resistance of the cells at beginning of life andthe end-of-life. During aging of the cell periodic capacity test are doneat low C-rates. The internal resistance increase is the measurement ofthe power fade due to the aging of cells.

Continuous cycling of a battery leads to capacity fade and to anincrease in the internal resistance. The capacity and the internal re-sistance are used as the metrics for measuring aging at the systemlevel. Figure 20a shows typical discharge curves of a LiFePO4 basedLi-ion battery cycled at 16 C-rate between 45 and 55% SOC. As seenin this figure, as the battery ages the knee of the discharge curve isapproached much earlier than expected. Thus the total current drawnfrom the battery is less as compared to the beginning of the life. Sim-ilarly, as seen in the Fig. 20b the internal resistance of the batterycalculated from the open circuit potential, the loading current and thevoltage drop due to the load increases during continuous cycling ofthe batteries.

In Fig. 21 the capacity and the internal resistance of the batteriesC3 and C4 are plotted against the cumulative Ah. The cumulative Ah is

Figure 21. Capacity drop and resistance increase in cells C3 and C4 for multi-scale characterization studies.


the total Ah used during charging and discharging of the cell. The datashows the drop in capacity and the increase in the internal resistanceduring the cycling of the batteries, and thus measures the performanceof the batteries according to the system level aging metrics. The dropin the capacity of the C4 battery is at a slightly higher rate as comparedto the C3. Also the overall increase in the internal resistance of theC4 battery seems to be higher than the C3. Thus the higher C-rate hasa negative effect on the performance of the batteries and the batteriestend to age faster at higher C-rates.

Surface electrical properties.— Here we summarize the changein the surface electrical properties such as surface resistance, surfaceconductivity and surface potential measured with scanning probe tech-niques. They show the effect of aging at the micro-nano meter scalein the composite cathode structure.Surface resistance.—Advances in AFM instrumentation has led to thedevelopment of a technique known as scanning spreading resistancemicroscopy (SSRM).155,169 The SSRM module used in AFM mea-sures the surface resistance between the conductive tip and the samplewhile the tip is scanned in contact mode across the sample surface. Themost important application of the SSRM technique can be found in themapping of carrier concentration inside a semiconductor device.170 Incontrast to SSRM, there also exists a method called current sensingAFM (CSAFM) to measure the surface current between the conduc-tive tip and the sample. This has been previously used in lithium ionbattery research. A review of AFM techniques used in electrical char-acterization of battery materials has been presented by Nagpure andBhushan.170

The nanoscale surface resistance measurements were taken byNagpure et al.156 with a Nanoscope IIIa Dimension 3000 AFMequipped with the SSRM application module. The conductive SCMPIT (Veeco Instruments) probes used in this study were coated withplatinum-Iridium on front and back side and had a nominal tip radiusof 20 nm. A known DC bias voltage of +1 V was applied between thesample and the conductive tip, and the current was monitored using alogarithmic current amplifier built into the SSRM sensor, as shown inthe schematic in Fig. 22.

The module applies the same bias to the 1 M� reference resistormounted inside the module. The resistance is then measured by acomparator that compares the current flowing through the sample tothe current flowing through the reference resistor. The output of theSSRM module is in volts. The module is calibrated by connecting

Figure 22. Schematic of the AFM-based resistance measurement techniquewhere the surface height is measured in contact mode, and the resistance ismeasured by the current resulting from the applied sample DC bias voltage.(The schematic is for Dimension AFM (Veeco Instruments, Inc.) (adapted fromAnonymous171).

several resistances of known value in the module instead of the tip-sample. For example, if 1 M� resistance is connected instead of thetip-sample, the output of the comparator is 0 V as the same currentflows from the sample resistance and the reference resistor. Thus a0 V output corresponds to a 1 M� resistance between the tip and thesample. When a positive bias is applied between the tip and the sample,the output voltage is inversely proportional to the surface resistancewhile it is directly proportional to the surface resistance if a negativebias is applied. The total resistance between the tip and the sampledepends on the contact resistance, the spreading resistance, and thebulk resistance. One of the resistances dominates the total resistancedepending on the contact force applied on the tip, the applied bias andthe condition of the sample material. Depending upon the material,when a high enough contact force and a suitable bias is applied, a stableelectrical contact is established between the tip and the sample, andthe total resistance measured will be the surface resistance dominatedby the contact resistance and the spreading resistance.171

Figure 23 shows the SSRM surface resistance image of theLiFePO4 cathode sample harvested from the unaged and aged cells.As the module configuration when +1 V is applied between thetip and the sample, the higher voltage reading represents lower sur-face resistance. The surface resistance scale on the unaged sample is0–2 V, while the scale on the aged sample is 0–20 mV. The lowervoltage output in the case of aged samples indicates higher surfaceresistance as compared to unaged sample. Thus surface resistanceincreases as the cells are aged.

Based on their results, Nagpure et al.64 have proposed a mecha-nism that leads to the increase in the surface resistance of the LiFePO4

cathode sample, shown in Fig. 24. When the tip scans over the sur-face of the sample a circular contact is formed between the LiFePO4

nanoparticles and the tip. As mentioned earlier, the LiFePO4 nanopar-ticles have very poor conductivity (σ = 2 × 10−9 S cm−1),70,71 andhence to increase their conductivity, they are coated with carbon.7 Inthe case of the unaged sample the total surface resistance measured isthe resistance of the carbon-coated LiFePO4 nanoparticles (Ru). Dueto the coarsening of the nanoparticles the overall resistance increasesto (Ra).

The coarsening may also causes loss of the carbon coating, whichleads to a further increase in the resistance of these particles. Inaddition to this, the total surface resistance of the aged sample couldincrease due to the additional resistance from the nano crystalline de-posit (NCD) formed on the cathode surface. The NCD is formed dueto the chemical reactions taking place at the surface of the cathode.Further experiments are needed to investigate the details of the NCDon the LiFePO4 cathode surface, but it was observed by Zhang et al.172

and Kostecki and McLarnon32 on LiNi0.8Co0.2O2 cathode surface.Surface conductivity.—Ramdon and Bhushan157 have used the currentsensing capabilities of AFM to determine the effect of differences

Figure 23. Surface resistance maps of a LiFePO4 cathode sample harvestedfrom unaged and aged cells. A + 1 V DC bias is applied to the sample (adaptedfrom Nagpure et al.64).


Figure 24. Schematic of a proposed mechanism explaining increase inthe surface resistance of a LiFePO4 cathode due to aging (adapted fromNagpure et al.64).

in surface morphology on the surface conductance of unaged andaged cathodes. They used Agilent 5500 AFM equipped with a currentsensing preamplifier having a sensitivity of 1 nA/V. The experimentswere conducted in the contact mode of the AFM with the tip coatedwith conductive material. CSAFM involves a bias voltage appliedbetween the sample and the tip, which creates a current, and thiscurrent is used to construct a conductivity map. The voltage used intheir experiment was 3 V.

Figure 25 shows the results of their experiment. There were greateroccurrences of higher conducting regions within the sample for both5 μm × 5 μm and 2 μm × 2 μm for the unaged cathodes. In the agedsample it was observed that the overall conductivity was lower andonly the edges of some particles showed conductivity.

Fig. 25b shows a profile extraction that was done for the unaged andthe aged cathodes, and it can be seen that there are higher currents inthe unaged sample going up to 2 nA for that section as compared to theaged with the highest reading being 0.01 nA. The 2 μm profile of theunaged sample showed that the particles had higher current readingas compared to the aged samples that had very low conductance.The histogram in Fig. 25c shows the current data extracted from thecurrent maps. The unaged sample showed that 20% of the values fallbetween 1 to 10 nA while the other 80% are distributed from 0 to 1 nA.The majority of the aged cathode current values were between 0 and0.1 nA. They have attributed the change in the surface conductivityto the active material losing contact with the current collector, poorconductivity of the PVDF binder, and the rearrangement of the carbonadditive.Surface charge/potential.—Another technique of interest is Kelvinprobe microscopy (KPM), which has been used in a variety of appli-cations to measure surface potential. Because of the sensitive natureof silicon to charge buildup and subsequent discharge which can dam-age small silicon parts, surface potential measurements have been ofinterest in the semiconductor industry. The technique has also beenused successfully to detect wear precursors from wear at very lowloads using AFM based Kelvin probe methods.155,169,173

The use of the Kelvin probe method was extended to the study ofLi-ion batteries by Nagpure et al.66 The KPM technique is based on thecontact potential difference method for measuring the electronic workfunction (EWF).174 Since EWF is strongly influenced by the surfacechemical composition and Fermi level of the material KPM can detect

the structural and chemical changes of the surface and provide vitalinformation about the onset of damage. Using KPM large areas ofthe entire cathode electrode can be scanned quickly giving spatialinformation of its surface. In this study, KPM was used for the firsttime to characterize aging of the cathode surfaces by measuring thechange in the surface potential that can be attributed to physical andchemical changes of the surface.

Nanoscale surface potential measurements have been made byNagpure et al.66 to study aged cathode samples. A schematic of thisinstrument with KPM setup is shown in Fig. 26. The KPM measuresthe surface potential of the samples in interleave mode. Along onescan line on the sample, in first pass, the surface height image isobtained in tapping mode. In second pass the tip is lifted off the sam-ple surface and a surface potential map is obtained. Both images areobtained simultaneously.175 During the first pass, the cantilever is me-chanically vibrated by the X-Y-Z piezo near its resonance frequency.The amplitude of the tip vibrations (not shown) is maintained at aconstant value by the feedback loop as the tip scans the surface of thesample. The signal from the feedback loop is used to construct theheight map of the sample surface (Fig. 26a). During the interleavedscan, the X-Y-Z piezo is switched off. Instead, an AC signal is applieddirectly to the conductive tip that generates an oscillating electrostaticforce on the tip. The tip is scanned along the surface topography lineobtained in the tapping mode with a certain lift off the sample (dottedline in Fig. 26a).

To briefly describe the operating principle of KPM, consider atip and sample interaction as seen in Fig. 26b–26d. When the tipand sample are electrically connected (Fig. 26b) electrons flow fromthe material with the lower work function to the material with thehigher work function. Due to the difference in the work function ofthe electrically connected tip and the sample, an electrostatic contactpotential difference (or surface potential difference) is created betweenthe tip and the sample.174 The value of this surface potential (��) isgiven by the following equation

�� = �ti p − �sample

e[6.1]

where �ti p and �sample are work functions of the tip and the sample,respectively, and e is the magnitude of the charge of one electron. ��will be affected by any adsorption layer and the phase of the materialnear the surface. Electrostatic force is created between the tip andsample under the influence of this surface potential difference and theseparation dependent local capacitance C of the tip and sample. Thisforce is given by

F = 1

2(��)2 ∂C

∂z[6.2]

where z is the distance between the tip and sample.Along with ��, in the operation of the KPM a compensating DC

voltage signal (VDC ) and AC voltage signal, VAC sin(ωt) (Fig. 26c andFig. 26d), is applied directly to the tip. Thus the electrostatic forcebetween the tip and the sample becomes:

F = 1

2

∂C

∂z{(�� + VDC )2 + VAC

2

2}︸︷︷︸

DC term

+ ∂C

∂z(�� + VDC ) VAC sin(ωt)︸︷︷︸

ω term

− 1

4

∂C

∂zV 2

AC cos(2ωt)︸︷︷︸2ω term

[6.3]

The cantilever responds only to the forces at or very near its reso-nance frequency. Thus, only the oscillating electric force at ω acts asa sinusoidal driving force that can excite oscillations in the cantilever.The DC and the 2ω terms do not cause any significant oscillationsof the cantilever. In tapping mode, the cantilever response (RMS am-plitude) is directly proportional to the drive amplitude of the tappingpiezo. Here in the interleave mode the response is directly proportionalto the amplitude of the ω term.175 The servo controller applies a DC


Figure 25. A 5 μm × 5 μm (left) and 2 μm × 2 μm (right) comparisons of unaged and aged LiFePO4 cathode samples. (a) Surface height and conductivity mapsfor unaged and aged. Arrows indicate line where sections were taken. (b) Profile of surface height and current overlay of both unaged and aged. (c) Histogram ofthe distribution of the current in the conductivity maps of both unaged and aged.157


Figure 26. (a) Schematic of the two pass interleavescan method used in KPM (adapted from Rice175).(b) Electrostatic potential and interaction force be-tween a conducting tip and a sample (for illustration�ti p > �sample is assumed), (c) external DC volt-age applied to nullify the force, and (d) external ACvoltage with adjustable DC offset is applied to the tipwhich leads to its vibration (adapted from Bhushanand Goldade176).

voltage signal equal and out of phase with �� so that the amplitudeof the tip becomes zero (F = 0). This compensating signal from theservo controller creates the surface potential map of the sample.176

The conductive AFM tip is necessary for the KPM experiments.The tips used in these experiments had an electrically conductive 5 nmthick chromium coating and 25 nm thick platinum coating on bothsides of the cantilever (Budget Sensors, Model # Multi75E-G). Theresonant frequency of the tips was 75 kHz, and the radius was lessthan 25 nm. The interleave height was optimized to 150 nm for a goodsurface potential signal.

The surface potential maps of the unaged and aged LiFePO4 cath-ode samples are shown in Fig. 27. The maps were collected by apply-ing +1.0 V and +3.3 V from the external DC voltage source. Maps forsamples without an externally applied voltage are shown for compar-ison. Within each surface potential map for both the unaged and agedsample, Nagpure et al.66 observed no large difference in the contrast,suggesting an almost uniform dissipation of charge over the surface ofthe samples under the externally applied voltage. This indicates thatunder the external source the sample tends to charge uniformly evenin an aged condition. The uniform charging is good for the cell as itavoids large local currents and subsequent damage to the cathode.

The surface potential image discussed above is generated by amatrix of 256 × 256 data points. The last column of Fig. 27 also showsthe distribution of these data points in unaged and aged cathodes. Foreach case a histogram is created with 17 equally spaced bins. The binsize was optimized using Sturges rule,177

k = 1 + log2(n) [6.4]

where k is the number of bins, and n is total number of data points.Then a normal probability density function as shown below is used tofit the data.178

f (x) = 1√2πσ2

e− (x−μ)2

2σ2 [6.5]

where μ is the mean, and σ is the standard deviation of the data points.The unaged sample had mean values of the surface potential almost

equivalent to the external applied voltage. The mean values of surfacepotential on the aged sample are lower than that of the unaged sample.Thus, even though the externally applied voltage was the same for theunaged and aged samples the charge sustained on the surface of theaged cathode is less than that sustained on the unaged cathode.

The surface potential measured using KPM is the difference be-tween the work functions of the tip and sample surface. Since the samekind of tip is used in these experiments, the work function of the tipis constant in each surface potential map. Figure 27 shows the changein the work function of the aged sample as compared to the unagedsample. The work function is the property of the structure near thesurface of the sample along with the chemical potential of the surface.The decreased surface potential in the aged sample is the indicationof the surface modification and could occur due to one or all of thefactors discussed below.

A phase change of the cathode material occurs from LiFePO4

to FePO4 and back to LiFePO4 during respective charging and dis-charging cycles of the battery. During charging, the Li-ions fromthe LiFePO4 cathode are intercalated in the graphite anode. Duringdischarging, the Li-ions move out of the graphite anode and are in-tercalated back in the cathode. The olivine structured LiFePO4 has adifferent work function than that of the metastable FePO4. The changein the surface potential map of the aged sample indicates that one ofthe phases might be growing in the cathode sample during the batteryaging. Andersson and Thomas179 have demonstrated this phase changeas a source of initial capacity loss using neutron diffraction data. Basedon their experiments they have proposed a radial model and a mosaicmodel for the phase change between LiFePO4 and FePO4. In eitherof their models they have suggested unconverted inactive regions ofLiFePO4 entrapped by the FePO4 phase. They concluded that, in real-ity, the superposition of the essential features of the two models mightbe occurring.

Summary.— The electrical properties of the LiFePO4 based Li-ion batteries were studied at different scales. The capacity drop andinternal resistance were used as the system level metrics. As the


Figure 27. Surface potential map of the unaged (left column) and the aged (middle column) LiFePO4 cathode samples with external voltage of +1.0 V and+3.3 V. The data for a sample without any external voltage is shown for comparison. The right column shows the normal probability density distribution of thesurface potential values obtained for the unaged and aged samples. The mean value of the surface potential decreases after aging (adapted from Nagpure et al.66).

battery approached the EOL the knee in the discharge curve wasapproached rapidly. The batteries cycled at higher C-rate tend to agefaster.

SSRM was used to measure the change in the surface resistance.The aged sample showed much higher surface resistance as comparedto the unaged sample. The loss of performance can be attributed tothe coarsening phenomena observed in the physical/morphologicalstudies. The coarsening phenomenon can lead to the disbonding ofthe nanoparticles from the aluminum substrate causing loss of con-tact between the active material and the current collector, leading toan increase in the internal resistance. The coarsening can also lead toseparation of particles, leading to the loss of electrical contact betweenparticles. The coarsening phenomena can also cause the degradationin the carbon coating leading to a further drop in the electrical perfor-mance of the cathode.

KPM was used to measure the change in the surface potential. Theaged sample showed a less charge sustaining capacity as compared to

the unaged sample. The loss in the ability of the cathode to retain theapplied charge can also be attributed to the coarsening phenomena. Inthis case, due to the larger particle size the overall distance traveled bythe applied charge is increased, thus leading to the loss of capabilityto sustain the applied charge within the applied time.

Multi-Scale Characterization of Cathode - Structuraland Chemical

In this part, the chemical and structural changes in the cathodematerial due to the aging of the batteries are examined. The longrange structure of the LiFePO4 nano particles is characterized withX-ray diffraction. Then Raman spectroscopy is used to characterizethe carbon-coating of the cathode material. The electron energy lossspectroscopy was used to understand the changes in the local structureof the LiFePO4 nanoparticles due to aging of the batteries. Electron


based techniques fail in characterizing the Li in the cathode material.Hence two neutron techniques are added to the scheme of the multi-scale characterization. The local lithium environment was probed withthe nuclear magnetic spectroscopy. Finally, neutron depth profilingwas used to measure the lithium concentration in the unaged and agedsamples of the cathode material.

Characterization of carbon coating.— Raman spectroscopy is aunique analytical tool for identifying and characterizing the elementswithin the sample. It is a non-destructive tool and requires very mini-mal sample preparation. The atmospheric CO2 and H2O do not inter-fere with the Raman signal, so no special atmospheric conditions arenecessary during the experiments. Several different researchers haveused Raman spectroscopy to characterize different types of carbonin different forms such as crystalline, non-crystalline, and amorphouscarbons.180–184 Saito et al.185 have used Raman spectroscopy to analyzethe single-wall carbon nanotubes.

Recently Raman spectroscopy has been used to analyze the carboncoating of LiFePO4 nanoparticles used in lithium-ion batteries. Thestudies have been conducted to understand the effect of carbon coatingon the electrochemical performance of LiFePO4 based lithium-ionbatteries. In the studies done by Doeff et al.186 they showed thatthe structure of the residual carbon present on the LiFePO4 powderaffects its electrochemical performance and the better performanceis dependent on the quality of the carbon rather than the quantity ofthe carbon. Similarly, Cho et al.187 have used RS for studying theeffect of the coating thickness on the capacity of LiFePO4 compositecathodes. Julien et al.188 characterized the carbon-film coating onthe LiFePO4 nanoparticles and discussed the Li+ diffusion throughthe carbon coating. Wilcox et al.189 used RS to study the factors,in particular the synthetic additives, which can affect the quality ofthe carbon coatings. Also, the effects of the thermal treatments onthe performance of the carbon coating using RS have been studiedby Maccario et al.190 RS is very useful in characterizing the carboncoating of LiFePO4 nanoparticles for two main reasons. One, carbonhas a strong scattering with two E2g modes predicted to be Ramanactive.189 Second, the penetration depth of light inside the LiFePO4

particles is very small, thus the first coating layer can be easily probedwith RS.188

In the multi-scale characterization plan RS was used to analyzethe carbon coating on the LiFePO4 nanoparticles in several commer-cial cells aged with different C-rates.69 As mentioned earlier, it is acommon practice in the production of lithium-ion battery electrodesto add carbon, either by use of carbon additives to the LiFePO4 matrixor by surface coating of LiFePO4 particles with thin layers of carbonto improve the electronic conductivity. Degradation in the quality ofthe carbon coating can lead to decreased electronic performance ofthe cathode.

Labram, an integrated confocal Raman microscope system, madeby ISA Group Horiba was used to analyze the carbon-coating. Sincethe positions of the Raman bands are dependent on the wavelength ofthe incident laser, a He-Ne laser with 512 nm excitation wavelengthwas used in these experiments for comparison of our data with thepublished literature. The laser power was adjusted to 2.5 mW and thelaser spot size was at ∼5 μm. RS experiments were conducted underambient conditions at room temperature. The data acquisition timewas set at 10 s for all the samples. The commercial software packageincluded in the Labram system was used for background subtractionand baseline correction.

Figure 28 shows a typical Raman spectra obtained on sample C0(solid dark line). The Raman spectroscopy of a disordered carbonshows two distinct peaks. The peak at ∼1600 cm−1 is referred to asG (graphite) peak and the peak at ∼1350 cm−1 is referred to as D(disordered) peak. The G peak is attributed to the optically allowedE2g zone-center mode of crystalline graphite while D peak is attributedto the disorder allowed zone-edge modes of graphite.182,188

The Raman spectra are deconvoluted according to these two char-acteristic D and G peaks. As can be seen in Fig. 28 the Raman spec-tra were satisfactorily deconvoluted with Breit-Wigner-Fano (BWF)

Figure 28. Deconvolution method used for fitting of experimental Ramanspectra. The method is demonstrated with the experimental Raman spectra(dots) for C0 battery. The data is deconvoluted in two peaks (dotted line) andthen fitted (solid line). The D peak is fitted with Lorentzian and G peak is fittedwith Breit-Wigner-Fano (BWF) line shape.69

plus Lorentzian scheme. A BWF line is used for the G peak and aLorentzian line is used for the D peak. The BWF line shape is givenby

I (ω) = I0[1 + 2(ω − ω0)/Q�]2

1 + [2(ω − ω0)/�]2[7.1]

where I0 is the peak intensity, ω0 is the peak position, � is assumedas the full width at half maximum (FWHM) and Q−1 is the BWFcoupling coefficient. Due to the coupling of a discrete mode to thecontinuum BWF line has an asymmetric line shape.184,191 A Lorentzianline shape given by Eq. 6.2, which belongs to the same family as BWFis used for the D peak:

L = I0

[�

(ω − ω0)2 + �2

][7.2]

The deconvolution of the Raman spectra based on BWF+ Lorentzian scheme is shown for the data obtained for sample C0 inFig. 28.

Figure 29 shows the fitted Raman spectra for all the samples usingthe deconvolution method described above. The deconvolution pro-cedure satisfactorily fits the experimental Raman spectra for all thesamples. The two characteristic D and G peak are observed in all thesamples. Note that the positions of the Raman bands are dependent onthe incident laser wavelength, so for quantitative comparison betweenspectra given here, the excitation wavelength of 512 nm was main-tained in this study. The data shows a uniform coating of carbon onthe LiFePO4 particles with highly disordered carbon. The relative in-tensities of the D and G band are associated with the increased carbondisorder similar to disorder in microcrystalline graphite.186,192

According to Doeff et al.186 the electrochemical performance of thecarbon coated LiFePO4 cathode is not only dependent on the quantityof the carbon but also on the quality of carbon. The quality of thecarbon coating in the different samples is compared by comparingthe intensity ratios of the D and G band (ID/IG). Usually a lowerID/IGratio is desired in a good quality LiFePO4 cathode. As canbe seen in Figure 30, ID/IG ratio increases with increasing C-rate.


Figure 29. Raman spectra of all the cells. Each spectrum was fitted with thedeconvolution method shown in Fig. 28.69

According to Tuinstra and Koenig193 the in-plane correlation lengthID/IG is related to the ID/IG ratio, which quantifies the mean basal-plane diameter of graphite parallel to (001).190 The following modifiedTuinstra-Koenig relation gives the value of La,

La = C(λL )

ID/IG[7.3]

where C(λL ) is a variable scaling coefficient depending on excitationwavelength λL and given by

C(λL ) = C0 + λLC1 [7.4]

where C0 = −126 Å and C1 = 0.033.194 As the ID/IG ratio increasesfrom 0.76 to 0.81 the in-plane correlation length ID/IG calculatedusing Eq. 7.3 and Eq. 7.4, drops from 5.64 to 5.27 nm for cells C0through C6. The increasing trend of the ratio and decreasing trend ofthe in-plane correlation length suggest the lower amounts of graphite

Figure 30. Intensity ratio analyzes (ID/IG ). The intensity is calculated asthe area under the respective curve. The intensity increases with the C-rateindicating poor quality of carbon leading to loss of electrical conductivity inbatteries cycled at higher C-rate.69

Figure 31. XRD spectra of unaged and aged samples. Both the samples showpresence of LiFePO4 and FePO4 phases.

clusters in very highly disordered carbon. Thus the higher ID/IG ratiohere indicates poor quality carbon in cells aged with a higher C-rate.189 This leads to poor electronic properties of the carbon coatingand contributes to the increased ohmic resistance of the cell. Thus theoverall electrode performance is affected in cells aged with a higherC-rate. The composite cathodes cycled with a higher C-rate have poorelectronic conductivity. The higher ID/IG ratio could be the resultof the thermal effects and the strain developed in the matrix due tothe volume change of the active material during each charging anddischarging cycle.

In summary RS was used to analyze the carbon coating of agedLiFePO4 nanoparticles. According to the Raman studies the carboncoating degrades in quality as batteries are aged at higher C-rates.The higher ID/IG ratio in the case of batteries cycled at a higherC-rate indicates poor quality carbon leading to a loss of electricalconductivity and a subsequent decrease in the performance of thebattery.

Phase and local structure analysis.— The phase and the localstructure analysis of the cathode samples is necessary to understandthe chemical structure change due to the aging of the cells. The X-raydiffraction is good in analyzing the long-range structure of the ma-terial. The electron energy loss spectroscopy will provide a localizedanalysis of the change in the electronic bonding between the hostactive material matrix due to the change in the phase observed withXRD.X-ray diffraction (XRD).—X-ray diffraction is a non-destructive tech-nique mainly used for studying long range structural ordering of ma-terials and phase identification. It is also used for quantitative analysisof phases, residual stress measurement, crystal structure and three-dimensional material properties. In lithium ion battery research it hasbeen used for ex-situ phase identification of the cathode materials afterbeing charged and discharged. Recently in situ XRD has been demon-strated to analyze the crystalline structure of the cathode materialduring charging and discharging cycles.195

Li et al.195 have used Rietveld fitting and quantitative phase analysisto analyze the phase fractions. The two-phase fitting was performedusing LiFePO4 and FePO4 as end-members and the structural datagiven by Anderson et al.196 and Channagiri et al.152 The results ofquantitative phase analysis demonstrate an increase in FePO4 phasefraction with aging at a given location on the cathode as seen inFig. 31. The increase in FePO4 phase with aging was explained byconsidering separation at the Carbon-LiFePO4 interface with aging.This separation would result in fewer regions of the cathode where athree phase boundary is present (Active material/Carbon/Electrolyte),reducing the efficiency of Li intercalation into the solid nanoparticles.The change in the volumetric concentration of the active material


would be a very important input parameter in the electrochemical andperformance models of the Li-ion batteries.

Electron energy loss spectroscopy (EELS) (nm).—Electron energy lossspectrometry (EELS) is based on the analysis of the energy distributionof electrons that have interacted inelastically with the specimen. Theseinelastic collisions carry information about the electronic structure ofthe specimen, which helps in understanding the electronic bondingbetween the various elements of the specimen. EELS studies can alsohelp identify the thickness of the sample. The technique can be appliedto any amorphous as well as crystalline sample. The EELS spectrumis gathered with the help of a magnetic prism spectrometer that isoften interfaced into TEM.197

So far, in lithium ion battery research, EELS has been used tostudy the local electron structure of the host material, the interca-lation/deintercalation process of the Li within the host material andthe subsequent phase changes.58,160 In the multi-scale characterizationplan EELS was included to analyze the local electronic bonding ofthe Li with its neighboring atoms and to identify the changes in theseelectronic bonding schemes between the LiFePO4 cathode samplesharvested from the unaged and aged batteries. Such studies were con-ducted along with the high-resolution TEM imaging studies reportedin morphological studies by Nagpure et al.68 The sample preparationprocess has already been discussed earlier.

Figure 32 shows the microstructure and the corresponding EELSmeasurements for the unaged and aged samples. The areas were cho-sen for a single particle analysis. Due to the uncertainty in establishingthe absolute value for the energy loss scale all the spectra were alignedat O K edge (532 eV). All the spectra were normalized to the intensityof the O K edge peak. As shown in Fig. 32b, a significant differencein the shape of the O K edge peak is observed. The peaks in the datawere fitted with a Gaussian function. The O K edge peak is at 532 eV,with a pre-peak at ∼528 eV found in the aged sample which is almostnegligible in the unaged sample. Figure 32c shows changes in theFe L2,3 edge with aging. It can be seen in this figure that the maindifference between the aged and unaged sample is the position of theFe L2,3 edge. The onset of the Fe L2,3 edge for the aged sample is∼2 eV higher than for the unaged sample. The EELS measurementswere conducted from the periphery to the core of the LiFePO4 particlein both the unaged and aged sample. But note that in Fig. 32b and 32cnot all spectra are shown, and only a representative of the phenomenais presented. As can be seen in Fig. 32b, the intensity of the O K edgepre-peak is higher at the core than at the periphery of the large particlein the aged sample. Thus the ratio of the pre-peak to the main featureof O K edge peak was less at the core of the larger particle in the agedsample than at the periphery. It is also interesting to note that if theEELS spectra are obtained at the core and the periphery of a largeparticle in the aged sample, there is a shift of the Fe L2,3 edge to ahigher energy.

The differences in the shape of the O K edge and the position of theFe L2,3 edge have been explained in previous spectroscopy work byLaffont et al.160 and Miao et al.58 The pre-peak at the O K edge and theshift to higher energy of the Fe L2,3 edge observed in the aged sampleis characteristic of a highly delithiated LiFePO4 (a charged cell), whilethe spectra observed in the unaged sample is characteristic of a welllithiated LiFePO4 (a discharged cell). Since in this study both sampleswere discharged before disassembly, it is believed the phenomena ob-served here is due to the aging of the cells. The measurements suggestthat the core of the larger, coarsened LiFePO4 particle in the aged sam-ple has a different lithium composition than the periphery. It is thusbelieved that during aging the LiFePO4 nanoparticles sinter togetherresulting in coarsening of the particles. This coarsening is expected toincrease the Li-ion diffusion length through the particles, and thus thetransformation of nanoparticles during discharging of the cell fromFePO4 back to LiFePO4 is expected to be incomplete, leaving anFePO4 (or low Li-concentration) core and a LiFePO4 shell around thecore in large particles. As the cell ages the FePO4 (or low Li concen-tration) core increases and the LiFePO4 shell decreases. This leadsto the conclusion that the aging has caused significant compositional

Figure 32. (a) TEM images of unaged and aged LiFePO4 cathode samplesshowing the location of EELS spectrum (b) and (c). (b) O K edge of the unagedand aged LiFePO4 cathode samples. There exists a pre-peak in the case of theaged sample suggesting a change in the density of states of O. (c) Fe L2,3 edgeof the unaged and aged LiFePO4 cathode samples. The edges shift to the rightin case of the aged sample. The EELS data was normalized with the O L2,3edge peak. The individual spectra were offset vertically in order to present thedetails.68

changes in the LiFePO4 nanoparticles. The active lithium is lost fromthe host cathode material, thus reducing its capacity. The diminishedlevels of Li in the cathode can be expected to lead to a compromisedcapability of the overall cell to recharge.

The electronic structure calculations were performed on super-cells containing six formula units of LixFePO4 with x = 0, 0.25, 0.5,0.75, and 1 for detailed analysis and interpretation of the experimentalresults. The structural data for the starting materials in these calcu-lations were adapted from Tang and Holzwarth.198 LiFePO4 formsan orthorhombic olivine structure with a slightly distorted hexagonalclose packed oxygen array belonging to the symmetry group Pnma,199

listed as no. 62 in the International Tables for Crystallography.200

Figure 33 shows the crystal structure of this material with one unitcell constructed with Materials Studio. The O atoms are located at thetetrahedral sites around each P atom. The divalent Fe ions form anoctahedral arrangement with the O atoms. The Li atoms are locatedin channels along the b axis of the orthorhombic structure.198

The density functional theory (DFT), as implemented in the Vi-enna Ab-initio Simulation Package (VASP)201,202 was employed toperform the electronic structure calculations within the generalized


Figure 33. Crystal structure of LiFePO4 showing one unit cell constructedwith Materials Studio.68

gradient approximation (GGA) with a PW91203 type projector aug-mented wave (PAW) potentials using a cutoff energy of 500 eV, en-hanced by a coulombic term U204 to include strong correlation effects(GGA + U) for the Fe d orbitals. Within this framework the exchangeterm U is combined with the coulomb term U and (U − J), an ef-fective value of U referred to as Ueff, is used. A value of 4.3 eV waschosen for Ueff following Miao et al.58 All the calculations here havebeen performed for the ferro-magnetic configuration for consistency.An energy convergence of better than 10−6 eV was achieved whenrelaxing the geometry. The initial and relaxed lattice parameters forstructures with varying lithium contents calculated with the GGA+ U approximation are shown in Table VII.

Following Duscher et al.,205 the Z + 1 approximation method hasbeen applied to simulate the electron energy loss near edge structure(ELNES). The ELNES onset was set up at the Fermi energy of thedifferent structures. This approximation has been shown to modelcore hole excitation spectra in oxides well if dipole selection rulesare used (change in orbital angular momentum quantum number byone).205,206 Integration for the angular momentum resolved conductionband density of states (DOS) has been performed using the tetrahedronmethod with Blochl corrections for 6 formula unit supercells createdfrom the geometrically relaxed unit cells, with a 4 × 4 × 4 Monkhorst-Pack k-point mesh for Brillouin zone sampling for the supercells.207

Figure 34 shows ELNES for the O K edge and Fe L2,3 edge ob-tained by the first-principles calculations. A small pre-peak for theO K edge is found for FePO4, which is not found in structures withLixFePO4 (x > 0). This is in agreement with the observed experi-mental trend presented in Fig. 32b. For the Fe L2,3 edge (Fig. 34b)a peak shift toward higher energies can be observed with decreasinglithium content, which has also been observed in the experimentalresults (Fig. 32c). For FePO4 with no lithium, the calculated EELSshows a reverse shift in the Fe L2,3 edge, in agreement with Miaoet al.,58 which the band structure calculations suggest could poten-

Table VII. Initial lattice parameters and relaxed latticeparameters for structures with varying lithium content obtainedby generalized gradient approximation (GGA) with PW91 typeof pseudopotentials, enhanced by a U term to include strongcorrelation effects (GGA+U). The structural co-ordinates wereadapted from Tang and Holzwarth198 for FePO4 and LiFePO4,while the intermediate structures were created by subsequentlyremoving lithium from LiFePO4 structure.68

a-lattice(Å) b-lattice (Å) c-lattice (Å)

Compound initial relaxed initial relaxed initial relaxed

FePO4 9.81 9.946 5.79 5.891 4.78 4.866Li0.25FePO4 10.33 10.041 6.008 5.947 4.69 4.861Li0.5FePO4 10.33 10.203 6.008 5.993 4.69 4.806Li0.75FePO4 10.33 10.324 6.008 6.026 4.69 4.787LiFePO4 10.33 10.418 6.008 6.067 4.69 4.745

Figure 34. (a) The O K edge electron energy loss near edge structure (ELNES)calculated within the Z+1 approximation and dipole selection rules using theVienna ab-initio simulation package (VASP). (b) Analogous calculation of theFe L2,3 edge ELNES. The energies are set at the Fermi energy, which is 0 eVon the x-axis. The ELNES intensities were normalized to the O K edge peak.The individual spectra were offset vertically in order to present the details.68

tially be due to the fact that Li acts as a donor in FePO4, causing ashift in the Fermi level.

Figure 35 shows O p states, Fe d states, and P s and p states andtheir hybridization based on band structure calculations. In a perfectlyionic state the O ions in FePO4 could be expected to have a valenceof 2 with fully filled 2p states. Covalent bonding, however, leadsto hybridization between the Fe 3d, O 2p, and P 3s and 3p states,giving rise to empty states (above the Fermi level) with some O 2pstates. This can be seen from Fig. 35, where the atom resolved DOS,obtained from first-principles calculations, has been plotted for threecompositions: FePO4, Li0.5FePO4, and FePO4. In all three compoundsthe valence band just below the Fermi level (region 1 in Fig. 35) hasmajor contributions from the O 2p states with some Fe 3d states. Theconduction band just above the Fermi level (region 2 in Fig. 35), onthe other hand, is dominated by Fe 3d states with small contributionsfrom O 2p states. Moving to higher energy bands (>10 eV, region 3in Fig. 35), antibonding states are found with O 2p, 3s, and 3p states.In FePO4 the contribution of O 2p states in region 2 is significant andgives rise to the pre-peak A observed in the simulated O K edge EELSspectra, shown in Fig. 34a, due to transitions from the 1s core orbitalof oxygen. The O 2p states present in region 3 gives rise to peaks Band C seen in Fig. 34a, after core hole corrections which shift thesestates toward lower energies by approximately 3 eV.


Figure 35. O p states Fe d states, and P s and p states and their hybridization showing how the states move with Li concentration and thus give rise to variationsin the intensity of O K edge pre-peak. The black line is the Fermi level given by Vienna Ab-initio Simulation Package (VASP).68

While Li addition does not affect the positions of peaks B andC, it does lead to a continuous decrease in the intensity of pre-peakA, as observed in both the experimental (Fig. 32b) and simulated(Fig. 34a) O K edge EELS spectra. This can be attributed to thefollowing two causes. Firstly, on addition of Li the Fe 3d states shiftto higher energies (from ∼3–5 eV in FePO4 to ∼6–8 eV in LiFePO4)because of the reduction in the oxidation state of Fe from Fe3+ toFe2+ (region 2 in Fig. 35). Secondly, it leads to a continuous decreasein the extent of hybridization between Fe 3d and O 2p states, suchthat the contribution of O 2p states in region 2 becomes negligiblein LiFePO4. This analysis is similar to the arguments put forwardby Kinyanjui et al.,208 who studied only the end compounds. Basedon the decrease in intensity of pre-peak A with Li addition, the pre-peak is expected to be completely absent for Li concentrations greaterthan ∼75%. Similarly, in the case of Fe L edges the intensities of thesharp lines themselves scale with the number of unoccupied 3d statesof the Fe atom. In the aged sample the shift is ∼2 eV. Accordingto the first principles simulations presented, this would correspondto a reduction in Li content of ∼80%. Thus, the FePO4 core andLiFePO4 shell, co-exist within large particles, and as the cell agesthe FePO4 (low Li content) core expands while the LiFePO4 shelldecreases.

The energy at the Fe L2,3 edge peak obtained from first-principlescalculations was plotted against the Li concentration in LixFePO4 inFig. 36. The shift to higher energy in the location of the Fe L2,3 edgepeak follows a linear trend with an approximate slope of −1.9 eVwith increasing Li concentration. Considering the experimental shiftof ∼2 eV between the unaged and aged samples, this would indicatea Li loss of ∼80% in the aged sample. Since complete Li depletionfrom LiFePO4 would lead to a downward rather than the observedupward peak shift, the calculation here indicates that the aged sampleis not completely Li depleted, but rather remains at a low Li contentof ∼20%.

To summarize, the EELS measurement showed that the densityof states for O changes as the cell ages. This was evident in thepresence of the pre-peak in the case of the O K edge. The increasein the ratio of the pre-peak to the O K edge peak in the EELS datafrom the core to the surface of the large LiFePO4 particle indicatesdifferent lithium composition within the particle. There is also a shiftof almost 2 eV for the L2,3 edge of Fe in the aged sample. At a certain

age of the cell the particles start to coarsen. The ion diffusion lengthis expected to increase in the coarser particles, and this is expectedto lead to an incomplete transformation between LiFePO4 and FePO4

while charging and discharging. The FePO4 core is expected to expandin subsequent cycles, thus reducing the capacity of the host cathodematerial.

The experimental results were analyzed with the help of simu-lated ELNES spectra for the olivine structure (space group Pnma)of LixFePO4 with x = 0, 0.25, 0.5, 0.75, and 1. The nature of theO pre-peak was confirmed by comparing the position of the O 2pbands arising due to strong hybridization among the O p states, Fe dstates, and P s and p states with the Fermi level position. The Li losswas quantified by these calculations as 80%, suggesting a strongly

Figure 36. Calculated energy at the Fe L2,3 edge peak vs. Li concentration inLixFePO4. The data fits a straight line with slope −1.9 eV. Based on this plotit is estimated that the aged sample was Li0.2FePO4.68


Li depleted, but not completely Li free, core region in the coarsenedparticles.

Loss of cyclable lithium.— Loss of cyclable lithium is consideredas the main reason for capacity fade in Li-ion batteries.73,74,209,210

In lithium-ion batteries, Li is the most important element as it is di-rectly involved in the electrochemical process during the charging anddischarging cycles of batteries. Hence, understanding the Li concen-tration, as well as the local crystallographic and electronic structureof Li within the host LiFePO4 structure, is critical to predicting theperformance of the lithium-ion batteries in terms of operating volt-age, residual capacity, and rate capability. In the previous section lossof Li was demonstrated through indirect measurements with EELS.The common electron spectroscopy techniques fail to identify andqualitativly measure lithium within the sample. The energy dispersivespectroscopy (EDS) technique, which is commonly used to identifythe atomic percent of the elements in the component, fails to detect Li.The EDS detectors are very sensitive to impurities. To avoid repeatedexposure of the detectors to atmosphere, they are maintained undera vacuum and are separated from the column vacuum in the electronmicroscope by a beryllium window. The thin beryllium window onthe EDS detector absorbs low energy X-rays and thus prevents theuse of EDS in the detection of elements with an atomic number lessthan five. EELS provides an indirect method to probe the lithiumand its local environment within the sample. The EELS studies haveshowed the change in the density of states of O in the aged LiFePO4

cathode sample and the subsequent loss of Li from the host LiFePO4

structure. XRD techniques are useful in identifying the phases of theLiFePO4 material present in the cathode and long-range structuraldata. However, it lacks the ability to provide local crystallographicand electronic structure of lithium within the sample.

Therefore neutron based techniques such as neutron imaging, neu-tron depth profiling (NDP) or NMR, etc. prove vital in studyinglithium within the sample because neutrons have high penetrationpower and detectors do not require any special protection from theenvironment.59,211 Among these neutron techniques, NMR can playa vital complementary role to study cathode materials in lithium-ionbatteries as it directly probes the local Li environment.212 NMR andNDP have been used in characterizing the lithium content in the elec-trode samples harvested from aged large format Li-ion cells.Nuclear magnetic resonance (NMR).—Solid state NMR is extremelyuseful for studying the local structure in ordered and disordered ma-terials. Solid state Li NMR in particular is very useful due to itshigh sensitivity toward the atomic and electronic environment at thelithium site within the host cathode structure.213 NMR can distinguishbetween the metallic and semiconductor behavior of the materials.While probing the local and electronic environment of the nuclearprobe it can also monitor the electronic structure of the surroundingcations.212 In NMR spectroscopy it is also possible to quantify thespecies taking part in battery charging and discharging, and moni-tor the effect on the local structural changes of these species as thefunction of the aging of the battery. Due to its sensitivity toward thelocal electronic structure it can also distinguish between diamagneticand paramagnetic behavior of materials. Most of the materials usedas cathode in lithium-ion batteries show paramagnetic behavior incharged and discharged state.214

The naturally abundant 7Li isotope (93%) has larger quadrupleand gyromagnetic moments as compared to the less abundant 6Li(7%) isotope. The quadruple interactions result from the interactionsbetween the quadruple nucleus and the electric field gradient at thenucleus. The quadruple interactions of 6Li are smaller compared with7Li but they result in higher resolution spectrum that is easier tointerpret.214 Thus the coupling between the lithium nucleus and theunpaired electrons can be exploited in magic angle spinning (MAS)NMR to study the changes in the local electronic structures as thefunction of the battery aging in the paramagnetic cathode materials.

Given these advantages of NMR, it has been used by several re-searchers to study different types of cathode materials. Layered ox-

Figure 37. NMR spectra of samples harvested from C0 and C6 batteries. Anisotropic 7Li peak is observed in C0 while similar speak is absent in C6.69

ides such as LiCoO2 and LiNiO2 have been studied by Dahn et al.,215

Marichal et al.,216 Levasseur et al.,217 and Carlier et al.218,219 Thespinel structured materials, such as LiMn2O4, have been studied byMorgan et al.,220 Gee et al.,221 Lee et al.,222,223 Lee and Gray,224 Tuckeret al.,225 and Verhoeven et al.226 The spinel structured materials, suchas LiFePO4, have also been studied by Gaubicher et al.,227 Tuckeret al.,213,225,228 and Arrabito et al.229 The goal in these studies has beento understand and predict the effect of local and electronic structureon lithium NMR shift in these battery materials. In situ NMR studiesusing a toroid detector with limited resolution have also been con-ducted by Gerald et al.230 Chevallier et al.231 have also shown thatNMR signals from plastic bag batteries can be successfully obtainedfor analysis.

In the multi-scale characterization plan a magic angle spinning(MAS) nuclear magnetic resonance (NMR) with 7Li probe was used toprobe the presence of lithium in the unaged and aged cells by Nagpureet al.69 Since Li is vital in charging and discharging of the batteries,NMR can provide a vital understanding about its local environmentwithin the host structure and any changes to the structure due to agingduring cycling of the cells.

A Bruker DSX 300 MHz NMR spectrometer was used to probethe lithium in LiFePO4 nanoparticles. A 7 mm triple resonance MASprobe was tuned to the 7Li frequency of 38.9 MHz. The shifts in the7Li were referenced with 1 M LiCl(aq) solution. The Bloch Decayexperiment method was used with relaxation delay of 10 s and spinrate of 10 kHz.

Figure 37 shows the NMR spectra for C0 and C6 samples. In thecase of the C0 sample a single isotropic 7Li peak is observed whilethis peak is absent in the case of the C6 sample. The NMR spectraof C0 shows a small chemical shift of ∼8 ppm. There is also con-siderable broadening of the peak. The multiple spinning side bandsaccompanying the isotropic peak observed by Tucker et al.213,228 arenot observed in this case. The single isotropic band indicates one localenvironment for the lithium in the case of C0. The crystal structure ofthe LiFePO4 was shown in Fig. 33. LiFePO4 shows a paramagneticbehavior and the single isotropic peak in C0 is as expected for para-magnetic materials containing a single type of Li site. Lithium NMRspectra for paramagnetic materials are dominated by series of largerinteractions, such as quadruple coupling (6Li, I = 1; 7Li, I = 3/2) andhyperfine interactions between nucleus and the unpaired electrons.214

The possibility of a Knight shift in the battery materials is excludeddue to their electronic insulating character.228

According to Tucker et al.213,228 the shift in the case of LiFePO4

can be attributed to the hyperfine interactions through-bond transfer(specifically Li-Fe-O bond) of the unpaired electron density via theoxygen p-orbitals to the Li s-orbitals. Since LiFePO4 is electronicallyless conductive the Knight shift characteristic of metal conductors isignored for this material. The broadening of the peak can be attributedto the considerable local disorder in the coordination sphere of Li inLiFePO4.213 The absence of a peak in the case of the C6 samples


indicates the presence of FePO4 instead of the LiFePO4 phase. Thisis consistent with an observation by Nagpure et al.,68 using EELNS.The Li depletion in the case of the aged samples caused the changesin the local electronic structure of the sample. The Li depletion in theaged sample caused the transitions from the 1s core orbital of oxygenand strong hybridization between the Fe 3d, O 2p, and P 3s and 3pstates, giving rise to empty states (above the Fermi level) with some O2p states. The lithium starved FePO4 phase indicates loss of cyclingcapability of the battery.

In summary NMR was used to probe the local Li environmentof the LiFePO4 nanoparticles. The solid state 7Li NMR is very criti-cal in studying the local environment and electronic structure of theLiFePO4 nanoparticles as it directly probes the Li within the sample.An isotropic peak with a small chemical shift, a characteristic of para-magnetic materials, is observed in the unaged LiFePO4 sample. Theabsence of such a peak in the aged sample indicates the Li starvedFePO4 phase. The loss of active Li directly affects the loss of cyclingcapacity of the battery.

Neutron depth profiling (NDP).—NDP is a very useful technique instudying the concentration of lithium within the sample. It is a non-destructive analytical technique based on the nuclear fission reactionbetween beams of neutrons with certain elements, such as lithium,throughout the sample. The cold neutrons are delivered through aneutron guide to the NDP chamber. In this work, the cold neutronsrefer to neutrons with energy less than 5 meV. Since cold neutronshave extremely low energy and momentum, there is no center-of-massmotion in the neutron-lithium reaction. Furthermore, the neutron eventrate is insufficient to cause significant temperature rise in the sample,nor is there significant radiation damage to the sample during themeasurement period.

Ziegler et al.232 for the first time used the nuclear reaction ex-periment to determine the concentration of boron impurity in siliconwafers. The sample was bombarded with a well-collimated beam oflow energy neutrons in a vacuum, and the emitted energized particleswere analyzed using a charged-particle spectroscopy for the concen-tration profile of the 10B in the sample. Later, Downing et al.233 coinedthe term neutron depth profiling (NDP) for this technique. Since thenthere have been several applications of this technique to other neutronsensitive light-weight isotopes, some of which are listed by Downinget al.234 Biersack and Fink235 were first to study the implantation oflithium in semiconductors using NDP. Later on Krings et al.236 stud-ied lithium diffusion in electrochromic WO3 films using NDP. Theycompared the secondary ion mass spectrometry (SIMS), elastic recoildetection (ERD), and NDP techniques while profiling the lithium con-centration along the depth of lithium intercalated thin electrochromicWO3 films. They concluded that the NDP technique has a very gooddepth resolution with high sensitivity, and proves to be very usefulover the other techniques because of its non-destructiveness. Lamazeet al.237 have demonstrated the use of NDP in two thin film batterymaterials. They profiled the lithium concentration in ion beam assisteddeposition (IBAD) thin lithium phosphorus oxynitride films and thinlithium cobalt oxide films. The main advantage was again the non-destructive nature of the NDP technique. The study was limited tothe deposited thin films rather than electrodes extracted from actuallithium ion cell.

Whitney et al.238 used NDP to profile the lithium concentration in acathode of the Li-ion lab cells and in an anode of the off-the-shelf Li-ion cells. The lithium transportation was studied for storage of cells atdifferent temperatures and cycling of the cells at different rates. Theydemonstrated a method to determine the thickness of the solid elec-trolyte interface on a graphite anode in a LiFePO4 cell when stored fordifferent lengths of time under different temperatures. They also pro-filed the lithium concentration in LiFePO4 and LiNi1/3Mn1/3Co1/3O2

cathodes after cycling for only 100 cycles. This helped to understandthe lithium distribution in initial cycles, but did not address the issueof lithium transportation during the end of life of the cells.

Nagpure et al.67 used the NDP technique in the multi-scale charac-terization plan for detailed analysis of the lithium concentration in the

Figure 38. A schematic layout of the cold neutron depth profiling chamber atNIST (adapted from Tun et al.285). At the center of the chamber the sampleis mounted using a 21 cm diameter aluminum ring shaped disk concentricallycovered with a thick dielectric sheet. The dielectric has a 1 cm dia. hole at thecenter of the disk, which serves as the defining window for charged particlesexiting from the sample in the direction of the detector.67

commercial cells. The effect of C-rate on the lithium concentrationtoward the EOL of the battery was measured. All NDP experimentsdiscussed here were conducted at the NIST Center for Neutron Re-search (NCNR). A schematic of the NDP facility is shown in Fig. 38.The sample is attached to an aluminum disk (Fig. 38) which is heldvertically at the center of a vacuum chamber by the grooves providedon the sample mount. The sample mount is oriented such that thesample faces the surface-barrier type charged particle detector. Thedetector has an active area of 150 mm2 and is placed slightly morethan 10 cm from the neutron beam-spot on the sample. An area of∼0.8 cm2 of the sample is illuminated by the cold neutron beam en-tering the vacuum chamber. Upon the absorption of the neutron by theelemental atom in the sample, monoenergetically charged alpha andtriton particles are emitted and travel diametrically opposite from thesite of the reaction. More specifically, when the neutron reacts withthe 6Li atom in this sample, monoenergetically charged alpha (4He)and triton (3H) particles are emitted as shown in the reaction below,

6Li + n −−−→ 4He(2055 keV) + 3H(2727 keV) [7.5]

The energy of the 4He and 3H particles at the reaction site is knownto be at 2055 keV and 2727 keV, respectively.234 These heavy chargedparticles lose energy via a stochastic collision with electrons alongthe path traveling outwards. Both, the count rate and the residualenergy are simultaneously measured from all depths for the particlespecies emerging in the direction of the detector (Fig. 38). The chargedparticles do not lose any energy after leaving the surface of the sampletraveling to the detectors, since the sample chamber is maintained at avacuum less than 1.33 mPa (10−6 Torr). Calibration performed priorto the experiment determined the full width half maximum (FWHM)energy resolution of 18 keV for the charged particle detector. Thesamples were exposed to the neutron beam for various time lengthsranging between 3 to 4 hours. The exposure time was not fixed sothe data was normalized with respect to the run time, but the sampleswere exposed long enough so that the statistical error in counting ofthe 4He or 3H particles is no higher than 3%.

The reaction center of mass coincides with the site of the lithiumatom. Thus the 4He and triton 3H particles originate from the samelocation as that of the original lithium atom, and their respectiveenergies are directly related to the location of the lithium atom inthe sample. The energy loss of the charged particle per unit lengthtraveled through the sample is given by the stopping power function


of the sample. Mathematically, to the first-order approximation, thedepth is related to the stopping power by Braggs law given as

x =E0∫

E(x)

d E

S(E)[7.6]

Here x is the path length traveled by the particle through the material,E0 is the initial energy of the particle, E(x) is the energy of the particleemerging from the surface, and S(E) is the stopping power of thesample material.232 The Stopping and Range of Ions in Matter (SRIM)code developed by Ziegler et al.239 is then used to obtain the stoppingpower of the LiFePO4 cathode and the graphite anode and to assign theresidual energies of the charged particle to the corresponding depth inthe sample. The concentration of 6Li within the sample is determinedby comparing the count rate observed from the sample with that ofa well characterized boron concentration standard, labeled as N6.240

Since the natural abundance of 6Li in the sample is only 7.5%, the totalLi elemental concentration is obtained by dividing the determined 6Liconcentration by 0.075.

The energy spectrum of the 2727 keV 3H particle is used herebecause of its two advantages over the corresponding energy spectrumof the 2055 keV 4He particle. First, since the 3H particle has higherenergy and less mass, the concentration profiles can be obtained togreater depth in the sample. Second, the 3H energy spectrum is notoverlapped by the 4He energy spectrum, but the 3H energy spectruminterferes with the 4He energy spectrum at low energies, i.e., by thecharged particles from greater depths below the sample’s surface.

Figure 39 shows the lithium concentration profile in the anodeand cathode of the various cells aged with different C-rates. Thelithium profile obtained from cell C0 is established as the baseline forcomparison. In the left column the lithium concentration profiles of theanode can be seen changing from section # 1 to section # 5 at the sameC-rate. The surface concentration increases across the different cellswith the C-rate. The right column shows the lithium concentrationprofile in the cathode. The profiles remain identical from sections 1to 5 at the same C-rate, but the slope of the profile decreases withincreasing C-rate.

Figure 40 shows the effect of the SOC combined with the C-rate on the lithium concentration profile. Fig. 40a shows the lithiumconcentration profile in the cell cycled between 60 and 70% SOC with∼6 C-rate (C6) for sections # 1, 3, and 5. The lithium concentrationprofile in cell C4 (same as in Fig. 39) is shown again in this figurefor comparison. In C6, even though the C-rate is high, the amountof lithium buildup near the surface of the anode is less as comparedto C4. The prominent change of lithium concentration profiles in theanode from section # 1 to section # 5 observed in C4 is also absentin C6 except for minor deviations near the sub-surface. Similar to C4,the lithium concentration profiles in sections # 1, 3, and 5 of cell C6are identical to each other. However the lithium concentration profilefor C6 has dropped below the concentration profile in C4. Thus, theoverall lithium concentration in the cathode has dropped significantlyin C6 as compared to C4. Thus at a higher SOC and moderate C-rate, the lithium buildup on the surface of the anode is contained, butlithium is lost from the host cathode material. In Fig. 40b the lithiumconcentration profile in section # 5 of C16 is compared with C0. Inthis case cell C16 is cycled between 45 and 55%, but with a very highC-rate of 16C. It should be noted that cells C0 and C16 in this datawere chosen from a different batch than the earlier cells. The basicchemistry was the same, but the initial lithium concentration in thecathode was much higher in these cells. The lithium buildup on thesurface of the anode was very high in C16 compared to any othercell in this study. The concentration in the anode dropped across itsthickness with a steep slope. The lithium concentration profile in thecathodes of cells C0 and C16 are identical, but the concentration oflithium in the cathode was significantly lower than in C0. Thus, atmoderate SOC but very high C-rate the process of lithium buildupon the surface of the anode is enhanced while there is significant lossof lithium from the host cathode. These results suggest that a cell

Figure 39. Effect of C-rate on the lithium concentration in anode and cathode.The profiles were measured in all six sections from C0, C1, C3, and C4; onlyprofiles over section # 1, 3 and 5 are shown here. Based on the Li concentrationprofile in the anode, the lithium tends to build up at the surface of the anodesamples aged with higher C-rates, whereas the lithium concentration dropsalong the thickness of the cathode anode samples. The SOC varies from 0 to10%.67

operating at high SOC and moderate C-rate has the least amount oflithium build up on the anode surface, and also the least amount oflithium is lost from the host cathode.

Figure 41 shows the lithium concentration profiles obtained onsection # 3 of cell C0 and C6 at various locations within the samesection. The aim here was to identify any change in the lithium con-centration profiles measured at spots away from the center of the givensection. The lithium concentration profiles in the anode shown in theleft column of Fig. 41 are similar for both cells at various locations onsection # 3. This indicates that the lithium concentration in the anodedoes not vary along the height of the anode. The right column showsthe lithium concentration profile in the cathode from both cells. Theprofiles for C0 measured at various locations on section # 3 are iden-tical, but the profile measured at the center spot on the front side hasa higher surface concentration and shows a higher gradient along thethickness than at any other location on the section # 3. The profilesfor C6 measured at various locations on section # 3 are identical.


Figure 40. Effect of state of charge (SOC) and C-rate on the lithium concen-tration profile in anode and cathode, (a) in section # 1, 3 and 5 from C4 and C6,and (b) comparison between section # 5 from C0 and C16. The lithium buildupon the anode surface from a cell cycled at higher SOC is less but increases withincreasing C-rate. The lithium concentration drops in the cathode with higherSOC and higher C-rate. The SOC varies from 0 to 10% for C4, 45 to 55% forC6, and 60 to 70% for C16 during cycling of the cell.67

Since the intensity and change in the lithium concentration in theunaged cell (C0) were greater at the center of the section, the mea-surements were taken at the center of each section throughout thisstudy.

As expected for a completely discharged unaged cell (C0)(Fig. 39), the lithium concentration in the anode is significantly lowerwith little buildup of lithium at the surface, while most of the lithiumis concentrated in the cathode. The lithium concentration profiles inthe anode show higher surface concentration as the C-rate increases.The lithium concentration is at a maximum near the surface, and itdecays exponentially with the depth (thickness) of the sample. Thelithium buildup on the anode surface from a cell cycled at higher SOCis less, but increases with increasing C-rate. The lithium concentrationdrops in the cathode with higher SOC and higher C-rate. The lithiumconcentration profiles in the cathode show a uniform gradient, but theconcentration decreases with increasing C-rate.

The analysis of the surface lithium concentration in the anode isshown in Fig. 42. As seen in Fig. 42a the surface lithium concentrationis nearly constant over all the sections for C0 and C1. In the case ofC3 and C4 the surface lithium concentration increases from section# 1 to section # 5. Thus the buildup of lithium on the surface of theanode is greater toward the core of the cylindrical cell than againstthe outer edge. For example, in the case of cell C4 where the highestchange is observed, the concentration increases from 1.36 × 1020 to3.74 × 1020 atoms/cm3 from edge to core. In Fig. 42b the effect of

Figure 41. Lithium concentration profiles measured at different locations onsection # 3 in the anode and cathode of C0 and C6 cell. The profiles weremeasured at three different spots along a straight line on one face (front) and ontwo spots on the opposite face (back). There is no change in the concentrationprofiles along the straight vertical line in a section.67

C-rate on the lithium concentration gradient in the anode is shown.The lithium concentration gradient increases with the C-rate. Thelithium concentration gradient is very small in the case of cells C0and C1 and is very prominent in the case of cells C3 and C4. Thelithium concentration gradient in all cells exists only for a certaindepth from the surface of the anode. The depth up to which thelithium concentration gradient exists in the anode also increases withthe C-rate. In the case of cell C4 the lithium concentration gradientexists up to ∼1 μm in the anode. Thus with increasing C-rate not onlydoes the lithium buildup on the surface increase, but the lithium buildup in the sub-surface area also increases.

It is well known that a solid electrolyte layer (SEI) composed ofthe decomposition products of the electrolyte salt and the solvent isformed on the surface of the anode.30 The thickness of the SEI isusually of the order of tens of nanometer.241,242 This thickness of theSEI on a given type of anode varies depending on the electrolytecomponents, mode of cycling, overpotential, temperature, etc.243–246

The lithium concentration profiles for the anode presented here notonly indicate higher lithium content in the SEI layer at higher C-rate, but also show that the lithium concentration in the SEI layer ischanging from the outer edge to the core of the cylindrical cell aged ata certain C-rate. This has never been reported before in literature. Thisstudy reveals that the anode-electrolyte interphase cannot be assumedto be alike over the length of the anode in a cylindrical cell as is thecommon practice adapted in Li-ion cell modeling.

The analysis of the surface lithium concentration was also con-ducted and is presented in Fig. 43. A buildup of lithium on the surfaceas seen in the anode is not observed in cathode samples from differentcells. Since there is no buildup, it is certain that there is no lithiumplating occurring at the cathode surface. The initial expectation was adecrease in the lithium concentration in the aged sample as compared


Figure 42. (a) Surface lithium concentration of the anode samples taken fromcells aged with different C-rate. The surface concentration increases linearlywith C-rate. The surface concentration also increases from section 1 to 5within a cell. (b) Lithium concentration gradient in section # 3 of the anodesamples taken from cells aged with different C-rate. The concentration gradientincreases with C-rate up to a certain depth of the anode. The depth at whichconcentration gradient disappears increases with C-rate.67

to the unaged sample. The decrease in the lithium concentration in thecase of cells C1, C3, and C4 (Fig. 39) is not very prominent, but theresults in Fig. 40 are in good agreement with this hypothesis. There-fore, there is a critical C-rate beyond which the drop in the lithiumconcentration from the cathode is noticeable. In Fig. 43, the analysisof the lithium concentration gradient along the depth of the cathodeis shown for section # 3 of different cells. The lithium concentrationgradient observed on a particular section decreases exponentially withthe C-rate, as shown by the curve in Fig. 43. For example, in the caseof cells C0 and C4 the gradients are −1.63 × 1018 atoms/cm3/μm and−0.46 × 1018 atoms/cm3/μm. For a higher C-rate the concentrationgradient is lower, indicating that the flux available for diffusion oflithium into the cathode particles is decreasing. Thus the further cy-cling of the cells at still higher C-rate will be strongly affected. Sincethe concentration gradient has a negative slope, it indicates that thelithium diffusion within the LiFePO4 is restricted as the diffusion frontmoves toward the current collector. No fluctuations were observed inthe concentration profile as were observed by Whitney et al.238 Thus

Figure 43. Lithium concentration gradient in section # 3 of the cathode sam-ples taken from cells aged with different C-rate. The concentration gradientdecreases with C-rate.67

there is no structural breakdown of the cathode material, unlike thatconcluded by Whitney et al.238

The decrease in the lithium concentration can be explained by achange in the particle size or coarsening of the LiFePO4 nanoparticlesobserved in physical/morphological studies. Due to the coarsening ofthe nanoparticles, the diffusion length for the lithium increases withineach particle. As a result, the net uptake of lithium during the discharg-ing processes is low. During each charge cycle lithium diffuses outof the LiFePO4, and phase change occurs from LiFePO4 to FePO4.In the discharge cycle the lithium diffuses back in the host FePO4

particle, and the phase changes from FePO4 to LiFePO4. During theearly life of the battery the phase change from LiFePO4 to FePO4 andback to LiFePO4 might be complete, but as the particle size increasesdue to coarsening, the diffusion length changes, and this will affectthe phase change. The incomplete phase change continues to occurin subsequent cycles while the particle size tends to increase. Thusthe lithium retaining capacity of the particle drops in each subsequentcycle. The loss of active lithium in the cathode is directly related tothe drop in capacity of the battery while the increase in the particlesize and the subsequent increase in the diffusion length are directlyrelated to the rate capabilities of the battery.

In summary, The Li concentration profile across the electrodesof the cells at the end of life is affected by the C-rate of thecharge/discharge cycle and SOC of the battery. The Li concentrationprofile changes along the length of the electrode from outer edge tothe core of the cylindrical cell, but it remains constant along the heightof the electrode. In the case of the anode, the lithium concentrationprofile decays exponentially along the thickness of the anode. The Libuilds up on the surface of the anode, and the buildup rate increasesalong the length of the anode and also with the C-rate. This buildupbelow the surface extends to a higher depth in cells cycled at higherC-rate. There is no buildup of the lithium near the cathode surface.Beyond a certain critical C-rate the lithium concentration drops withincreasing C-rate, and it has a constant gradient along the depth ofthe cathode. The gradient of the lithium concentration profile in thecathode decreases with increasing C-rate. While the coarsening of theLiFePO4 particles limits the diffusion of the lithium in the cathode, thesurface concentration of the lithium on the anode increases with theC-rate. The quantitative measurement of the lithium profiles for theanode and cathode can prove instrumental in calibrating the diffusionmodels of the Li-ion cells.

Oudenhoven et al.,247 have demonstrated that lithium depth profilescan be measured in situ inside all solid state thin-film micro-batteriesto monitor the charging and discharging processes. Since NDP is only


sensitive for the 6Li isotope, a thin-film battery that contained a 6Li-enriched LiCoO2 cathode was analyzed, resulting in enhanced signals.They claim that depending on the materials composition and densityan analysis depth of up to 50 μm from the top surface can be obtained.

The battery that was analyzed in this measurement consisted ofa monocrystalline silicon substrate with a 200 nm Pt bottom currentcollector, a 500 nm LiCoO2 cathode, a solid-state electrolyte consist-ing of 1.5 μm nitrogen doped Li3PO4 (LiPON) and a 150 nm Cu topcurrent collector. The LiCoO2 and LiPON films were deposited usingmagnetron sputtering. The sputter chamber contained a LiCoO2 anda lithium phosphate target. The lithium-metal anode is formed duringthe first charge cycle by in situ lithium plating. On top of the coppercurrent collector a thick protective coating was deposited to protect thebattery stack. The material of the protective coating is not mentioned.

It is possible to in situ monitor the charge-discharge profile byintegrating the difference between the continuously measured NDPspectra and the spectrum of the as-deposited (discharged) battery inthe energy range of the cathode (475–960 keV) and the anode (1510–1625 keV). The amount of lithium removed or stored on both sides can,with this difference, be determined accurately, even when the depthprofile is relatively inaccurate. With this improved tolerance towarddepth inaccuracy, the NDP measurement time for each spectrum canbe reduced to less than 10 minutes, short enough with respect to the∼3 hour (dis)charging time to follow these processes in situ.

It was concluded that the (initial) exchange rate is very low, forexample, due to the absence of required Li vacancies in the elec-trode or electrolyte, or due to a high activation energy for the ionconductivity mechanism in these materials. During the charging pro-cess, the necessary exchange of lithium occurs between the cathodeand electrolyte. Oudenhoven et al.,247 claim that when the packaging

is sufficiently thin, it can also be applied to analyze classical liquidelectrolyte micro-batteries.

Nagpure et al.248 have studied copper current collectors with NDP.Figure 44a shows the high-resolution optical microscopy image of theanode cross-section. The copper current collector (CCC) of ∼6μmin thickness is visible between graphite coatings on either side. Thelithium concentration is measured for this thin CCC from both faces.Figure 44b shows the measured Li concentration profile from the twosurfaces of the CCC. The profiles from each surfaces resembles aclassic diffusion profile from surfaces similar to metalliding or car-burization. The profile was reproducible for different CCC samples.The profile from the front face has a maximum of 0.025% atomic Liand the profile from the back face has a Li concentration of 0.08%atomic Li. The measured profiles do not have the same maximum atthe surface, but show similar exponential decay along the thicknessof the CCC. The data should not be confused with a plating of Lion the CCC surface as the NDP measurements indicate that Li haspenetrated into the copper sub-surface.

The first principle calculations by Van de Walle et al.249 haveshown enhanced Li solubility (30 at.%) in FCC copper at 400 K.Also, the calculated phase diagram using differential thermal analysisand electromotive force measurements from high temperature havesuggested 18 at.% solubility of Li in copper.250 Therefore, the tendencyfor Li diffusion into the CCC should be expected. During operation ofthe battery there exists a high concentration of Li atoms at the CCCsurface, especially when the battery is fully charged. However, at theoperating temperature of the batteries diffusion of Li to form copperalloys is not expected due to high activation energies.251 Suzuki et al.252

have concluded that it is possible for mass transfer across a copper filmcoated on a carbon fiber using electrochemical insertion and extraction

Figure 44. (a) Anode (Graphite-Cu-Graphite) showing the electrode structure; and (b) measured lithium concentration profile from the two surfaces of the coppercurrent collector (adapted from Nagpure et al.248).


mechanisms. However, they have not reported measurements showingthe presence of Li within the CCC films.

Presence of Li in the CCC indicates the loss of cyclable Li. Amonglosses of active Li, the loss into the CCC is responsible for the loss ofelectrical capacity of the battery. The diffusion of Li into the CCC canalter its both electrical and thermal behavior. The increased levels of Liin Cu would change battery impedance and eventually degrade batteryperformance through ohmic losses. The residual resistivity of the CCCwill be affected due to the Li impurity, as given by Nordheim’s rule:253

ρr (x) =Ax [7.7]

where ρr (x)is the residual resistivity of Cu due to Li impurity, A isa constant and the x is the impurity concentration. Also, change inthe thermal properties and local heating due to increased impedancecan cause delamination between the CCC and the active graphitecoating, leading to a further increase in the overall battery impedance.These effects, now evident from these measurements, should be givenconsideration while building battery performance and aging models.Only then can accurate estimates of the performance and aging ofthe Li-ion battery be established to guide the successful deploymentin electric vehicles. Even though a specific mechanism for the abovephenomena eludes us, the discovery is significant for aging studies ofLi-ion batteries.

In summary, neutron depth profiling has been used to characterizethe copper current collector used in the real life Li-ion battery. Thedata shows the presence of lithium in the CCC with a profile similarto a metalliding or carburization process. The presence of lithiumin the CCC will affect its thermal and electrical behavior during theoperation of the battery. The presence of lithium beyond the activematerial and in the CCC suggests that the degradation and loss ofactive Li in the current collectors cannot be ignored in efforts for theoverall understanding of the aging mechanisms predicting the life andperformance of the batteries.

Summary.— In summary, the chemical and structural characteri-zation of the LiFePO4 nanoparticles reveals changes in the lithiumconcentration, local lithium bonding and local Li environment. Ac-cording to the XRD studies both LiFePO4 and FePO4 phases co-existed in the aged samples. The presence of the FePO4 could indi-cate that there are regions within the cathode strip that are inactiveduring the charging-discharging process. A more quantitative analysisof the phases present within the samples is necessary to identify theratios of the inactive material. The change in the volumetric concen-tration of the active material would be a very important input to theelectrochemical and performance models of the Li-ion batteries.

Raman studies show the degradation in the quality of the carboncoating. This has a direct effect on the electronic conductivity ofthe composite cathode material. Due to the loss in the quality ofthe carbon, the electrical resistance between the particles and theparticles and the current collector can increase, leading to the loss ofperformance of the batteries. EELS showed that the density of statesfor O changes as the cell ages. This was evident in the presence of thepre-peak in the case of the O K edge. The increase in the ratio of the pre-peak to the O K edge peak in the EELS data from the core to the surfaceof the large LiFePO4 particle indicates a different lithium compositionwithin the particle. There is also a shift of almost 2 eV for the L2,3 edgeof Fe in the aged sample. At a certain age of the cell the particles start tocoarsen. The ion diffusion length is expected to increase in the coarserparticle, and this is expected to lead to an incomplete transformationbetween LiFePO4 and FePO4 while charging and discharging. TheFePO4 core is expected to expand in subsequent cycles, thus reducingthe capacity of the host cathode material. The experimental resultswhen analyzed with the help of simulated ELNES spectra for theolivine structure (space group Pnma) of LixFePO4 with x = 0, 0.25,0.5, 0.75, and 1 showed 80% loss of Li in the aged cathode suggestinga strongly Li depleted, but not completely Li free, core region inthe coarsened particles. Thus coarsening of the nanoparticles and theincrease of the FePO4 phase within the coarsened particle will lead tothe loss of performance of the batteries.

NMR and NDP are used to overcome the limitation of electronspectroscopic studies in detecting the lithium in the samples. Accord-ing to the NMR studies a single Li environment is present in theunpaged sample. The absence of the Li peak in the aged sample re-asserted the results of the EELS, suggesting the loss of active Li fromthe host cathode material. The loss of active Li directly affects the cy-cling capacity of the battery. NDP measurements help in quantifyingthe loss of the active Li. The Li concentration profile measured withNDP across the electrodes of the cells is affected by the C-rate of thecharge/discharge cycle of the battery. The Li concentration profile isalso affected by the state of charge of the cell. NDP measurementshave also proved the effects of the cell shape and size on the aging ofthe battery. The Li concentration profile changes along the length ofthe electrode from the outer edge to the core of the cylindrical cell,but it remains constant along the height of the electrode. In the caseof the anode, the lithium concentration profile decays exponentiallyalong the thickness of the anode. The Li builds up on the surface ofthe anode, and the buildup rate increases along the length of the anodeand also with the C-rate. This buildup below the surface extends to ahigher depth in cells cycled at a higher C-rate. There is no buildup ofthe lithium near the cathode surface. Beyond a certain critical C-ratethe lithium concentration drops with increasing C-rate, and it has aconstant gradient along the depth of the cathode. The gradient of thelithium concentration profile in the cathode decreases with increasingC-rate.

Modeling

Battery models can be used to predict the performance of the bat-tery, optimize the design parameters and predict the life of the cellunder various operating conditions. The models vary in complex-ity, and can be as simple as based on a power law or as complexto include detailed physiochemical phenomena. Li-ion battery per-formance models can be categorized mainly as equivalent electricalcircuit models (EECM) or first principles based physiochemical mod-els. There are certain other types of models such as the model based onPeukert’s law, or based on the artificial neural network, which fall in adifferent category than the two discussed here. In the following discus-sion we review the framework of four EECM and two electrochemicalmodels. We will also discuss an empirical model developed for theLiFePO4 cells based on extensive aging studies. Then we will discussa couple of methods to introduce aging effects in the electrochemicalmodels.

Equivalent electrical circuit models.— The simplest method tomodel the electrochemical performance of the battery is by using theregular electrical elements. The common elements such as resistor,capacitor, inductor, etc. are used to model the performance of thebattery. The circuit with these elements represents the overall electro-chemical performance of the battery. These models lack the detailsnecessary for accurate prediction of the performance of the battery.The models are still popular as they offer less computation and arevery suitable for control applications, such as on-board battery diag-nostic and prognostic, state of charge estimation, and state of healthestimation.

These models rely on the electrochemical impedance spectroscopydata (EIS) and employ an equivalent circuit with common electricalelements that emulate the complex impedance data. The EECM canhave three major components: a static component in the form of asource representing the open circuit voltage (OCV), a dynamic com-ponent that represents the kinetic aspect of the cell internal impedanceand a load.254

Simple battery model.—The most simple battery model can be thoughtof as an electrical circuit with a resistance in series with an ideal volt-age source, as shown in Fig. 45a.255,256 The ideal voltage represents anideal battery with open circuit voltage (E0). The actual battery termi-nal voltage (Vb) is then given by the voltage drop across the constantresistance (Rb). This resistance represents the internal resistance of the


Figure 45. Different equivalent electrochemical circuit models. (a) Simplebattery model, (b) Thevenin model, (c) Dynamic model (adapted from Durret al.256).

battery. But the model fails to account for the true internal resistanceof the battery as the internal resistance is assumed to be constant inthis model, while the actual resistance is a function of the state ofcharge, and electrolyte concentration. Thus the model is limited toapplications where the state of charge can be assumed to be constantor the effect of the state of charge can be neglected.Thevenin model.—The other commonly used model is the Theveninbattery model based on the Thevenin theorem. This model consistsof a parallel circuit of capacitance (C0) and overvoltage, resistance(R0) is connected in series with an internal resistance (R) in serieswith ideal battery voltage (E0) (Fig. 45b).256–258 C0 represents the ca-pacitance of the double layer formed at the interface of the electrodeand the electrolyte due to charge separation. The R0 represents thenon-linear resistance between the electrodes and the electrolyte. Thismodel again fails to recognize that the various components consid-ered here depend on the state of charge of the battery. The constantvalue assumption of the components leads to the main drawback ofthis model in predicting the performance of the battery. The modelsometimes assumes different sets of parameters at different states ofcharge, but this limits the continuous battery evaluation.259 The modelalso fails to account for the faradaic processes within the battery.256

Dynamic model.—The Thevenin model has been expanded to accountfor the non-linear behavior of the parameters to develop the DynamicModel of the battery performance.256,257,260 The model can be repre-sented as shown in Fig. 45c.256 Vb is the battery terminal voltage.The battery as a voltage source is represented by an equivalent ca-pacitor (Cb). This helps in considering the SOC as the charge stored

Figure 46. Cell polarization curve as a function of the applied current.22

in the capacitor. Rp represents the small leakage current in the bat-tery, which depends on the open circuit voltage. Ric and Rid representthe resistance of the electrolyte and the electrodes. The values areconsidered to be dependent on the charge discharge process. The ac-tivation overpotential and the overpotential due to the mass transportare represented by the parallel R-C circuit. R0c and R0d represent thevoltage drop during charging and discharging respectively while C0

represents the capacitance due to the double layer at the interface ofthe electrode and the electrolyte. The values of the various elementsof the circuit are considered to be a function of the open circuit volt-age (OCV). Thus this model predicts the behavior of the battery withbetter accuracy as compared to other EECM models.

First principle electrochemical model.— These models are basedon the physiochemical processes within the cell and apply the elec-trochemical kinetic and transport phenomena to predict the behaviorof the cell.261 Whenever a current flows from the cell during chargingor discharging a shift in potential of the cell is observed.22,262 As seenin Fig. 46 the potential deviates from the equilibrium potential andcauses the cell polarization.

There are several key aspects of lithium-ion batteries that must beconsidered in any model of their behavior. The electrodes are gener-ally porous, and therefore the distribution of the reaction through thedepth of the electrode must be considered. The active material is aninsertion compound, in which the chemical potential and other ther-modynamic properties may vary continuously with inserted lithiumconcentration, and solid-state diffusion of lithium through the activematerial must be considered. Finally, as in most batteries, the elec-trolyte is a concentrated, nonideal solution, and mass transport acrossthe electrolyte has a significant effect on battery performance.263

The symbols used in the following discussion are summarized inTable VIII.Pseudo 2D (P2D) model.—The P2D model is based on the porouselectrode theory, concentrated solution theory, Ohm’s law, Butler-Volmer kinetics, and charge and mass balance.264,265 The electrodesused in the battery are porous electrodes to provide the large surfacearea for the electrochemical reactions. The porous electrode theoryhelps in modeling the actual porous electrode, which is a mixture ofactive material, binders, filler material, and electronic conductive coat-ing. The porous electrode theory treats the structure of the electrodeas the superposition of active material, electrolyte, and filler material.This leads to the simplification of the structure and the ability to con-sider the ohmic potential drop and mass transfer that occur in bothseries and parallel during the electrode processes across the surface.266

Each phase is considered to have its own volume fraction. The mate-rial balances are averaged about a volume small so that they are smallwith respect to the overall dimensions of the electrode but large withrespect to the pore dimensions. This simplification allows one to treatthe electrochemical reaction as a homogeneous term, without having


Table VIII. List of symbols used in Modeling section.

List of Symbols

aj specific area of the porous electrode ‘j’ (m2 m−3)Aj surface area of the electrode ‘j’ (m2)brug Bruggman’s coefficientc1, j concentration of lithium (mol m−3)cs,j average concentration of lithium in the solid phase of

electrode ‘j’ (mol m−3)1,j solid phase concentration of lithium at the surface of the

sphere (mol m−3)D1,j diffusion coefficient of lithium in the solid phase inside

electrode ‘j’ (m2 s−1)D2,eff effective diffusion coefficient of lithium in the solution

phase (= D2,jε2brug) (m2 s−1)

D2 diffusion coefficient of lithium in the liquid phase (m2

s−1)F Faraday’s constant (C mol−1)i0j,side exchange current density for the side reaction (A m−2)J applied current (A)Jj local volumetric current density for intercalation reaction

(A m−3)Js,j side reaction current (A)Js,j local volumetric current density for side reaction (A m−3)k rate constant for electrochemical reaction (A m−2 mol

m−3) (1 + α)

L length of the cell (m)Ms,j molecular weight of the side reaction product (kg mol−1)r radial coordinate (m)Rj radius of the particle (m)RSEI resistance of the film (�m−2)R universal gas constant (J mol K−1)t time (s)T temperature (K)V cell voltage (V)x coordinate across the thickness of the cell (m)y scaled radial co-ordinate (= rL/Rj) (m)

Greekα transfer coefficients of the electrochemical reactionε volume fraction of a phaseϕ local potential of a phase (V)η over potential driving a reaction (V)κ Ionic conductivity of the electrolyte (S m−1)σeff effective conductivity of an electrode (= σεj) (S m−1)σ conductivity of the electrode (S m−1)ρs,j density of the side reaction product (kg m−3)δf film thickness (m)

Subscript1 solid phase2 liquid phasej = n or pp positive electroden negative electrodes side reaction propertysep separator

to worry about the exact shape of the electrode–electrolyte interface,which can lead to heterogeneity in the electrode process.263

The electrolyte that fills the pores of the porous electrode is mostlya binary electrode with a lithium salt and organic solvent. The driv-ing forces arising due to the chemical potential and the mass fluxwithin this liquid phase is modeled using the concentrated solutiontheory.53 The charge balance is applied to the charge flowing fromthe electrode surface to the electrolytes during the electrochemicalreaction. The mass balance is applied to account for the change ofthe concentration within the electrolyte due to the mass transfer at theelectrode-electrolyte surface.263

The potential drop in the electrode and the electrolyte is modeledusing Ohm’s law. The kinetics of the electrochemical processes is

Figure 47. Schematic of the Li-ion cell to demonstrate the layout of the(a) pseudo 2D model, and (b) single particle model (adapted from San-thanagopalan et al.81).

modeled with the Butler–Volmer equation that gives the relationshipbetween the current density and the overpotential. The relationship de-pends on the exchange current density also known as the rate constant.All of these equations form a set of coupled non-linear differentialequations having various dependent variables, such as the concentra-tions of the active material, the potential drop, and the reaction rates.Hence their solution requires a rigorous numerical treatment such asthe finite-difference technique.

Fuller et al.267,268 have laid the foundation for the mathematicalmodel of lithium-ion batteries based on the porous electrode the-ory. The model was further simplified by Doyle and Newman.269,270

The model and the equations presented here follow the work by Ra-madass et al.271 The schematic of the model is shown in Fig. 47a.The schematic shows three areas within the cell, namely the negativeelectrode, the separator and the positive electrode. The negative andthe positive electrodes are the porous composite electrodes made ofactive material, binder and filler material. The potential drop acrossthe separator is assumed to be zero and thus no current flows throughthe separator. For modeling purposes the cell can be considered tohave two separate phases, the solid phase that represents the negativeand the positive electrodes and the liquid phase that represents theelectrolyte.

The solid phase is assumed to be comprised of identical sphericalparticles. In the solid phase the diffusion of lithium along the radialdirection is considered to be the predominant transport mode. Thusconcentration of lithium needs to be calculated along the pseudo radialdirection at each x interval. This gives the model its name of P2Dmodel. In the case of the liquid phase, the concentration and thepotential is assumed to vary only in x direction and it is solved for byapplying the concentrated solution theory.

The overpotential in the negative and the positive electrode can begiven as:

η j = φ1, j − φ2 − U θj [8.1]

The open circuit potential (OCP) (U θj ) is often determined experimen-

tally. The OCP can be a function of the state of charge of the battery.


The model is setup to determine the values of the potential of eachelectrode (φ1, j ) and the liquid phase potential (φ2).

In the case of the electronically conducting solid phase, as per thecurrent conservation and Ohm’s law, the potential distribution is givenby,

∇ · (σ j,e f f ∇φ1, j ) − Jj = 0 [8.2]

Further the lithium concentration within the solid phase is given by,

∂c1, j

∂t= D1, j

r 2

∂

∂r

(r 2 ∂c1, j

∂r

), c1, j = c1, j |r = R j [8.3]

Finally, the Butler-Volmer equation governs the kinetics of the elec-trochemical reactions and carries the overpotential term.

Jj = a j k j

(cmax

1, j − c1, j

)1/2(c1, j )

1/2(c2)1/2

×{

exp

(αa F

RTη j

)− exp

(−αc F

RTη j

)}[8.4]

In the case of the liquid, the potential distribution is given by,

∇ · (κe f f ∇φ2) + ∇ · (κD∇ ln c2) + Jj = 0 [8.5]

Finally, the mass transport through the liquid phase is governed by,

ε2∂c2

∂t= ∇ ·

(Def f

2 ∇c2

)+ (1 − t+)

FJ [8.6]

As stated earlier, and evident through the governing equations, themodel involves two different length scales, the thickness of the cell(L) that is several order of magnitude higher than radius of the particle(Rj). Adanuvor et al.,272 Verbrugge,273 and Verbrugge and Koch274

have suggested methods to avoid instabilities arising due to these twodistinct length scales. Ramadass et al.271 scales the radial coordinateas follows,

y = rL

R j[8.7]

Single Particle (SP) model.—Haran et al.275 presented a simpler rep-resentation of the electrode. This was first presented for the metalhydride system and later extended to the lithium ion system.81,276 Inthis model, each electrode is represented by a single spherical parti-cle. This approach is popularly referred to as the single particle (SP)model. The simplified single particle model is orders of magnitudefaster, however it does not account for all the physical processes.For example, the solution phase diffusion limitations are ignored, andthus the validity of the model is limited. In this model the overallframework of the PE model is maintained but instead of consideringindividual particles, each electrode is represented by a single sphericalparticle whose area is equivalent to that of the active area of the solidphase in the porous electrode. A schematic of this model is providedin Fig. 47b. This model assumes that the limitations posed by thesolution phase of the cell are negligible. Hence, the solution phase isnot considered while developing the model equations and so φ2 is setto zero in the above equations.

Based on this simplification the electrode potential is a function ofonly the overpotential and the OCP as follows,

η j = φ1, j − U θj [8.8]

The Butler-Volmer kinetics is then given by,

J = Iapp [8.9]

Jj ± A j k j F(cmax

1, j − c1, j

)1/2(c1, j )

1/2(c2)1/2

×{

exp

(αa F

RTη j

)− exp

(−αc F

RTη j

)}= 0 [8.10]

Modeling aging effects in graphite-LiFePO4 cells.— The abovemodels simulate the discharge curve of the batteries. There have beenseveral different attempts to include aging models or, in other words,capacity fade models in the above sets of equations. Here we discussthe three different kinds of capacity fade mechanisms incorporated into the basic model of the lithium-ion batteries to understand the agingof the batteries.Empirical model.—Wang et al.,72 based on their extensive acceleratedaging studies of large format cells, developed an empirical model.They have shown that the cells used at high temperatures and highdischarge rates have short cycle life. It was observed that the capacityloss is strongly affected by cycling time and cell temperature, whilethe effect of DOD is negligible at low C-rates such as C/2. Using acurve-fitting technique, they demonstrated that capacity fade followeda power law relationship with charge throughput between 15◦C and60◦C. The model parameters varied depending on the C-rate. Insteadof having different model parameters for the different C-rates, theysimultaneously fitted the experimental data for all C-rates and foundthe optimal values of the pre-exponent factor, B for each C-rate byminimizing the error (difference between measured value and themodel value). The following is the model they have proposed for thecapacity fade

Qloss = B. exp

⌊−31700 + 370.3 × C-rate

RT

⌋(Ah)0.55

[8.11]Ah = cycle number × DO D × 2

where Qloss is the percent of the capacity loss and Ah is the totalAh-throughput which is directly proportional to the cycling time atthe given C-rate. The values of B are obtained by curve fitting thedata from several cells at different C-rates. The values of B are 31630(C/2), 21681 (2C), 12934 (6C), and 15512 (10C). For all C-rates, themodel equations indicated that the power law factors were valued veryclose to 0.5. The square-root of time dependence was considered tobe consistent with the aging mechanisms that involve diffusion andparasitic reactions leading to loss of active lithium.Effect of solid electrolyte interphase.—The most prominent aging ef-fect modeled for the lithium ion batteries is the SEI formation. This ismodeled as a potential drop across the SEI layer formed on the anodesurface due to the side reaction. Darling and Newman277 includeda side reaction that occurs in a propylene carbonate (PC)/LiyMn2O4

system in which they were able to predict the importance of the stateof charge and self-discharge of the battery with cycling. Later Aroraet al.75 simulated the phenomenon of capacity fade by consideringthe lithium deposition as a side reaction during over-charge condi-tions and extended this concept to the increase in the thickness of thesurface film with cycling. Here we discuss the model by Ramadasset al.271 in which the potential drop across the film was expressed as afunction of the film thickness, which varied with time in accordancewith Faraday’s law, as shown in the Eq. 8.11.

∂δ f, j

∂t= − Js, j Ms, j

a jρs, j F[8.12]

The loss of active material due to the side reaction and the resultantadditional drop in the anodic overpotential were used to account forthe capacity fade in the cell as given by Eq. 8.12.

Js, j = −a j i0j,side

{− exp

(αc F

RTη j

)}[8.13]

Thus the potential of the negative electrode is given by,

ηn = φ1,n − φ2 − U θn − (Jn + Js,n)δ

anκ[8.14]


Figure 48a shows the results of this model for different number ofcycles. As can be seen, the capacity of the cell faded after a numberof cycles.Effect of change in porosity.—Sikha et al.278 have modeled the effectof the porosity change of the negative electrode on the capacity fadeof the battery. They have assumed that during the operation of thebattery, due to the side reaction and its products, plugging of poresin the negative electrode occurs. This leads to a change in the surfacearea of the active material and a loss of active material due to theside reaction. They have tried to overcome the use of any empiricalrelationship to examine the effect of the side reaction and the porositychange on the capacity fade of the battery. Their model is based onthe model developed by Evans et al.279 for the lithium/thionyl chlorideprimary cell.

The governing equation for the porosity effect is the overall mate-rial balance in the matrix phase is,

∂ε j

∂t= −

∑k=1,2

solid phases∑i

a j js, j,k Vi j = n, p [8.15]

Here aj, the surface area to volume ratios is given by,

a j = 3

(1 − ε j − ε f, j

Rs, j

)j = n, p [8.16]

The results of the model are shown in Fig. 48b. The capacity is seendropping after each cycle due to change in the porosity.Effect of change in particle size.—Nagpure et al.67 have observedcoarsening of the cathode nanoparticles during aging of the batteries.Tang et al.280 have modeled the effect of particle size in nanoscaleolivines. This effect can also be modeled into the basic model dis-cussed above. Figure 48c shows the effect of the change in particlesize on the performance of the batteries. These results were obtainedby using the BAND subroutine.267,268,281 The change in the particlesize affects the diffusion rates and leads to a change in the powerrating of the cell. As seen in the Fig. 48c the resistance of the batter-ies changes which increased the particle size. This affects the powerrating of the battery.

Summary and Outlook

The increasing awareness about greenhouse gases has led to thedemand for clean renewable energy sources. The goal to reduce CO2

emissions from concentrated sources, such as coal fired power plantsor distributed sources such as automobiles, along with reduced depen-dency on foreign oil can be achieved with efficient electrical energystorage devices. Understanding the degradation mechanisms in theEES is instrumental in developing safe, reliable and efficient deviceswith long cycle life.

The automobile industry is actively pursuing the development ofelectric vehicles and has adopted battery technology as EES devices.Recently, advanced Li-ion batteries have been actively pursued asthe electrical energy storage device for electric vehicles (EV), hy-brid electric vehicles (HEV) and plug-in HEVs (PHEV) due to theirhigh energy and power density over other battery chemistries. Use ofcurrent Li-ion batteries or future Li-air batteries in EV, HEV, PHEV,and also the temporary storage systems for renewable energy sourceswould reduce the dependence on fossil fuels and provide a cleanenergy technology.

While the mechanism of the operation of these batteries is known,the aging mechanisms are still under investigation. Aging of the cellsat the macroscopic or system level is quantified by the change in theinternal resistance measured by impedance techniques. To understandthe related loss of capacity, it is imperative to understand the degrada-tion of the electrode materials of the battery. The degradation of thematerial is caused by several simultaneous physiochemical processesthat occur within the batteries and that makes material characterizationof the electrodes a challenging task.

Figure 48. Results of various aging effects included in the electrochemicalmodels. (a) Effect of formation of solid electrolyte interphase on capacityfade (adapted from Ramadass et al.271). (b) Effect of number of cycles whichcorrespond to change in porosity of the electrode on the capacity fade (adaptedfrom Sikha et al.278). (c) Effect of change in the particle size on the performanceof the battery based on the BAND subroutine.


Performance of any electrode material is investigated by testingthese materials in a small experimental (so-called coin) cell. In com-mercial batteries the electrodes are made up of nanomaterials to lever-age the effects of high surface area. These nanomaterials are packedtogether on either copper or aluminum current collector strips. Theselong electrode strips are then rolled and packed into a cylindrical can.Thus commercial batteries are larger in size as they provide the nec-essary building blocks for the battery packs. The effects of scaling inthe commercial cell might be overlooked if the results of the so-calledcoin cell experiments are to be believed alone. This further adds to thecomplexity of analyzing the degradation mechanisms in commercialbatteries. As such a systematic multi-scale characterization plan isnecessary to understand the degradation mechanisms of the battery.

The electrodes within the battery have been characterized by sev-eral different techniques with resolutions ranging from mm to nm.Techniques including thermography, scanning electron microscopy(SEM), transmission electron microscopy (TEM), atomic force mi-croscopy (AFM), X-ray diffraction (XRD), Raman spectroscopy, nu-clear magnetic resonance (NMR) and neutron depth profiling (NDP)have been applied at different length scales to obtain spatial and tempo-ral data about the degradation of the electrode materials. Such multi-scale characterization plans are applicable to any existing batterychemistry or upcoming battery chemistries such as Li-air, metal-airetc. In this overview paper a review of the results of such a multi-scalecharacterization applied to LiFePO4 based Li-ion batteries has beenpresented.

Thermography maps provide the necessary visual data of the cath-ode strips in identifying the damaged areas for further characterization.Once the areas of interest are identified, SEM and AFM are useful instudying the surface morphology and grain coarsening at μm to nmlength scales. AFM is also useful in studying certain functional prop-erties, such as surface resistance and surface potential. TEM provideshigh-resolution micrographs for particle analysis. Electron energy lossspectroscopy (EELS) is useful in identifying the bonding of the ele-ments in the active material. XRD provides useful information aboutthe lattice parameter, and Raman gives information about the carboncoating over the LiFePO4 nanoparticles. NMR is useful in identifyingthe different chemical compositions of the LiFePO4 nanoparticles af-ter aging. NDP is instrumental in providing the lithium concentrationprofiles in the electrodes. These multi-scale studies reveal changes inthermal diffusivity, permanent phase change, structural disordering,coarsening of nanoparticles and loss of active lithium in the cathodeover the life of the battery.

Coarsening has been identified as a major aging parameter in thesestudies, but quantifying the coarsening of the nanoparticles has re-mained a major challenge. Since the commercial cathodes are denselypacked, identifying the correct particle size distribution has been adifficult task so far. High-resolution imaging combined with imageprocessing algorithms would be necessary to establish the particlesize distribution in the cathode. Such a distribution would be a veryimportant input to the modeling process as one can vary the distri-bution as the function of the aging of the battery and identify itsperformance.

The different Li-ion battery models are available to predict electro-chemical performance and aging. The models are briefly categorizedas equivalent electrical circuit (EECM) models or first principles basedphysiochemical models. The EECM models are the simplistic modelsbased on the cycling studies of the batteries. These types of modelslack the details necessary for predicting the performance of the bat-teries with a high degree of accuracy. Nevertheless, because of theirlow computation requirement they are popular for any on-board bat-tery management system. The first principles based physiochemicalmodels have a high degree of accuracy and represent mathematicallythe various processes within the battery during the charge/dischargecycle. Due to the heavy computation necessary to solve the set of lin-ear differential equations, they are not suitable for an on-board batterymanagement system. The coarsening effect, observed as a result ofthe multi-scale characterization of the cathode material, was simulatedwith Newman’s model. The simulation results show a loss of capacity

of the battery with an increase in the particle size of the active cathodematerial.

The aging mechanisms identified above need to be further investi-gated. The multi-scale techniques that give spatial information shouldbe applied such as to get the temporal data of the aging mechanisms.The above study was conducted on the batteries aged untill they lost20% of their capacity. Thus only the final effects of aging are visiblethrough characterization. The batteries should be aged to differentdegrees between 100% and 80% capacity and then characterized ac-cording to the multi-scale techniques. Such a study would provideknowledge about the on-set of aging and its progress through the lifeof the battery.

Aging of the batteries remains a challenge in such studies, becauseas the chemistries improve the life of the batteries also improve. Butto achieve conditions and see the effects of cycling similar to the reallife aging cycle, the batteries should be aged properly with a syntheticaging cycle. Often even in a synthetic aging cycle the battery aginghas be accelerated to accomplish the studies within a certain timelimit. Thus one should study the effects of accelerated aging cycleson actual aging of the batteries. These effects should then be filteredfrom the data to identify the true aging mechanisms.

Lastly, the studies selected in the multi-scale characterization arenot limited to the device or to the chemistry of the device. They canbe easily extended to the future generations of EES including, but notlimited to, Li-air, and Li-metal.

APPENDIX A1: COMPARISON OF BATTERYCHEMISTRIES

BatteriesA battery is a device that stores electrical energy in chemical form, and by the prin-

ciple of a galvanic cell, it converts this chemical energy into electricity when connectedto an external load. A galvanic cell is a device consisting of an anode and a cathodedipped in an electrolyte, and it produces electricity by a spontaneous reduction- oxida-tion (redox) reaction. Batteries are classified according to their chemistries. Dependingon the chemistry of the battery, different materials are used to make its components.Table A1.1 summarizes the properties of various battery chemistries, while Table A1.2lists the advantages and limitations of these batteries. These different battery chemistriesand their advantages and limitations are briefly discussed here.

Lead-acid

French physician Gaston Plant introduced the lead acid battery in 1859. It was thefirst commercially available rechargeable battery. Though many battery chemistries wereintroduced later on, lead acid is still used in a lot of applications due its cost effectivenessand ruggedness. Because of gassing and water depletion, this battery can never be chargedto its full capacity. Also, each time the battery is discharged completely, it tends tolose a small amount of its capacity. Because of the lead content, this battery is treatedas non-friendly to the environment. They are used in wheelchairs, hospital equipment,automobiles for auxiliary equipment, and uninterruptible power supply systems.

Nickel-Cadmium

The nickel-cadmium battery was invented in 1899 by a Swedish man, WaldmarJungner. In 1947, Neumann was successful in introducing the completely sealed versionof this battery. This battery chemistry has a moderate energy density and a long cycle life.The main drawback of this battery chemistry is the memory effect, in which the batterygradually loses its maximum energy capacity if it is repeatedly recharged after being onlypartially discharged. Though the metals used are toxic, it remains a favorite choice inareas where the most rigorous charge-discharge cycles are expected. Because of its abilityto draw heavy load currents, it is also a favorite choice in applications like power tools.

Nickel-Metal hydride

Development of the nickel-metal hydride battery started in 1970. Only after stablemetal hydride alloys were developed in 1980, was this battery available for consumers.The cathode in the Ni-MH battery is composed of nickel hydroxide. The anode is mostlycomposed of an intermetallic compound of type AB5, where A is a rare earth mixture oflanthanum, cerium, and titanium, and B is nickel, cobalt, manganese and/or aluminum.The materials used in this battery are non-toxic. Though it is better in some aspects thanthe nickel-cadmium battery, it shares some of its drawbacks with the nickel-cadmiumbattery due to the nickel technology. The cycle life of this battery is less than that of thenickel-cadmium. It has a higher energy density compared to nickel-cadmium and showsno memory effect. Before the lithium-ion battery was introduced, the nickel-metal-hydridebattery was used in mobile computing and wireless communications. It is often believed


Table A1.1. Characteristics of commonly used rechargeable batteries.52

Lead-acid(sealed) Ni-Cd Ni-MH

Li-ioncobalt oxide

Li-ionmanganese

Li-ionphosphate

Commercial use since 1970 1950 1990 1991 1996 2000Gravimetric energydensity (Wh/kg)

30–50 45–80 60–120 150–190 100–135 90–120

Internal resistance(m�)

<10012 V pack

100 to 2006 V pack

200–3006 V pack

150–300 pack100–130 per cell

25–75 per cell 25–50 per cell

Cycle life (to 80% ofinitial capacity)

200–300 1500 300–500 300–500 Better than300 to 500

> 1000

Fast charge time (h) 8 to 16 1 2 to 4 1.5 to 3 1 or lessOvercharge tolerance High Moderate Low Low. Cannot tolerate trickle chargeSelf-discharge/month(room temperature)

5% 20% 30% <10%

Cell voltage (V) 2 1.25 1.25 Nominal 3.6Average 3.7

Nominal 3.6Average 3.8

3.3

Load current:Peak 5 20 5 <3 >30 >30Best 0.2 1 0.5 or lower 1 or lower 10 or lower 10 or lowerOperatingtemperature (◦C)

−20 to 60 −40 to 60 −20 to 60 −20 to 60

Maintenancerequirement

3 to 6 months 30 to 60 days 60 to 90 days Note required

Safety Thermallystable

Thermallystable Fuse

recommended

Thermallystable Fuse

recommended

Protectioncircuit mandatory

Stable to150 (◦C)


Stable to250 (◦C)


Stable to250 (◦C)

Toxicity Toxic leadand acidsharmful to

environment

Highly toxicHarmful to

environment

Relativelylow toxicity,

should berecycled

Low toxicity, can be disposed in small quantities

Table A1.2. Advantages and limitations of commonly used rechargeable batteries (adapted from Buchmann52).

Advantages Limitations

Lead-acid (sealed) Very inexpensive and simple to manufactureWell-developed technologyLowest self-dischargeLow maintenance- no memory effect, no electrolyte to fill onsealed versionCapable of high discharge rates

Low energy density – limits use to stationary and wheeledapplicationsVoltage should never drop below 2.1 VAllows only limited number of full discharge cyclesEnvironmentally unfriendly due to the lead contentThermal runaway can occur due to improper chargingSome versions can never be charged to their full potential

Nickel-cadmium Fast and simple chargeHigh cycle lifeGood load performance Long shelf lifeEasy storage and transportationGood low temperature performanceOne of the most rugged rechargeable batteriesLowest in terms of cost per cycleAvailable in a wide range of sizes and performance options

Relatively low energy densityShows memory effectEnvironmentally unfriendly and so some countries restrict itsuseRelatively high self-discharge- needs recharging after storage

Nickel-metal-hydride

30–40% higher capacity than standard nickel-cadmiumLess prone to memory effect than nickel-cadmiumSimple transportationEnvironmentally friendly - contains only mild toxins; profitablefor recycling

Limited service life of 200–300 cyclesRelatively short storage lifeLimited discharge currentMore complex charge algorithm due to heat generated duringchargingTrickle charge settings are critical because the battery cannotabsorb overchargeHigh self-dischargeShould be stored in cool place at 40◦C High maintenance

Lithium-ion Highest gravimetric energy density (Wh/kg)Does not need prolonged primingRelatively low self-dischargeLow Maintenance - no memory effectCells with high current capacity can be manufactured for powertool applications

Requires protection circuit to maintain voltage and currentwithin safe limitsAging is a major issueExpensive to manufacture


among researchers that nickel-metal-hydride led to the development of the lithium-basedbattery.

Lithium-ion

The research for lithium-ion battery technology started with lithium batteries. In1912, G. N. Lewis began working on lithium batteries. Lithium (atomic number 3, group1, period 2) was used as an anode in lithium batteries. Lithium is an alkali metal, andbeing the lightest of the metals with the greatest electrochemical potential, it has thelargest energy density for weight. But lithium is very unstable, as it has only one valenceelectron. This made lithium batteries very unsafe for commercial use, and so researchshifted from a lithium battery to a lithium-ion battery, which is a much safer option.

APPENDIX A2: A GUIDE TO UNDERSTANDING BATTERYSPECIFICATIONS (Taken from MIT Electric Vehicle Team,

December 2008)

Battery basics

The different battery classifications you might see in the electric vehicle literature arediscussed here.

� Cell, Module, and Pack: Hybrid and electric vehicles have a high voltage batterypack that consists of individual modules and cells organized in series and parallel. A cellis the smallest, packaged form a battery can take and is generally on the order of one to sixvolts. A module consists of several cells generally connected in either series or parallel.A battery pack is then assembled by connecting modules together, again either in seriesor parallel.

� Battery Classifications: There are several ways batteries are classified. Firstlythe batteries are classified based on their usability as secondary and primary batteries.A primary battery is one that cannot be recharged. A secondary battery is one that isrechargeable. Secondly, the batteries are classified based on their chemistry. For e.g.: Leadacid, Nickel metal hydride, Li-ion etc. Batteries of same chemistry are further classifiedbased on their application or shape. Based on the application, the main trade-off in batterydevelopment is between power and energy. Batteries can be either high-power or high-energy, but not both. Often manufacturers will classify batteries using these categories.Other common classifications are High Durability, meaning that the chemistry has beenmodified to provide higher battery life at the expense of power and energy. Thirdly, thebatteries are classified based on their shape as prismatic, cylindrical or pouch batteries.

� C- and E- Rates: In describing batteries, discharge current is often expressedas a C-rate in order to normalize against battery capacity, which is often very dif-ferent between batteries. A C-rate is a measure of the rate at which a battery is dis-charged relative to its maximum capacity. A 1C rate means that the discharge currentwill discharge the entire battery in 1 hour. For a battery with a capacity of 100 Ah(Amp-hr), this equates to a discharge current of 100 Amps. A 5C rate for this batterywould be 500 A, and a C/2 rate would be 50 A. Similarly, an E-rate describes thedischarge power. A 1E rate is the discharge power to discharge the entire battery in1 hour.

Battery condition

Variables used to describe the current condition of a battery:

� State of Charge (SOC) (%): An expression of the present battery capacity as apercentage of maximum capacity. SOC is generally calculated using current integrationto determine the change in battery capacity over time.

� Depth of Discharge (DOD) (%): The percentage of battery capacity that hasbeen discharged expressed as a percentage of maximum capacity. A discharge to at least80% DOD is referred to as a deep discharge.

� Terminal Voltage (V): The voltage between the battery terminals with loadapplied. Terminal voltage varies with SOC and discharge/charge current.

� Open-circuit Voltage (V): The voltage between the battery terminals with noload applied. The open-circuit voltage depends on the battery state of charge, increasingwith state of charge.

� Internal Resistance (�): The resistance within the battery, generally differentfor charging and discharging, also dependent on the battery state of charge. As internalresistance increases, the battery efficiency decreases and thermal stability is reduced asmore of the charging energy is converted into heat.

Battery technical specifications

This section explains the specifications you may see on battery technical specificationsheets used to describe battery cells, modules, and packs.

� Nominal Voltage (V): The reported or reference voltage of the battery, alsosometimes thought of as the normal voltage of the battery.

� Cut-off Voltage (V): The minimum allowable voltage. It is this voltage thatgenerally defines the empty state of the battery.

� Capacity or Nominal Capacity (for a specific C-rate) (Ah): The coulomet-ric capacity, the total Amp-hours available when the battery is discharged at a certaindischarge current (specified as a C-rate) from 100 percent state-of-charge to the cut-offvoltage. Capacity is calculated by multiplying the discharge current (in Amps) by thedischarge time (in hours) and decreases with increasing C-rate.

� Energy or Nominal Energy (for a specific C-rate) (Wh): The energy capacityof the battery, the total Watt-hours available when the battery is discharged at a certaindischarge current (specified as a C-rate) from 100 percent state-of-charge to the cut-off voltage. Energy is calculated by multiplying the discharge power (in Watts) by thedischarge time (in hours). Like capacity, energy decreases with increasing C-rate.

� Cycle Life (number for a specific DOD): The number of discharge-charge cyclesthe battery can experience before it fails to meet specific performance criteria. Cycle lifeis estimated for specific charge and discharge conditions. The actual operating life ofthe battery is affected by the rate and depth of cycles and by other conditions such astemperature and humidity. The higher the DOD, the lower the cycle life.

� Specific Energy (Wh/kg): The nominal battery energy per unit mass, sometimesreferred to as the gravimetric energy density. Specific energy is a characteristic of thebattery chemistry and packaging. Along with the energy consumption of the vehicle, itdetermines the battery weight required to achieve a given electric range.

� Specific Power (W/kg): The maximum available power per unit mass. Specificpower is a characteristic of the battery chemistry and packaging. It determines the batteryweight required to achieve a given performance target.

� Energy Density (Wh/L): The nominal battery energy per unit volume, sometimesreferred to as the volumetric energy density. Energy density is a characteristic of the batterychemistry and packaging. Along with the energy consumption of the vehicle, it determinesthe battery size required to achieve a given electric range.

� Power Density (W/L): The maximum available power per unit volume. Powerdensity is a characteristic of the battery chemistry and packaging. It determines the batterysize required to achieve a given performance target.

� Maximum Continuous Discharge Current (A): The maximum current at whichthe battery can be discharged continuously. This limit is usually defined by the batterymanufacturer in order to prevent excessive discharge rates that would damage the batteryor reduce its capacity. Along with the maximum continuous power of the motor, thisdefines the top sustainable speed and acceleration of the vehicle.

� Maximum 30-sec Discharge Pulse Current (A): The maximum current at whichthe battery can be discharged for pulses of up to 30 seconds. This limit is usually defined bythe battery manufacturer in order to prevent excessive discharge rates that would damagethe battery or reduce its capacity. Along with the peak power of the electric motor, thisdefines the acceleration performance (0–60 mph time) of the vehicle.

� Charge Voltage (V): The voltage that the battery is charged to when charged tofull capacity. Charging schemes generally consist of a constant current charging until thebattery voltage reaching the charge voltage, then constant voltage charging, allowing thecharge current to taper until it is very small.

� Float Voltage (V): The voltage at which the battery is maintained after beingcharge to 100 percent SOC to maintain that capacity by compensating for self-dischargeof the battery.

� (Recommended) Charge Current (A): The ideal current at which the battery isinitially charged (to roughly 70% SOC) under constant charging scheme before transi-tioning into constant voltage charging.

� (Maximum) Internal Resistance (�): The resistance within the battery, generallydifferent for charging and discharging.

ACRONYMS

AFM Atomic force microscopyC-rate Charge-discharge rate of the battery. 1C is the current it

takes fully charge or discharge the battery in 1 hourCSAFM Current sensing atomic force microscopeDFT Density functional theoryDOS Density of statesEC Electrochemical capacitorEDLC Electric double layer capacitorEDS Energy dispersive spectroscopyEELS Electron energy loss spectroscopyEES Electrical energy storage devicesEIS Electrochemical impedance spectroscopyELNES Electron loss near edge structureEOL End of lifeEV Electric vehicleEWF Electronic work functionGGA Generalized gradient approximationHEV Hybrid electric vehicle


ICE Internal combustion engineIR InfraredKPM Kelvin probe microscopyMAS Magic angle spinningNDP Neutron depth profilingNMR Nuclear magnetic resonancePAW Projector augmented wavePHEV Plug-in hybrid vehicleRS Raman spectroscopySEM Scanning electron microscopySOC State of chargeSOFC Solid oxide fuel cellSSRM Scanning spreading resistance microscopySTEM Scanning transmission electron microscopyPSD Photosensitive diodeTEM Transmission electron microscopyUSABC United States Advanced Battery ConsortiumUSCAR United States Council for Automotive ResearchVASP Vienna ab-initio simulation packageXRD X-ray diffraction

References

1. Anonymous, “Basic Research Needs For Electrical Energy Storage, Report of theBasic Energy Sciences Workshop for Electrical Energy Storage,” April, Tech Rep.,U. S. Department of Energy, Washington, D.C. (2007).

2. M. S. Whittingham, MRS Bulletin, 33, 411 (2008).3. M. S. Whittingham, “Materials Challenges Facing Electrochemical Energy Storage:

Batteries and Capacitors,” In Fundamentals of Materials for Energy and Environ-mental Sustainability, ( D.S. Ginley and D. Cohen, eds.), Materials Research Society,Warrendale, PA (2011).

4. M. S. Whittingham, Proceedings of the IEEE, 100, 1518 (2012).5. M. Winter and R. J. Brodd, Chem. Rev., 104, 4245 (2004).6. M. Armand and J. M. Tarascon, Nature, 451, 652 (2008).7. J. B. Goodenough, J. Power Sources, 174, 996 (2007).8. Y. M. Chiang, Science, 330, 1485 (2010).9. V. Srinivasan, “Batteries for Vehicular Applications,” In Physics of Sustainable

Energy: Using Energy Efficiently and Producing It Renewably, ( D. Hafemeister,B. Levi, M. Levine, and P. Scliwartz, eds) pp. 283–296, 2008 American Institute ofPhysics, Berkley, CA.

10. D. Howell, Overview of Battery R & D Activities, Tech Rep., U. S. Depart-ment of Energy, Washington, D.C (2012). Available from: http://www1.eere.energy.gov/vehiclesandfuels/.

11. J. Marcicki, “Modeling, Parametrization, and Diagnostic for Lithium-Ion Batterieswith Automotive Application,” The Ohio State University, Columbus, OH, PhDThesis (2012).

12. Anonymous, “FreedomCAR 42 V Energy Storage System End-of-Life PerformanceGoals,” Southfield, MI, USABC, (2002).

13. Anonymous, “USABC Goals for Advanced Batteries for Evs,” Southfield, MI,USABC, (2006).

14. Anonymous, “USABC Requirements of End of Life Energy Storage Systems forPHEVs,” Southfield, MI, USABC, (2006).

15. Anonymous, EV Everywhere: - A Grand Challenge in Plug-In Electric VehiclesGrand challenge, Initial Framing Document, U. S. Dept. of Energy: Washing-ton D. C., (2012). Available from: http://www1.eere.energy.gov/vehiclesandfuels/pdfs/ev_everywhere/ev_everywhere_initial_framing_doc_081512_final_2.pdf.

16. Anonymous, EV Everywhere: - A Grand Challenge, Blueprint, U. S. Dept. ofEnergy: Washington D. C., (2012). Available from: http://www1.eere.energy.gov/vehiclesandfuels/electric_vehicles/pdfs/eveverywhere_blueprint.pdf.

17. C. M. Hayner, X. Zhao, and H. H. Kung, Annu. Rev. Chem. Biomed Eng., 3, 445(2012).

18. M. Winter, J. O. Besenhard, J. H. Albering, J. Y. Yang, and M. Wachtler, Prog.Batteries Battery Mater., 17, 208 (1998).

19. M. Winter, J. O. Besenhard, M. E. Spahr, and P. Novak, Adv. Mater., 10, 725 (1998).20. M. S. Whittingham, Chem. Rev., 104, 4271 (2004).21. H.-K. Song, K. T. Lee, M. G. Kim, L. F. Nazar, and J. Cho, Adv. Funct. Mater., 20,

3818 (2010).22. K. Pinkwart and J. Tubke, “Thermodynamics and Mechanistics,” In Handbook of

Battery Materials, 2nd Ed., ( C. Daniel and J. O. Besenhard, eds.) pp. 3–26, Wiley,Weinheim, Germany (2011).

23. F. Kong, R. Kostecki, G. Nadeau, X. Song, K. Zaghib, K. Kinoshita, andF. McLarnon, J. Power Sources, 97–98, 58 (2001).

24. P. G. Bruce, B. Scrosati, and J.-M. Tarascon, Angew. Chem. Int., 47, 2930 (2008).25. S. Hossain, Y.-K. Kim, Y. Saleh, and R. Loutfy, J. Power Sources, 114, 264 (2003).26. M. S. Whittingham, Science, 192, 1126 (1976).27. Q. Fan, P. J. Chupas, and M. S. Whittingham, Electrochem. Solid St., 10, A274

(2007).28. E. Peled, J. Electrochem. Soc., 126, 2047 (1979).

29. R. Kanno, Y. Kawamoto, Y. Takeda, S. Ohashi, N. Imanishi, and O. Yamamoto, JElectrochem. Soc., 139, 3397 (1992).

30. J. Vetter, P. Novak, M. R. Wagner, C. Veit, K. C. Moller, J. O. Besenhard, M. Winter,M. Wohlfahrt-Mehrens, C. Vogler, and A. Hammouche, J. Power Sources, 147, 269(2005).

31. E. Ferg, R. J. Gummow, A. de Kock, and M. M. Thackeray, J. Electrochem. Soc.,141, L147 (1994).

32. R. Kostecki and F. McLarnon, Electrochem. Solid St., 5, A164 (2002).33. R. Kostecki and F. McLarnon, Electrochem Solid tate Lett., 7, A380 (2004).34. C. Johnson, N. Li, J. Vaughey, S. Hackney, and M. Thackeray, Electrochem. Com-

mun., 7, 528 (2005).35. S.-H. Park, S.-H. Kang, and C. Johnson, Electrochem. Commun., 9, 262 (2007).36. J. Whitacre, K. Zaghib, W. West, and B. Ratnakumar, J. Power Sources, 177, 528

(2008).37. M. Dubarry, C. Truchot, M. Cugnet, B. Liaw, K. Gering, S. Sazhin, D Jamison, and

C. Michelbacher, J. Power Sources, 196, 10328 (2011).38. M. Dubarry, C. Truchot, M. Cugnet, B. Liaw, K. Gering, S. Sazhin, D Jamison, and

C. Michelbacher, J. Power Sources, 196, 10336 (2011).39. K. Nam, W. Yoon, H. Shin, K. Chung, S. Choi, and X. Yang, J. Power Sources, 192,

652 (2009).40. J. Belt, V. Utgikar, and I. Bloom, J. Power Sources, 196, 10213 (2011).41. S. Jeong, J. Shin, K. Nahm, T. Prem Kumar, and A. M. Stephan, Mater Chem. Phys.,

111, 213 (1999).42. C. Yang, H. Lai, Z. Liu, and P. Ma, J. Chem. Eng. Data, 51, 1345 (2006).43. A. K. Padhi, K. S. Nanjundaswamy, and J. B. Goodenough, J. Electrochem. Soc.,

144, 1188 (1997).44. A. K. Padhi, K. S. Nanjundaswamy, C. Masquelier, S. Okada, and

J. B. Goodenough, J. Electrochem. Soc., 144, 1609 (1997).45. A. Yamada, S. C. Chung, and K. Hinokuma, J. Electrochem. Soc., 148, A224 (2001).46. L.-X. Yuan, Z.-H. Wang, W.-X. Zhang, X,-L. Hu, J.-T. Chen, Y.-H. Huang, and

J. B. Goodenough, Energy Environ. Sci., 4, 269 (2011).47. P. Arora and Z. Zhang, Chem. Rev., 104, 4419 (2004).48. S. Zhang, J. Power Sources, 164, 351 (2007).49. K. Xu, Chem. Rev., 104, 4303 (2004).50. J. Y. Song, Y. Y. Wang, and C. C. Wan, J. Power Sources, 77, 183 (1999).51. S. C. Nagpure and B. Bhushan, “Nanomaterials for Electrical Energy Storage De-

vices,” In Encyclopedia of Nanotechnology, ( B. Bhushan, ed.) pp. 1597–1608,Springer, Heidelberg, Germany (2012).

52. I. Buchmann, Batteries in a Portable World: A Handbook on Rechargeable Batteriesfor Non-Engineer, second ed., Cadex Electronics Inc., Richmond, VA (2001).

53. J. S. Newman, Electrochemical Systems, second ed., Prentice-Hall, EnglewoodCliffs, NJ (1991).

54. J. Newman and K. E. Thomas-Alyea, Electrochemical Systems, 3rd Ed., Wiley,Hoboken, NJ (2004).

55. J. R. Dahn, Phys. Rev. B, 44, 9170 (1991).56. V. R. Albertini, P. Perfetti, F. Ronci, P. Reale, and B. Scrosati, Appl. Phys. Lett., 79,

27 (2001).57. R. Kostecki and F. McLarnon, J. Power Sources, 119–121, 550 (2003).58. S. Miao, M. Kocher, P. Rez, B. Fultz, R. Yazami, and C. C. Ahn, J. Phys. Chem. A,

111, 4242 (2007).59. J. B. Siegel, X. Lin, A. G. Stefanopoulou, D. S. Hussey, D. L. Jacobson, and

D. Gorsich, J. Electrochem. Soc., 158, A523 (2011).60. A. Senyshyna, M. J. Muhlbauera, K. Nikolowskia, T. Pirling, and H. Ehrenberg, J.

Power Sources, 203, 126 (2012).61. R. S. Rubino, H. Gan, and E. S. Takeuchi, J. Electrochem. Soc., 148, A1029 (2001).62. P. Spagnol, S. Onori, N. Madella, Y. Guezennec, and J. Neal, “Aging and Charac-

terization of Li-Ion Batteries in a HEV Application for Lifetime Estimation,” Proc.of IFAC Symposium Advances in Automotive Control (2010).

63. V. Marano, S. Onori, Y. Guezennec, G. Rizzoni, and N. Madella, “Lithium-ionBatteries Life Estimation for Plug-in Hybrid Electric Vehicles,” In Proceedings ofthe Vehicle Power and Propulsion Conference, IEEE, 536–543 (2009).

64. S. C. Nagpure, B. Bhushan, S. S. Babu, and G. Rizzoni, Scripta Mater., 60, 933(2009).

65. S. C. Nagpure, R. Dinwiddie, S. S. Babu, G. Rizzoni, B. Bhushan, and T. Frech, J.Power Sources, 195, 872 (2010).

66. S. C. Nagpure, S. S. Babu, and B. Bhushan, J. Power Sources, 196, 1508 (2011).67. S. C. Nagpure, R. G. Downing, B. Bhushan, S. S. Babu, and L. Cao, Electrochim.

Acta, 56, 4735 (2011).68. S. C. Nagpure, S. S. Babu, B. Bhushan, A. Kumar, R. Mishra, W. Windl, L. Kovarik,

and M. Mills, Acta Mater., 59, 6917 (2011).69. S. C. Nagpure, B. Bhushan, and S. S. Babu, Appl. Surf. Sci., 259, 49 (2012).70. S. Franger, F. Le. Cras, C. Bourbon, C. Benoit, P. Soudan, and J. Santos-Pena,

“Overview on the practical electrochemical behaviour of optimized lithium ironphosphate,” In Recent Research Developments in Electrochemistry, Vol. 8, (S. G. Pandalai, ed.) pp. 225–256, Transworld Research Network, Kerala, India(2005).

71. C. Benoit and S. Franger, J. Solid State Electr., 12, 987 (2008).72. J. Wang, P. Liu, J. Hicks-Garner, E. Sherman, S. Soukiazian, M. Verbrugge,

H. Tataria, J. Musser, and P. Finamorec, J. Power Sources, 196, 3942 (2011).73. M. Safari and C. Delacourt, J. Electrochem. Soc., 158, A562 (2011).74. M. Safari and C. Delacourt, J. Electrochem. Soc., 158, A1436 (2011).75. P. Arora, R. E. White, and M. Doyle, J. Electrochem. Soc., 145, 3647 (1998).76. M. Safari, M. Morcrette, A. Teyssot, and C. Delacourt, J. Electrochem. Soc., 156,

A145 (2009).77. D. Goers, M. Spahr, A. Leone, W. Markle, and P. Novak, Electrochim. Acta, 56,

3799 (2011).

http://dx.doi.org/10.1557/mrs2008.82

http://dx.doi.org/10.1109/JPROC.2012.2190170

http://dx.doi.org/10.1021/cr020730k

http://dx.doi.org/10.1038/451652a

http://dx.doi.org/10.1016/j.jpowsour.2007.06.217

http://dx.doi.org/10.1126/science.1198591

http://www1.eere.energy.gov/vehiclesandfuels/

http://www1.eere.energy.gov/vehiclesandfuels/

http://www1.eere.energy.gov/vehiclesandfuels/pdfs/ev_everywhere/ev_everywhere_initial_framing_doc_081512_final_2.pdf

http://www1.eere.energy.gov/vehiclesandfuels/pdfs/ev_everywhere/ev_everywhere_initial_framing_doc_081512_final_2.pdf

http://www1.eere.energy.gov/vehiclesandfuels/electric_vehicles/pdfs/eveverywhere_blueprint.pdf

http://www1.eere.energy.gov/vehiclesandfuels/electric_vehicles/pdfs/eveverywhere_blueprint.pdf

http://dx.doi.org/10.1146/annurev-chembioeng-062011-081024

http://dx.doi.org/10.1002/(SICI)1521-4095(199807)10:10<725::AID-ADMA725>3.0.CO;2-Z

http://dx.doi.org/10.1021/cr020731c

http://dx.doi.org/10.1002/adfm.201000231

http://dx.doi.org/10.1016/S0378-7753(01)00588-2

http://dx.doi.org/10.1002/anie.200702505

http://dx.doi.org/10.1016/S0378-7753(02)00588-8

http://dx.doi.org/10.1126/science.192.4244.1126

http://dx.doi.org/10.1149/1.2789418

http://dx.doi.org/10.1149/1.2128859

http://dx.doi.org/10.1149/1.2069090

http://dx.doi.org/10.1149/1.2069090


http://dx.doi.org/10.1149/1.2059324

http://dx.doi.org/10.1149/1.1482199

http://dx.doi.org/10.1149/1.1793771

http://dx.doi.org/10.1016/j.elecom.2005.02.027








http://dx.doi.org/10.1016/j.matchemphys.2008.03.032

http://dx.doi.org/10.1021/je0600808

http://dx.doi.org/10.1149/1.1837571

http://dx.doi.org/10.1149/1.1837649

http://dx.doi.org/10.1149/1.1348257

http://dx.doi.org/10.1039/c0ee00029a

http://dx.doi.org/10.1021/cr020738u


http://dx.doi.org/10.1021/cr030203g

http://dx.doi.org/10.1016/S0378-7753(98)00193-1

http://dx.doi.org/10.1103/PhysRevB.44.9170

http://dx.doi.org/10.1063/1.1383058

http://dx.doi.org/10.1016/S0378-7753(03)00287-8

http://dx.doi.org/10.1021/jp068605q

http://dx.doi.org/10.1149/1.3566341



http://dx.doi.org/10.1149/1.1390344

http://dx.doi.org/10.1016/j.scriptamat.2009.01.033




http://dx.doi.org/10.1016/j.electacta.2011.02.037


http://dx.doi.org/10.1016/j.actamat.2011.07.043

http://dx.doi.org/10.1016/j.apsusc.2012.06.080

http://dx.doi.org/10.1007/s10008-007-0443-9


http://dx.doi.org/10.1149/1.3567007


http://dx.doi.org/10.1149/1.1838857

http://dx.doi.org/10.1149/1.3043429



78. W. Markle, C. Lu, and P. Novak, Electrochimica Acta, 56, 3799 (2011).79. D. Bedrov, G. Smith, and A. Van Duin, J. Phys. Chem. A, 116, 2978 (2012).80. G. Ning, R. White, and B. Popov, Electrochimica Acta, 51, 2012 (2006).81. S. Santhanagopalan, Q. Guo, P. Ramadass, and R. E. White, J. Power Sources, 156,

620 (2006).82. M. Broussely, S. Herreyre, P. Biensan, P. Kasztejna, K. Nechev, and R. Staniewicz,

J. Power Sources, 97, 13 (2001).83. S. J. Harris, A. Timmons, D. R. Baker, and C. Monroe, Chem. Phys. Lett., 485, 265

(2010).84. B. V. Ratnakumar and M. C. Smart, ECS Trans., 25(36), 241 (2010).85. W. Fang, O. Kwon, and C. Wang, Int. J. Energ. Res., 34, 107 (2010).86. T. Ohzuku, A. Ueda, N. Yamamoto, and Y. Iwakoshi, J. Power Sources, 54, 99

(1995).87. H. P. Lin, D. Chua, M. Salomon, H. C. Shiao, M. Hendrickson, E. Plichta, and

S. Slane, Electrochem. Solid State Lett., 4, A71 (2001).88. B. V. Ratnakumar, M. C. Smart, and S. Surampudi, J. Power Sources, 97–98, 137

(2001).89. J. Christensen and J. Newman, J. Solid State Electrochem., 10, 293 (2006).90. X. Zhang, W. Shyy, and A. Sastry, J. Electrochem. Soc., 154, A910 (2007).91. M. Verbrugge and Y. Cheng, ECS Trans, 16, 155 (2008).92. Y. Cheng and M. Verbrugge, Electrochem. Solid State Lett., 13, A128 (2010).93. Y. Cheng and M. Verbrugge, J. Electrochem. Soc., 157, A508 (2010).94. S. Renganathan, G. Sikha, S. Santhanagopalan, and R. White, J. Electrochem. Soc.,

157, A155 (2010).95. K. Zhao, M. Pharr, J. Vlassak, and Z. Suo, J. Appl. Phys., 108, 073517 (2010).96. R. Deshpande, Y. Cheng, M. Verbrugge, and A. Timmons, J. Electrochem. Soc.,

158, A718 (2011).97. D. Aurbach, M. D. Levi, K. Gamulski, B. Markovsky, G. Salitra, E. Levi, U. Heider,

L. Heider, and R. Oesten, J. Power Sources, 82, 472 (1999).98. J. Cho, G. B. Kim, H. S. Lim, C. S. Kim, and S. I. Yoo, Electrochem. Solid State

Lett., 2, 607 (1999).99. A. Du Pasquier, A. Blyr, P. Courjal, D. Larcher, G. Amatucci, B. Gerand, and

J.-M. Tarascon, J. Electrochem. Soc., 146, 428 (1999).100. H. Huang, C. Vincent, and P. Bruce, J. Electrochem. Soc., 146, 3649 (1999).101. E. Iwata, K. Takahashi, K. Maeda, and T. Mouri, J. Power Sources, 81–82, 430

(1999).102. T. Aoshima, K. Okahara, C. Kiyohara, and K. Shizuka, J. Power Sources, 97–98,

377 (2001).103. B. S. Haran, A. Durairajan, P. Ramadass, R. E. White, and B. N. Popov, “Studies

on Capacity Fade of Spinel based Li-Ion Batteries,” In Proceedings of the 36thIntersociety Energy Conversion Engineering Conference of IECEC 935-940, July29–August 2, 2001, Savannah, Georgia (2001).

104. S. Komaba, N. Kumagai, T. Sasaki, and Y. Miki, Electrochemistry, 69, 784(2001).

105. H. Oka, S. Kasahara, T. Okada, E. Iwata, M. Okada, T. Shoji, H. Ohki, and T. Okuda,Solid State Ionics, 144, 19 (2001).

106. H. Yamane, T. Inoue, M. Fujita, and M. Sano, J. Power Sources, 99, 60 (2001).107. N. Iltchey, Y. Chen, S. Okada, and J. Yamaki, J. Power Sources, 119–121, 749

(2003).108. H. Sclar, D. Kovacheva, and D. Zhecheva, J. Electrochem. Soc., 156, A938 (2009).109. A. Du Pasquier, A. Blyr, A. Cressent, C. Lenain, G. Amatucci, and J. M. Tarascon,

J. Power Sources, 81–82, 54 (1999).110. Y. Liu, X. Li, H. Guo, Z. Wang, Q. Hu, W. Peng, and Y. Yang, J. Power Sources,

189, 721 (2009).111. J. Park, J. Seo, G. Plett, W. Lu, and A. Sastry, J. Electrochem. Soc., 14, A14 (2011).112. L. Cai, Y. Dai, M. Nicholson, R. White, K. Jagannathan, and G. Bhatia, J. Power

Sources, 221, 191 (2013).113. W. J. Parker, R. J. Jenkins, C. P. Butler, and G. L. Abbott, J. Appl. Phys., 32, 1679

(1961).114. K. B. Larson and K. Koyama, J. Appl. Phys., 39, 4408 (1968).115. L. Vozar and W. Hohenauer, High Temp-High Press., 35/36, 253 (2003).116. M. Lafond-Huot and J. Bransier, Lett. Heat Mass Trans., 9, 49 (1982).117. A. M. Luc and D. L. Balageas, High Temp-High Press., 16, 209 (1984).118. I. Philippi, J.-C. Batsale, D. Maillet, and A. Degiovanni, Rev. Sci. Instrum., 66, 182

(1995).119. A. Degiovanni, J.-C. Batsale, and D. Maillet, Revue generale de Thermique, 35, 141

(1996).120. J.-C. Krapez, “Mesure de diffusivit longitudinale de plaques minces par mthode de

grille,” In Proceedings of Journe SFT Thermographie IR quantitative, ON-ERA,(1999).

121. J.-C. Batsale, C. Gobbe, and M. Quintard, Recent Res. Devel. Heat, Mass MomentumTransfer, 1, (1996).

122. L. Ramond, J.-C. Batsale, C. Gobbe, and M. Quintard, “Measurement of a ThermalExchange Coefficient in Porous Media by Infrared Thermography -Two TemperatureModel Application,” In Proceedings of 11th Int. Heat Transfer Conference, KyongJu Korea (1998).

123. L. Ramond, J.-C. Batsale, and C. Gobbe, Int. J. Thermal Sci., 38, 250 (1999).124. C. Moyne, J.-C. Batsale, and A. Degiovanni, Int. J. Heat Mass Tran., 31, 2305

(1988).125. C. Moyne, J.-C. Batsale, A. Degiovanni, and D. Maillet, “Thermal Conductivity

of Wet Porous Media: Theoretical Analysis and Experimental Measurements,” InProceedings of Thermal Conductivity 21 ( C. J. Cremers and H. A. Fine, eds.),pp. 109–120, Plenum Press, Lexington, KY (1990).

126. S. Azizi, J.-C. Batsale, C. Moyne, and A. Degiovanni, High Temp-High Press., 21,383 (1989).

127. S. Andre and A. Degiovanni, Int. J. Heat Mass Tran., 38, 3401 (1995).128. O. Hahn, F. Raether, M. C. Arduini-Schuster, and J. Fricke, Int. J. Heat Mass Tran.,

40, 689 (1997).129. M. Lazard, S. Andre, and D. Maillet, Int. J. Heat Mass Tran., 47, 477 (2004).130. R. Coquard and B. Panel, Int. J. Thermal Sci., 48, 747 (2009).131. F. Righini and A. Cezairliyan, High Temp-High Press., 5, 481 (1973).132. A. Degiovanni, Rev. Gen. Therm., 185, 417 (1977).133. R. E. Taylor, High Temp-High Press., 11, 43 (1979).134. D. Balageas, High Temp-High Press., 21, 85 (1989).135. R. E. Taylor and K. D. Maglic, “Pulse Method for Thermal Diffusivity Measure-

ment,” In Compendium of Thermophysical Property Mea- surement Methods:Survey of Measurement Techniques, Vol. 1, ( K. D. Maglic, A. Cezairliyan, andV. E. Peletsky, eds.) pp. 305–336, Plenum, New York (1984).

136. K. D. Maglic and R. E. Taylor, “The apparatus for thermal diffusivity measurementby the laser pulse method,” In Compendium of Thermophysical Property Mea-surement Methods: Recommend Measurement Techniques and Practices, Vol. 2, (K. D. Maglic, A. Cezairliyan, and V. E. Peletsky, eds.), pp. 281–314, Plenum, NewYork (1992).

137. M. Sheindlin, D. Halton, M. Musella, and C. Ronchi, Rev. Sci. Instru., 69, 1426(1998).

138. T. Baba and A. Ono, Meas. Sci. Technol., 12, 2046 (2001).139. L. Vozar and W. Hohenauer, High Temp-High Press., 33, 9 (2001).140. Anonymous, ASTM Designation: E, 1461–92, 933 (1992).141. H. E. Exner and E. Arzt, In Physical Metallurgy, ( R. W. Cahn and P. Haasen, eds.)

third ed., Elsevier Science Publication (1983).142. A. I. Brown and S. M. Marco, Introduction to Heat Transfer, third ed., McGraw-Hill,

New York (1958).143. E. R. Eckert and R. M. Drake, Heat and Mass Transfer, McGraw-Hill, New York

(1959).144. J. P. Holman, Heat Transfer, ninth ed., McGraw-Hill, New York (2002).145. W. J. Zhang and D. E. Miser, J. Nanopart. Res., 8, 1027 (2006).146. V. I. Kononenko, V. M. Baranovskii, and V. P. Dushchenko, Powder Metall. Met. C,

7, 175 (1968).147. A. Bhattacharya, V. V. Calmidi, and R. L. Mahajan, Intl. J. Heat Mass Tran., 45,

1017 (2002).148. J. Marcicki, G. Rizzoni, A. T. Conlisk, and M. Canova, “A Reduced-Order Elec- tro-

chemical Model of Lithium-Ion Cells for System Identification of Battery Aging,”In Proceedings of the 4th Annual Dynamic Systems and Control Conference, “Mod-eling and Estimation for Automotive & Energy Systems,” Arlington, VA (2011).

149. P. Maire, A. Evans, H. Kaiser, W. Scheifele, and P. Novak, J. Electrochem. Soc.,155, A862 (2008).

150. Y. Qi and S. J. Harris, J. Electrochem. Soc., 157, A741 (2010).151. P. Shearing, L. E. Howard, P. S. Jørgensen, N. P. Brandon, and S. J. Harris, Elec-

trochem Comm., 12, 374 (2010).152. S. Channagiri, S. C. Nagpure, S. S. Babu, G. J. Noble, and R. T. Hart, J. Power

Sources, 243, 750 (2013).153. D. P. Abraham, D. W. Dees, J. Knuth, E. Reynolds, R. Gerald, and Y.-E. Hyung et al.,

“Diagnostic Examination of Generation 2 Lithium-Ion Cells and Assessment ofPerformance Degradation Mechanisms,” ( D. P. Abraham, ed.) Oak Ridge NationalLaboratory, TN. Report # ANL-05/21 (2006).

154. G. Binnig, C. F. Quate, and C. Gerber, Phys. Rev. Lett., 56, 930 (1986).155. B. Bhushan, Nanotribology and Nanomechanics I - Measurement Techniques and

Nanomechanics, II - Nanotribology, Biomimetics, and Industrial Applications, thirded., Springer, Heidelberg, Germany (2011).

156. S. C. Nagpure and B. Bhushan, “Atomic Force Microscopy Studies of Aging Mech-anisms in Lithium-Ion Batteries,” In Applied Scanning Probe Methods Biomimeticsand Industrial Applications, Vol. 13, ( B. Bhushan and H. Fuchs, eds.) pp. 203–233,Springer, Heidelberg, Germany (2009).

157. S. Ramdon and B. Bhushan, J. Colloid Interface Sci., 380, 187 (2012).158. D. B. Williams and C. B. Carter, Transmission Electron Microscopy: A Textbook for

Materials Science, Vol. 1, first ed., Plenum, New York (2004).159. G. Chen, X. Song, and T. J. Richardson, Electrochem. Solid. St., 9, A295 (2006).160. L. Laffont, C. Delacourt, P. Gibot, M. Y. Wu, P. Kooyman, C. Masquelier, and

J. M. Tarascon, Chem. Mater., 18, 5520 (2006).161. C. Delmas, M. Maccario, L. Croguennec, F. Le Cras, and F. Weill, Nat. Mater., 7,

666 (2008).162. L. A. Giannuzzi, J. L. Drown, S. R. Brown, R. B. Irwin, and F. A. Stevie, “Focused

Ion Beam Milling and Micromanipulation Lift-out for Site Specific Cross-SectionTEM Specimen Preparation,” In Materials Research Society Symposium Proceed-ings 480 ( R. M. Anderson and S. D. Walck, eds.), pp. 19–27, Materials ResearchSociety, Pittsburgh, PA (1997).

163. L. A. Giannuzzi and F. A. Stevie, Micron, 30, 197 (1999).164. A. Brazier, L. Dupont, L. DantrasLaffont, N. Kuwata, J. Kawamura, and

J. M. Tarascon, Chem. Mater., 20, 2352 (2008).165. J. Y. Huang, L. Zhong, C. M. Wang, J. P. Sullivan, W. Xu, L. Q. Zhang, S. X. Mao,

N. S. Hudak, X. H. Liu, A. Subramanian, H. Y. Fan, L. A. Qi, A. Kushima, andJ. Li, Science, 330, 1515 (2010).

166. C. M. Wang, W. Xu, J. Liu, D. W. Choi, B. Arey, L. V. Saraf, J. G. Zhang, Z. G. Yang,S. Thevuthasan, D. R. Baer, and N. Salmon, J. Mater. Res., 25, 1541 (2010).

167. C. M. Wang, W. Xu, J. Liu, J. G. Zhang, L. V. Saraf, B. W. Arey, D. Choi, Z. G. Yang,J. Xiao, S. Thevuthasan, and D. R. Baer, Nano Letters, 11, 1874 (2011).

168. K. Yamamoto, Y. Iriyama, T. Asaka, T. Hirayama, H. Fujita, C. A. J. Fisher,K. Nonaka, Y. Sugita, and Z. Ogumi, Angewandte Chem.-Int’l. Ed., 49, 4414 (2010).

169. B. Bhushan, Springer Handbook of Nanotechnology, third ed., Springer, Heidelberg,Germany (2010).


http://dx.doi.org/10.1021/jp210345b



http://dx.doi.org/10.1016/S0378-7753(01)00722-4

http://dx.doi.org/10.1016/j.cplett.2009.12.033

http://dx.doi.org/10.1149/1.3393860

http://dx.doi.org/10.1002/er.1652

http://dx.doi.org/10.1016/0378-7753(94)02047-7

http://dx.doi.org/10.1149/1.1368736

http://dx.doi.org/10.1016/S0378-7753(01)00682-6

http://dx.doi.org/10.1007/s10008-006-0095-1

http://dx.doi.org/10.1149/1.2759840

http://dx.doi.org/10.1149/1.2987765

http://dx.doi.org/10.1149/1.3455179

http://dx.doi.org/10.1149/1.3298892

http://dx.doi.org/10.1149/1.3261809

http://dx.doi.org/10.1063/1.3492617

http://dx.doi.org/10.1149/1.3565183

http://dx.doi.org/10.1016/S0378-7753(99)00204-9

http://dx.doi.org/10.1149/1.1390922

http://dx.doi.org/10.1149/1.1390922

http://dx.doi.org/10.1149/1.1391625

http://dx.doi.org/10.1149/1.1392528

http://dx.doi.org/10.1016/S0378-7753(99)00227-X

http://dx.doi.org/10.1016/S0378-7753(01)00551-1

http://dx.doi.org/10.1016/S0167-2738(01)00899-2

http://dx.doi.org/10.1016/S0378-7753(01)00479-7

http://dx.doi.org/10.1016/S0378-7753(03)00215-5

http://dx.doi.org/10.1149/1.3212850

http://dx.doi.org/10.1016/S0378-7753(99)00136-6


http://dx.doi.org/10.1149/1.3516619



http://dx.doi.org/10.1063/1.1728417

http://dx.doi.org/10.1063/1.1656985

http://dx.doi.org/10.1068/htjr119

http://dx.doi.org/10.1016/0094-4548(82)90047-9

http://dx.doi.org/10.1063/1.1146432

http://dx.doi.org/10.1016/S0035-3159(96)80010-9

http://dx.doi.org/10.1016/S1290-0729(99)80088-X

http://dx.doi.org/10.1016/0017-9310(88)90163-9

http://dx.doi.org/10.1016/0017-9310(95)00075-K

http://dx.doi.org/10.1016/0017-9310(96)00137-8

http://dx.doi.org/10.1016/j.ijheatmasstransfer.2003.07.003

http://dx.doi.org/10.1016/j.ijthermalsci.2008.06.005

http://dx.doi.org/10.1063/1.1148776

http://dx.doi.org/10.1088/0957-0233/12/12/304

http://dx.doi.org/10.1068/htwu154

http://dx.doi.org/10.1520/E1461-11

http://dx.doi.org/10.1007/s11051-005-9056-3

http://dx.doi.org/10.1007/BF00774147

http://dx.doi.org/10.1016/S0017-9310(01)00220-4

http://dx.doi.org/10.1149/1.2979696

http://dx.doi.org/10.1149/1.3377130





http://dx.doi.org/10.1103/PhysRevLett.56.930

http://dx.doi.org/10.1016/j.jcis.2012.05.026

http://dx.doi.org/10.1149/1.2192695

http://dx.doi.org/10.1021/cm0617182

http://dx.doi.org/10.1038/nmat2230

http://dx.doi.org/10.1016/S0968-4328(99)00005-0

http://dx.doi.org/10.1021/cm7033933

http://dx.doi.org/10.1126/science.1195628

http://dx.doi.org/10.1557/JMR.2010.0198

http://dx.doi.org/10.1021/nl200272n

http://dx.doi.org/10.1002/anie.200907319


170. K. Slater, “Scanning Spreading Resistance Microscopy (SSRM),” In Support NoteNo. 294 Rev. A, Veeco Instruments Inc., Santa Barbara, CA (2000).

171. Anonymous, “Application Modules Training Supplement,” Veeco Instruments Inc.,Santa Barbara, CA (2004).

172. X. Zhang, P. N. Ross, Jr., R. Kostecki, F. Kong, S. Sloop, J. B. Kerr, K. Striebel,E. J. Cairns, and F. McLarnon, J. Electrochem. Soc., 148, A463 (2001).

173. D. DeVecchio and B. Bhushan, Rev. Sci Intsrum., 60, 3618 (1998).174. A. L. Zharin and D. A. Rigney, Tribol. Lett., 4, 205 (1998).175. A. Rice, “Nanoscope Controller Manual,” Rev. B, Veeco Instruments Inc., Santa

Barbara, CA (2002).176. B. Bhushan and A. Goldade, Appl. Surf. Sci., 157, 373 (2000).177. H. A. Sturges, J. Amer. Statist. Assoc., 21, 65 (1926).178. J. S. Bendat and A. G. Piersol, Engineering Applications of Correlation and Spectral

Analysis, second ed. (Wiley, New York, 1986).179. A. S. Andersson and J. O. Thomas, J. Power Sources, 97–98, 498 (2001).180. N.-H. Cho, K. M. Krishnan, D. K. Veirs, M. D. Rubin, C. B. Hopper, and

B. Bhushan, J. Mater. Res., 5, 2543 (1990).181. M. A. Tamor and W. C. Vassell, J. Appl. Phys., 76, 3823 (1994).182. J. Schwan, S. Ulrich, V. Bathori, H. Erhardt, and S. R. P. Silva, J. Appl. Phys., 80,

440 (1996).183. B. Bhushan, Diam. Relat. Mater., 8, 1985 (1999).184. A. C. Ferrari and J. Robertson, Phys. Rev. B, 61, 14095 (2000).185. R. Saito, T. Takeya, and T. Kimura, Phy. Rev. B, 57, 4145 (1998).186. M. M. Doeff, Y. Hu, F. McLarnon, and R. Kostecki, Electrochem. Solid St., 6, A207

(2003).187. Y. Cho, G. H. Fey, and H. Kao, J. Power Sources, 189, 256 (2009).188. C. M. Julien, K. Zaghib, A. Mauger, M. Massot, A. Ait-Salah, M. Selmane, and

F. Gendron, J. Appl. Phys., 100, 063511 (2006).189. J. D. Wilcox, M. M. Doeff, M. Marcinek, and R. Kostecki, J. Electrochem. Soc.,

154, A389 (2007).190. M. Maccario, L. Croguennec, B. Desbat, M. Couzi, F. Le Cras, and L. Servant, J.

Electrochem. Soc., 155, A879 (2008).191. M. V. Klein, “Raman studies of phonon anomalies in transition-metal compounds,”

In Light Scattering in Solids III, Topics in Applied Physics, Vol. 51, ( M. Cardonaand G. Guntherodt, eds.) pp. 121–171, Springer, Berlin (1982).

192. R. Vidano and D. B. Fischbach, J. Am. Ceram. Soc., 61, 13 (1978).193. F. Tuinstra and J. L. Koenig, J. Chem. Phys., 53, 1126 (1970).194. M. J. Matthews, M. A. Pimenta, G. Dreesselhaus, M. S. Dreesselhaus, and M. Endo,

Phys. Rev. B, 59, R6585 (1999).195. Z. G. Li, R. L. Harlow, F. Gao, P. Lin, R. Miao, and L. Liang, J. Electrochem. Soc.,

150, A1171 (2003).196. A. S. Andersson, B. Kalska, L. Haggstrom, and J. O. Thomas, Solid State Ionics,

130, 41 (2000).197. D. B. Williams and C. B. Carter, Transmission Electron Microscopy: A Textbook for

Materials Science, Vol. 4, first ed., Plenum, New York (2004).198. P. Tang and N. A. W. Holzwarth, Phys. Rev. B, 68, 165107-165107-10 (2003).199. M. S. Islam, D. J. Driscoll, C. A. J. Fisher, and P. R. Slater, Chem. Mater., 17, 5085

(2005).200. T. Hahn, (ed), International Tables for Crystallography, Volume A: Space-Group

Symmetry, fifth ed., Kluwer, Dordrecht (2002).201. G. Kresse and J. Furthmuller, Comp. Mater. Sci., 6, 15 (1996).202. G. Kresse and J. Furthmuller, Phys. Rev. B, 54, 11169 (1996).203. J. P. Perdew, J. A. Chevary, S. H. Vosko, K. A. Jackson, M. R. Pederson, D. J. Singh,

and C. Fiolhais, Phys. Rev. B, 46, 6671 (1992).204. V. I. Anisimov, J. Zaanen, and O. K. Andersen, Phys. Rev. B, 44, 943 (1991).205. G. Duscher, R. Buckzo, S. J. Pennycook, and S. T. Pantelides, Ultramicroscopy, 86,

355 (2001).206. W. Windl, T. Liang, S. Lopatin, and G. Duscher, Mater. Sci. Eng. B, 114–115, 156

(2004).207. H. J. Monkhorst and J. D. Pack, Phys. Rev. B, 13, 5188 (1976).208. M. K. Kinyanjui, P. Axmann, M. Wohfahrt-Mehrens, P. Moreau, F. Boucher, and

U. Kaiser, J. Phys-Condens. Mat., 22, 275501 (2010).209. C. Delacourt and M. Safari, J. Electrochem. Soc., 159, A1283 (2012).210. P. Liu, J. Wang, J. Hicks-Garner, E. Sherman, S. Soukiazian, M. Verbrugge,

H. Tataria, J. Musser, and P. Finamore, J. Electrochem. Soc., 157, A499 (2010).211. D. Goers, M. Holzapfel, W. Scheifele, E. Lehmann, P. Vontobel, and P. Novak, J.

Power Sources, 130, 221 (2004).212. C. P. Grey and Y. J. Lee, Solid State Sci., 5, 883 (2003).213. M. C. Tucker, M. M. Doeff, T. J. Richardson, R. Finones, J. A. Reimer, and

E. J. Cairnsa, Electrochem. Solid St., 5, A95 (2002).214. C. P. Grey and N. Dupre, Chem. Rev., 104, 4493 (2004).215. J. R. Dahn, U. von Sacken, and C. A. Michal, Solid State Ionics, 44, 87

(1990).216. C. Marichal, J. Hirschinger, P. Granger, M. Menetrier, A. Rougier, and C. Delmas,

Inorg. Chem., 34, 1773 (1995).217. S. Levasseur, M. Menetrier, E. Suard, and C. Delmas, Solid State Ionics, 128, 11

(2000).218. D. Carlier, M. Menetrier, and C. Delmas, J. Mater. Chem., 11, 594 (2001).219. D. Carlier, I. Saadoune, L. Croguennec, M. Menetrier, E. Suard, and C. Delmas,

Solid State Ionics, 144, 263 (2001).220. K. R. Morgan, S. Collier, G. Burns, and K. Ooi, J. Chem. Soc., Chem. Commun.,

1719 (1994).221. B. Gee, C. R. Horne, E. J. Cairns, and J. A. Reimer, J. Phys. Chem. B, 102, 10142

(1998).222. Y. J. Lee, F. Wang, and C. P. Grey, J. Am. Chem. Soc., 120, 12601 (1998).

223. Y. J. Lee, F. Wang, S. Mukerjee, J. McBreen, and C. P. Grey, J. Electrochem. Soc.,147, 803 (2000).

224. Y. J. Lee and C. P. Grey, Chem. Mater., 12, 3871 (2000).225. M. C. Tucker, J. A. Reimer, and E. J. Cairns, Electrochem. Solid St., 3, 463 (2000).226. V. W. J. Verhoeven, I. M. de Schepper, G. Nachtegaal, A. P. M. Kentgens,

E. M. Kelder, J. Schoonman, and F. M. Mulder, Phys. Rev. Lett., 86, 4314 (2001).227. J. Gaubicher, C. Wurm, G. Goward, C. Masquelier, and L. Nazar, Chem. Mater.,

12, 3240 (2000).228. M. C. Tucker, M. M. Doeff, T. J. Richardson, R. Finones, E. J. Cairns, and

J. A. Reimer, J. Am. Chem. Soc., 124, 3832 (2002).229. M. Arrabito, S. Bodoardo, N. Penazzi, S. Panero, P. Reale, B. Scrosati, Y. Wang,

X. Guo, and S. G. Greenbaum, J. Power Sources, 97–98, 478 (2001).230. R. E. Gerald, J. Sanchez, C. S. Johnson, R. J. Klinger, and J. W. Rathke, J. Phys.

Condens. Mater., 13, 8269 (2001).231. F. Chevallier, M. Letellier, M. Morcrette, J.-M. Tarascon, E. Frackowiak,

J.-N. Rouzaud, and F. Beguin, Electrochem. Solid St., 6, A225 (2003).232. J. F. Ziegler, G. W. Cole, and J. E. E. Baglin, J. Appl. Phys., 43, 3809 (1972).233. R. G. Downing, R. F. Fleming, J. K. Langland, and D. H. Vincent, Nuel. Inst. Meth-

ods, 218, 47 (1983).234. R. G. Downing, G. P. Lamaze, J. K. Langland, and S. T. Hwang, J. Res. Natl. Inst.

Stand. Technol., 98, 109 (1993).235. J. P. Biersack and D. Fink, “Implantation of Boron, and Lithium in Semiconductors,

and Metals,” In Ion Implantation in Semiconductors, ( S. Namba, ed.) pp. 211–218,Plenum Press, New York (1975).

236. L. H. M. Krings, Y. Tamminga, J. van Berkumc, F. Labohm, A. van Veen, andW. M. Arnoldbik, J. Vac. Sci. Technol. A, 17, 198 (1999).

237. G. P. Lamaze, H. H. Chen-Mayer, D. A. Becker, F. Vereda, R. B. Goldner, T. Haas,and P. Zerigian, J. Power Sources, 119–121, 680 (2003).

238. S. Whitney, S. R. F. Biegalski, Y. H. Huang, and J. B. Goodenough, J. Electrochem.Soc., 156, A886 (2009).

239. J. F. Ziegler, J. P. Biersack, and M. D. Ziegler, SRIM - The Stopping and Range ofIons in Matter, Lulu Press Co., Morrisville, NC (2008).

240. D. M. Gilliam, G. P. Lamaze, M. S. Dewey, and G. L. Greene, Nucl. Instrum. Meth-ods Phys. Res. Sect. A-Accel. Spectrom. Dect. Assoc. Equip., 334, 149 (1993).

241. K. Edstrom, M. Herstedt, and D. Abraham, J. Power Sources, 153, 380 (2006).242. T. Yoshida, M. Takahashi, S. Morikaa, C. Ihara, H. Katsukaa, T. Shiratsuchi, and

J. Yamaki, J. Electrochem. Soc., 153, A576 (2006).243. E. Peled, D. Golodnistsky, C. Menachem, and D. Bar-Tow, J. Electochem. Soc.,

145, 3482 (1998).244. J. Li, E. Murphy, J. Winnick, and P. Kohl, J. Power Sources, 102, 302 (2001).245. S. S. Zhang, K. Xu, and T. R. Jow, Electrochim. Acta, 49, 1057 (2004).246. P. Verma, P. Marie, and P. Novak, Electrochim. Acta, 55, 6332 (2010).247. J. F. M. Oudenhoven, F. Labohm, M. Mulder, R. A. H. Niessen, F. M. Mulder, and

P. H. L. Notten, Adv. Mater., 23, 4103 (2011).248. S. C. Nagpure, R. G. Downing, B. Bhushan, and S. S. Babu, Scripta Mater, 67, 669

(2012).249. A. Van de Walle, Z. Moser, and W. Gasior, Arch. Metall. Mater., 49, 535 (2004).250. W. Gasior, B. Onderka, Z. Moser, A. Debski, and T. Gancarz, CALPHAD, 33, 215

(2009).251. Z. Xiong, S. Shi, C. Ouyang, M. Lei, L. Hu, Y. Ji, Z. Wang, and L. Chen, Phys. Lett

A, 337, 247 (2005).252. J. Suzuki, M. Yoshida, C. Nakahara, K. Sekine, M. Kikuchi, and T. Takamura,

Electrochem. Solid St., 4, A1 (2001).253. R. M. Rose, J. Wulff, and L. A. Shepard, Structure and Properties of Materials, Vol.

4: Electronic Properties, Wiley, New York (1966).254. B. Y. Liaw, G. Nagasubramanian, R. G. Jungst, and D. H. Doughty, Solid State

Ionics, 175, 835 (2004).255. M. Casacca and Z. Salameh, IEEE Trans. Energy Convers., 11, 139 (1996).256. M. Durr, A. Cruden, S. Gair, and J. R. McDonald, J Power Sources, 161, 1400

(2006).257. M. Casacca and Z. Salameh, IEEE Trans. Energy Convers., 7, 442 (1992).258. Z. Salameh and M. Casacca, IEEE Trans. Energy Convers., 7, 93 (1992).259. J. Appelbaum and R. Weiss, “An Electrical Model of the Lead-Acid Bat-

tery,” Telecommunications Energy Conference, INTELEC International, 304–307(1982).

260. H. L. Chan and D. Sutanto, IEEE Power Engineering Society Winter Meeting Con-ference, 1, 470 (2000).

261. V. Ramadesigan, P. W. C. Northrop, S. De, S. Santhanagopalan, R. D. Braatz, andV. R. Subramaniana, J. Electrochem. Soc., 159, R31 (2012).

262. P. P. Mukherjee, S. Pannala, and J. A. Turner, “Modeling and Simulation of Bat-tery Systems,” In Handbook of Battery Materials, 2nd Ed., ( C. Daniel andJ. O. Besenhard, eds.) pp. 843–871, Wiley, Weinheim, Germnay (2011).

263. J. Newman, K. E. Thomas, H. Hafezi, and D. R. Wheeler, J. Power Sources, 119–121, 838 (2003).

264. J. Newman and W. Tiedemann, Am. Inst. Chem. Eng. J., 21, 25 (1975).265. K. E. Thomas, R. M. Darling, and J. Newman, “Modeling of lithium batteries,” In

Advances in Lithium-Ion Batteries, Kluwer Academic Publishers, New York (2002).266. J. Newman and C. W. Tobias, J. Electrochem. Soc., 109, 1183 (1962).267. T. F. Fuller, M. Doyle, and J. Newman, J. Electrochem. Soc., 141, 1 (1994).268. T. F. Fuller, M. Doyle, and J. Newman, J. Electrochem. Soc., 141, 982 (1994).269. M. Doyle and J. Newman, J. Power Sources, 54, 46 (1995).270. M. Doyle and J. Newman, J. Appl. Electrochem., 27, 846 (1997).271. P. Ramadass, B. Haran, P. M. Gomadam, R. E. White, and B. N. Popov, J. Elec-

trochem. Soc., 151, A196 (2004).272. P. K. Adanuvor and R. E. White, J. Electrochem. Soc., 135, 1888 (1988).

http://dx.doi.org/10.1149/1.1362541

http://dx.doi.org/10.1063/1.1149148

http://dx.doi.org/10.1023/A:1019171625552

http://dx.doi.org/10.1016/S0169-4332(99)00553-X

http://dx.doi.org/10.1080/01621459.1926.10502161

http://dx.doi.org/10.1016/S0378-7753(01)00633-4

http://dx.doi.org/10.1557/JMR.1990.2543

http://dx.doi.org/10.1063/1.357385

http://dx.doi.org/10.1063/1.362745

http://dx.doi.org/10.1016/S0925-9635(99)00158-2



http://dx.doi.org/10.1149/1.1601372


http://dx.doi.org/10.1063/1.2337556

http://dx.doi.org/10.1149/1.2667591

http://dx.doi.org/10.1149/1.2977961

http://dx.doi.org/10.1149/1.2977961

http://dx.doi.org/10.1111/j.1151-2916.1978.tb09219.x

http://dx.doi.org/10.1063/1.1674108

http://dx.doi.org/10.1103/PhysRevB.59.R6585

http://dx.doi.org/10.1149/1.1593653

http://dx.doi.org/10.1016/S0167-2738(00)00311-8


http://dx.doi.org/10.1021/cm050999v

http://dx.doi.org/10.1016/0927-0256(96)00008-0




http://dx.doi.org/10.1016/S0304-3991(00)00126-1

http://dx.doi.org/10.1016/j.mseb.2004.07.041


http://dx.doi.org/10.1088/0953-8984/22/27/275501


http://dx.doi.org/10.1149/1.3294790



http://dx.doi.org/10.1016/S1293-2558(03)00113-4

http://dx.doi.org/10.1149/1.1464505

http://dx.doi.org/10.1021/cr020734p

http://dx.doi.org/10.1016/0167-2738(90)90049-W

http://dx.doi.org/10.1021/ic00111a026

http://dx.doi.org/10.1016/S0167-2738(99)00335-5

http://dx.doi.org/10.1039/b006179o

http://dx.doi.org/10.1016/S0167-2738(01)00982-1

http://dx.doi.org/10.1039/c39940001719

http://dx.doi.org/10.1021/jp982301p

http://dx.doi.org/10.1021/ja9817794

http://dx.doi.org/10.1149/1.1393276

http://dx.doi.org/10.1021/cm000469t

http://dx.doi.org/10.1149/1.1391180

http://dx.doi.org/10.1103/PhysRevLett.86.4314

http://dx.doi.org/10.1021/cm000345g

http://dx.doi.org/10.1021/ja017838m

http://dx.doi.org/10.1016/S0378-7753(01)00632-2

http://dx.doi.org/10.1088/0953-8984/13/36/304

http://dx.doi.org/10.1088/0953-8984/13/36/304

http://dx.doi.org/10.1149/1.1612011

http://dx.doi.org/10.1063/1.1661816

http://dx.doi.org/10.1016/0167-5087(83)90953-5

http://dx.doi.org/10.1016/0167-5087(83)90953-5

http://dx.doi.org/10.6028/jres.098.008

http://dx.doi.org/10.6028/jres.098.008

http://dx.doi.org/10.1116/1.581573

http://dx.doi.org/10.1016/S0378-7753(03)00232-5

http://dx.doi.org/10.1149/1.3216033

http://dx.doi.org/10.1149/1.3216033

http://dx.doi.org/10.1016/0168-9002(93)90543-Q

http://dx.doi.org/10.1016/0168-9002(93)90543-Q


http://dx.doi.org/10.1149/1.2162467

http://dx.doi.org/10.1149/1.1838831

http://dx.doi.org/10.1016/S0378-7753(01)00820-5



http://dx.doi.org/10.1002/adma.201101819

http://dx.doi.org/10.1016/j.scriptamat.2012.07.009

http://dx.doi.org/10.1016/j.calphad.2008.10.006

http://dx.doi.org/10.1016/j.physleta.2005.01.041

http://dx.doi.org/10.1016/j.physleta.2005.01.041

http://dx.doi.org/10.1149/1.1344170

http://dx.doi.org/10.1016/j.ssi.2004.09.049

http://dx.doi.org/10.1016/j.ssi.2004.09.049

http://dx.doi.org/10.1109/60.486588


http://dx.doi.org/10.1109/60.148564

http://dx.doi.org/10.1109/60.124547

http://dx.doi.org/10.1109/PESW.2000.850009

http://dx.doi.org/10.1109/PESW.2000.850009


http://dx.doi.org/10.1016/S0378-7753(03)00282-9

http://dx.doi.org/10.1002/aic.690210103

http://dx.doi.org/10.1149/1.2425269

http://dx.doi.org/10.1149/1.2054684

http://dx.doi.org/10.1149/1.2054868

http://dx.doi.org/10.1016/0378-7753(94)02038-5

http://dx.doi.org/10.1023/A:1018481030499

http://dx.doi.org/10.1149/1.1634273

http://dx.doi.org/10.1149/1.1634273

http://dx.doi.org/10.1149/1.2096174


273. M. W. Verbrugge, J. Electrochem. Soc., 139, 3529 (1992).274. M. W. Verbrugge and B. J. Koch, J. Electrochem. Soc., 143, 600 (1996).275. B. S. Haran, B. N. Popov, and R. E. White, J. Power Sources, 75, 56 (1998).276. G. Ning and B. N. Popov, J. Electrochem. Soc., 151, A1584 (2004).277. R. Darling and J. Newman, J. Electrochem. Soc., 145, 990 (1998).278. G. Sikha, B. N. Popov, and R. E. White, J. Electrochem. Soc., 151, A1104 (2004).279. T. I. Evans, T. V. Nguyen, and R. E. White, J. Electrochem. Soc., 136, 328 (1989).280. M. Tang, H.-Y. Huang, H. Meethong, Y.-H. Kao, W. C. Carter, and Y.-M. Chiang,

Chem. Mater., 21, 1557 (2009).

281. M. Doyle, T. F. Fuller, and J. Newman, J. Electrochem. Soc., 140, 1526 (1993).282. F. A. Mantia, “Characterization of Electrodes for Lithium-Ion Batteries through

Electrochemical Impedance Spectroscopy and Mass Spectrometry,” PhD Thesis(2008).

283. T. Ohzuku, A. Ueda, and N. Yamamoto, J. Electrochem. Soc., 142, 1431 (1995).284. Anonymous, “Overview of lithium-ion batteries,” Panasonic Corp., Secaucus, NJ,

(2007).285. Z. Tun, J. J. Noel, Th. Bohdanowicz, L. R. Cao, R. G. Downing, and

L. V. Goncharova, Can. J. Phys., 88, 751 (2010).

http://dx.doi.org/10.1149/1.2069110

http://dx.doi.org/10.1149/1.1836486

http://dx.doi.org/10.1016/S0378-7753(98)00092-5

http://dx.doi.org/10.1149/1.1787631

http://dx.doi.org/10.1149/1.1838376

http://dx.doi.org/10.1149/1.1759972

http://dx.doi.org/10.1149/1.2096630

http://dx.doi.org/10.1021/cm803172s

http://dx.doi.org/10.1149/1.2221597

http://dx.doi.org/10.1149/1.2048592

http://dx.doi.org/10.1139/P10-062

multi-scale characterization studies of aged li-ion large ... · the performance of these batteries...

Documents