nano materials 2004

8/3/2019 Nano Materials 2004

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NanomaterialsBoxuan Gu and David McQuilling


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What are they? Nano = 10-9 or one billionth in size

Materials with dimensions and tolerances in

the range of 100 nm to 0.1 nm Metals, ceramics, polymeric materials, or

composite materials

One nanometer spans 3-5 atoms lined up in a

row Human hair is five orders of magnitude larger

than nanomaterials


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Nanomaterial Composition Comprised of many different elements

such as carbons and metals

Combinations of elements can make upnanomaterial grains such as titaniumcarbide and zinc sulfide

Allows construction of new materialssuch as C60 (Bucky Balls or fullerenes)and nanotubes


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How they are made Clay/polymer nanocomposites can be made

by subjecting clay to ion exchange and then

mixing it with polymer melts Fullerenes can be made by vaporizing carbon

within a gas medium

Current carbon fullerenes are in the gaseousphase although samples of solid state

fullerenes have been found in nature


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Bucky Ball properties Arranged in pentagons and hexagons A one atom thick seperation of two spaces; inside

the ball and outside Highest tensile strength of any known 2D structure or

element, including cross-section of diamonds whichhave the highest tensile strength of all known 3Dstructures (which is also a formation of carbonatoms)

Also has the highest packing density of all knownstructures (including diamonds) Impenetrable to all elements under normal

circumstances, even a helium atom with an energy of5eV (electron Volt)


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Bucky Ball properties cont. Even though each carbon atom is only bonded with

three other carbons (they are mosthappy with fourbonds) in a fullerene, dangling a single carbon atom

next to the structure will not affect the structure, i.e.the bond made with the dangling carbon is notstrong enough to break the structure of the fullerene

No other elementhas such wonderful properties ascarbon which allows costs to be relatively cheap;after all its just carbon and carbon is everywhere


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Buckminsterfullerene uses Due to their extremely resilient and sturdy nature bucky

balls are debated for use in combat armor Bucky balls have been shown to be impervious to lasers,

allowing for defenses from future warfare Bucky balls have also been shown to be useful at fighting

the HIV virus that leads to AIDS Researchers Kenyan and Wudl found that water soluble

derivates of C60 inhibit the HIV-1 protease, the enzymeresponsible for the development of the virus

Elements can be bonded with the bucky ball to createmore diverse materials including superconductors andinsulators

Can be used to fashion nanotubes


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Bucky Ball (C60) C240 colliding with C60 at

300 eV (Kinetic energy)

Bucky Balls

http://www.pa.msu.edu/cmp/csc/simindex.html


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Nanotube properties Superior stiffness and strength to all other materials Extraordinary electric properties Reported to be thermally stable in a vacuum up to

2800 degrees Centigrade (and we fret over CPUtemps over 50o C)

Capacity to carry an electric current 1000 timesbetter than copper wires

Twice the thermal conductivity of diamonds Pressing or stretching nanotubes can change their

electrical properties by changing the quantum statesof the electrons in the carbon bonds

They are either conducting or semi-conductingdepending on the their structure


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Nanotube uses Can be used for containers to hold various

materials on the nano-scale level

Due to their exceptional electrical properties,nanotubes have a potential for use ineveryday electronics such as televisions andcomputers to more complex uses likeaerospace materials and circuits


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Nanotubes

Switching nanotube-based memoryCarbon based nanotubes

http://www.pa.msu.edu/cmp/csc/simindex.html


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Applications of

Nanotechnology Next-generation computer chips

Ultra-high purity materials, enhanced thermalconductivity and longer lasting nanocrystalline

materials Kinetic Energy penetrators (DoD weapon)

Nanocrystalline tungsten heavy alloy to replaceradioactive depleted uranium

Better insulation materials Create foam-like structures called aerogels from

nanocrystalline materials Porous and extremely lightweight, can hold up to

100 times their weight


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More applications Improved HDTV and LCD monitors

Nanocrystalline selenide, zinc sulfide, cadmiumsulfide, and lead telluride to replace current

phosphors Cheaper and more durable

Harder and more durable cutting materials Tungsten carbide, tantalum carbide, and titanium

carbide Much more wear-resistant and corrosion-resistant

than conventional materials Reduces time needed to manufacture parts,

cheaper manufacturing


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Even more applications High power magnets

Nanocrystalline yttrium-samarium-cobalt grainspossess unusually large surface area compared to

traditional magnet materials Allows for muchhigher magnetization values Possibility for quieter submarines, ultra-sensitive

analyzing devices, magnetic resonance imaging(MRI) or automobile alternators to name a few

Pollution clean up materials Engineered to be chemically reactive to carbon

monoxide and nitrous oxide More efficient pollution controls and cleanup


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Still more applications Greater fuel efficiency for cars

Improved spark plug materials, railplug Stronger bio-based plastics

Bio-based plastics made from plant oils lacksufficient structural strength to be useful

Merge nanomaterials such as clays, fibers andtubes with bio-based plastics to enhance strengthand durability

Allows for stronger, more environment friendlymaterials to construct cars, space shuttles and amyriad of other products


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Applications wrapup Higher quality medical implants

Current micro-scale implants arent porous enough for tissueto penetrate and adapt to

Nano-scale materials not only enhance durability andstrength of implants but also allow tissue cells to adapt morereadily

Home pregnancy tests Current tests such as First Response use gold nanoparticles

in conjunction with micro-meter sized latex particles

Derived with antibodies to the human chorionicgonadotrophin hormone that is released by pregnant women The antibodies react with the hormone in urine and clump

together and show up pink due to the nanoparticlesplamson resonance absortion qualities


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Modeling and Simulation ofNanostructured Materials and

Systems


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Preface Each distinct age in the development of

humankind has been associated with

advances in materials technology.

Historians have linked key technological and

societal events with the materials technology

that was prevalent during the stone age,bronze age, and so forth.


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Significant events In materials 1665 - Robert Hooke material microstructure

1808 - John Dalton atomic theory

1824 - Portland cement 1839 - Vulcanization

1856 - Large-scale steel production

1869 - Mendeleev and Meyer Periodic Tableof the Chemical Elements

1886 - Aluminum

1900 - Max Planck . quantum mechanics


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Cont. 1909 - Bakelite

1921 - A. A. Griffith . fracture strength

1928 - Staudinger polymers (small moleculesthat link to form chains)

1955 - Synthetic diamond

1970 - Optical fibers

1985 - First university initiatives attemptcomputational materials design

1985 - Bucky balls (C60) discovered at RiceUniversity

1991 - Carbon nanotubes discovered by Sumio


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Why we need Computational

Materials?Traditionally, research institutions have relied on a

discipline-oriented approach to material

development and design with new materials.

It is recognized, however, that within the scope of

materials and structures research, the breadth of

length and time scales may range more than 12

orders of

magnitude, and different scientific and engineering

disciplines are involved at each level.


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To help address this wide-ranging

interdisciplinary research, Computational

Materials has been formulated with the specificgoal of exploiting the tremendous physical and

mechanical properties of new nano-materials b

understanding materials at atomic, molecular,and supramolecular levels.


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Computational Materials at LaRC draws

from physics and chemistry, but focuses

on constitutive descriptions of materials

that are useful in formulating

macroscopic models of material

performance.


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Benefit of Computational

materials First, it encourages a reduced reliance on costly

trial and error, or serendipity, of the Edisonian

approach to materials research. Second, it increases the confidence that new

materials will possess the desired properties whenscaled up from the laboratory level, so that lead-

time for the introduction of new technologies isreduced.

Third, the Computational Materials approachlowers the likelihood of conservative orcompromised designs that might have resultedfrom reliance on less-than-perfect materials.


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Schematic illustration of relationships between time

and length scales for the multi-scale simulation

methodology.


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Cont.

The starting point is a quantum

description of materials; this is carried

forward to an atomistic scale for initial

model development.

Models at this scale are based on

molecular mechanics or moleculardynamics.


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Cont. At the next scale, the models can incorporate

micro-scale features and simplified

constitutive relationships.

Further progress up, the scale leads to the

meso or in-between levels that rely on

combinations of micromechanics andwellestablished theories such as elasticity.


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Cont. The last step towards engineering-level

performance is to move from mechanics of

materials to structural mechanics by using

methods that rely on empirical

data,constitutive models, and fundamental

mechanics.


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Nanostructured Materials The origins of focused research into

nanostructured materials can be traced back to a

seminal lecture given by Richard Feynman in1959[1].

In this lecture, he proposed an approach to the

problem of manipulating and controlling things on a

small scale. The scale he referred to was not themicroscopic scale that was familiar to scientists of

the day but the unexplored atomistic scale.


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The nanostructured materials based on

carbon nanotubes and related carbon

structures are of current interest for much ofthe materials community.

More broadly then, nanotechnology presents

the vision of working at the molecular level,atom by atom, to create large structures with

fundamentally new molecular organization.


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Simluation methods


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Atomistic, Molecular

Methods The approach taken by the Computational

Materials is formulation of a set of integrated

predictive models that bridge the time andlength scales associated with material

behavior from the nano through the meso

scale.


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At the atomistic or molecular level, the reliance is

on molecular mechanics,

molecular dynamics, and coarse-grained, Monte-Carlo simulation.

Molecular models encompassing thousands and

perhaps millions of atoms can be solved by these

methods and used to predict fundamental,

molecular level material behavior. The methods

are both static and dynamic.


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Molecular dynamics simulations generate

information at the nano-level, including

atomic positions and velocities.

The conversion of this information to

macroscopic observables such as pressure,

energy, heat capacities, etc., requiresstatistical mechanics.


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An experiment is usually made on a macroscopic

sample that contains an extremely large number

of atoms or molecules, representing anenormous number of conformations.

In statistical mechanics, averages corresponding

to experimental measurements are defined in

terms of ensemble averages.


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For example

!

!M

i

iVMV

1

*/1

where Mis the number of configurations in the molecular

dynamics trajectory and Viis the potential energy of each

configuration.


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j

M

j

N

i

ii

ivv

m

M

K ! !

!1 1 2

1

where Mis the number of configurations in the simulation, Nis

the number of atoms in the system, miis the mass of the

particle iand viis the velocity of particle i.

To ensure a proper average, a molecular dynamics simulation

must account for a large number of representative

conformations.


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By using Newtons second law to calculate atrajectory, one only needs the initial positions of

the atoms, an initial distribution of velocities andthe acceleration, which is determined by thegradient of the potential energy function.

The equations of motion are deterministic; i.e.,the positions and the velocities at time zerodetermine the positions and velocities at all othertimes, t. In some systems, the initial positionscan be obtained from experimentally determinedstructures.


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In a molecular dynamics simulation, the timedependent behavior of the molecular system is

obtained by integrating Newtons equations ofmotion.

The result of the simulation is a time series ofconformations or the path followed by each atom.

Most molecular dynamics simulations areperformed under conditions of constant number ofatoms, volume, and energy (N,V,E) or constantnumber of atoms, temperature, and pressure(N,T,P) to better simulate experimental conditions.


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Basic steps in the MD

simulation

1. Establish initial coordinates.

2. Minimize the structure.

3. Assign initial velocities.

4. Establish heating dynamics.

5. Perform equilibration dynamics.

6. Rescale the velocities and check if thetemperature is correct.

7. Perform dynamic analysis of trajectories.


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Monte Carlo Simulation Although molecular dynamics methods

provide the kind of detail necessary to

resolve molecular structure and localizedinteractions, this fidelity comes with a price.

Namely, both the size and time scales of the

model are limited by numerical andcomputational boundaries.


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To help overcome these limitations,coarse-

grained methods are available that represent

molecular chains as simpler, bead-spring models. Coarse-grain models are often linked to Monte

Carlo (MC) simulations to provide a timely

solution.

The MC method is used to simulate stochastic

events and provide statistical approaches to

numerical Integration.


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There are three characteristic steps in the MCsimulation that are given as follows.

1. Translate the physical problem into ananalogous probabilistic or statistical model.

2. Solve the probabilistic model by a numerical

sampling experiment.3. Analyze the resultant data by usingstatistical methods.


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Continum Methods Despite the importance of understanding the

molecular structure and nature of materials,

at some level in the multi-scale analysis thebehaviour of collections of molecules and

atoms can be homogenized.


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At this level, the continuum level, the observed

macroscopic behaviour is explained by

disregarding thediscrete atomistic and molecular structure and

assuming that the material is continuously

distributed throughout its volume.

The continuum material is assumed to have an

average density and can be subjected to body

forces such as gravity and surface forces such as

the contact between two bodies.


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The continuum can be assumed to obey severalfundamental laws.

The first, continuity, is derived from theconservation of mass.

The second, equilibrium, is derived frommomentum considerations and Newtons second

law. The third, the moment of momentum principle, is

based on the model that the time rate of changeof angular momentum with respect to an arbitrarypoint is equal to the resultant moment.


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These laws provide the basis for the continuum

model and must be coupled with the appropriate

constitutive equations and equations of state toprovide all the equations necessary for solving a

continuum problem.

The state of the continuum system is described by

several thermodynamic and kinematic statevariables.

The equations of state provide the relationships

between the non-independent state variables.


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The continuum method relates the

deformation of a continuous medium to the

external forces acting on the medium and theresulting internal stress and strain.

Computational approaches range from

simple closed-form analytical expressions tomicromechanics to complex structural

mechanics calculations basedon beam and

shell theory.


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The continuum-mechanics methods rely on

describing the geometry, (I.e.physical

model), and must have a constitutiverelationship to achieve a solution.

For a displacement based form of

continuum solution, the principle of virtualwork is assumed valid.


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In general, this is given as:

jjj

S

jj

V

j

V

ijij

uFdSuTdVuP

dVW

HHH

HIWH

!

!


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where Wis the virtual work which is the work done by

imaginary or virtual displacements, is the strain, is the

stress, Pis the body force, u is the virtual displacement, T

is the tractions and Fis the point forces. The symbol is thevariational operator designating the virtual quantity.

For a continuum system, a necessary and sufficient

condition for equilibrium is that the virtual work done by

sum of the external forces and internal forces vanish forany virtual displacement.


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Software for Nanomaterials

SS


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BOSS-Biochemical and OrganicSimulation System

The B O S S program performs (a)Monte Carlo (MC) statistical mechanics

simulations for solutes in a periodicsolvent box, in a solvent cluster, or in adielectric continuum including the gas

phase, and (b) standard energyminimizations, normal mode analysis,and conformational searching.


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XMakemol

XMakemol is a mouse-based program,written using the LessTifwidget set, for

viewing and manipulating atomic andother chemical systems. It reads XYZinput and renders atoms, bonds and

hydrogen bonds.


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Features Animating multiple frame files

Interactive measurement of bond lengths,

bond angles and torsion angles Control over atom/bond sizes

Exporting to XPM, Encapsulated PostScriptand Fig formats

Toggling the visibility of groups of atoms

Editing the positions of subsets of atoms


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A watermolecule withvectors alongthe principalaxes


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As above,

withlightingturned off


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Candidate

structure for theH2O(20) globalminimum


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Buckminster

Fullerene


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Amsterdam Density Functional

(ADF) package The Amsterdam Density Functional (ADF)

package is software for first-principles

electronic structure calculations. ADF isused by academic and industrialresearchers worldwide in such diverse fields

as pharmacochemistry and materialsscience


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It is currently particularly popular in theresearch areas of:

homogeneous and heterogeneous catalysis

inorganic chemistry

heavy element chemistry

various types of spectroscopy

biochemistry


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ARP/wARP

ARP/wARP is a package for automated protein

model building and structure refinement. It isbased on a unified approach to the structuresolution process by combining electron densityinterpretation using the concept of the hybrid

model, pattern recognition in an electron densitymap and maximum likelihood model parameterrefinement.


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The ARP/wARP suite is under continuousdevelopment. The present release, Version 6.0,

can be used in the following ways:1. Automatic tracing of the density map and model

building. This includes the refinement of MRsolutions and the improvement of MAD and

M(S)IR(AS) phases via map interpretation2. Free atoms density modification

3. Building of the solvent structure


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Chemsuite - A suite designed for

chemistry on LinuxChemsuite is composed by several program:

Chem2D: A 2D molecular drawer.

Molcalc: A molecular weight calculator ChemModel3D: Molecular 3D modeler

ChemIR: An infrared spectra processor.

It can read, process, export and print Perkin

Elmerspectra. ChemNMR: 1D NMR Processor

ChemMC: Monte carlo Simulator and Integrator


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General Atomic and Molecular

Electronic Structure System (GAMESS) GAMESS is a program for ab initio quantum

chemistry. Briefly, GAMESS can compute

SCF wavefunctions ranging from RHF,ROHF, UHF, GVB, and MCSCF. Correlationcorrections to these SCF wavefunctionsinclude Configuration Interaction, second

order perturbation theory, and Coupled-Cluster approaches, as well as the DensityFunctional Theory approximation.


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Useful sitehttp://www.linuxlinks.com/Software/Scien

tific/Chemistry/

nano materials 2004

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