the technology vision 2020 nanoscale science and engineering · modellazione di mesoscala (insiemi...
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Multiscale modelling of nanostructured materials
Maurizio Fermeglia
MoSE - University of Trieste
WWW. MOSE.UNITS.IT
Trieste, 20 A pril, 2010 - slide 3 Maurizio Fermeglia – MO SE - UNITS
The technology vision 2020
Trieste, 20 A pril, 2010 - slide 4 Maurizio Fermeglia – MO SE - UNITS
Nanoscale science and engineering
Ability to work at molecular level, atom by atom, to create large structures with fundamentally new properties and functions* At least one dimension is of the order of nanometers
Functionality is critically dependent on nanoscale size
Promise of unprecedented understanding and control over basic building blocks and properties of natural and man-made objects*
Theory, modeling and simulation (TMS) Expected to play key role in nanoscale science and technology
McCurdy, C. W., Stechel, E., Cummings, P. T., Hendrickson, B., and Keyes, D.,
"Theory and Modeling in Nanoscience: Report of the May 10-11, 2002, Workshop
Conducted by the Basic Energy Sciences and Advanced Scientific Computing
Advisory Committees of the Office of Science, Department of Energy
Published by DOE
Also available on the web at
http://www.sc.doe.gov/bes/Theory_and_Modeling_in_Nanoscience.pdf
*M. Roco, FY 2002 National Nanotechnology
Investment Budget Request
Trieste, 20 A pril, 2010 - slide 5 Maurizio Fermeglia – MO SE - UNITS
Meccanica Quantistica (elettroni)
Meccanica molecolare (atomi)
Modellazione di
mesoscala (insiemi di atomi o molecole)
Simulazione di processo
FEM
Engineering design
1Å
Characteristic Length
1nm 1μm 1mm 1m
hears
seconds
nanoseconds
picoseconds
femtoseconds
Quantum Mechanics (electrons)
Molecular Mechanics (atoms)
Mesoscale modeling
(segments)
Process Simulation
FEM
Engineering design
1Å
Characteristic Time
1nm 1μm 1mm 1m
hours
minutes
microseconds
Multiscale Molecular Modeling
Trieste, 20 A pril, 2010 - slide 6 Maurizio Fermeglia – MO SE - UNITS
Hierarchy of Scales
Polymer morphology;
blend phase
separation; composite
structure
Molecular structure; free energies
of formation, reaction; dipole
moments and other spectroscopic
properties; reaction rates
Critical constants; phase
equilibria; PVT data;
diffusivity, viscosity
2
Trieste, 20 A pril, 2010 - slide 7 Maurizio Fermeglia – MO SE - UNITS
Hierarchy of Scales:
nanocomposites
Polymer morphology;
blend phase separation
Information for
building the force field
Information for building
the mesoscopic model;
effect of surface modifier
and its determination
Nanocomposite
mechanical and other
properties
Trieste, 20 A pril, 2010 - slide 9 Maurizio Fermeglia – MO SE - UNITS
Molecular Simulation vs Theory
Advances in computational hardware and algorithms
Moore‟s law
Gordon Bell Prize: 1Gflop/s in 1988 vs. 27 Tflop/s in 2002
More than four order of magnitude increase in 14 years
Add 2-3 orders of magnitude from parallelizat ion (cheap today)
Costs driven by consumer market
Trieste, 20 A pril, 2010 - slide 10 Maurizio Fermeglia – MO SE - UNITS
Number of transistors on a
sliver of silicon would double
every two years
Moore‟s law
Trieste, 20 A pril, 2010 - slide 11 Maurizio Fermeglia – MO SE - UNITS
Molecular Simulation vs Theory
Advances in computational hardware and algorithms
Moore‟s law
Gordon Bell Prize: 1Gflop/s in 1988 vs. 27 Tflop/s in 2002
More than four order of magnitude increase in 14 years
Add 2-3 orders of magnitude from parallelizat ion (cheap today)
Costs driven by consumer market
Costs for experiment? Labor-intensive, high capital costs
Costs for theory?
Labor-intensive 2
Do graduate students and/or lab personnel/equipment improve
by an order of magnitude every five years?
Trieste, 20 A pril, 2010 - slide 12 Maurizio Fermeglia – MO SE - UNITS
Moore‟s law and Molecular modeling
Trieste, 20 A pril, 2010 - slide 13 Maurizio Fermeglia – MO SE - UNITS
Algorithms vs Hardware
Monte Carlo algorithms to simulate Ising model
David Landau, U. of Georgia
•1970 •1975 •1980 •1985 •1990 •1995 •2000 •1
•10
•100
•1000
•10000
•100000
•1000000
•1E7
•1E8
•1E9
•1E10
•relative performance
•computer speed
3
Trieste, 20 A pril, 2010 - slide 14 Maurizio Fermeglia – MO SE - UNITS
Molecular Modeling: traditional approaches
Computational quantum chemistry
Solve Schrödinger equation numerically
Computationally intensive even for small molecules
In principle, yields exact electronic structure and energy as limiting case of increasingly accurate methods (HF, MP2, MP4,…)
Density functional theory (DFT) is approximate but fast
Atomistic simulation
Molecular dynamics Solve dynamical equations of motion for positions, velocities of atoms
Monte Carlo Generate configurations of equilibrium system stochastically according
to know distribution
Both require intermolecular and intermolecular potentials (force fields) as input
Trieste, 20 A pril, 2010 - slide 15 Maurizio Fermeglia – MO SE - UNITS
Theory Modeling and Simulation advances over past 15 years
Molecular dynamics on as many as billions of atoms
Car-Parrinello and related methods for ab initio dynamics Reactions, complex interfaces,…
Revolution in Monte Carlo methods (Gibbs ensemble, continuum configurational bias, tempering, connectivity alterig, etc) Extraordinarily fast equilibrat ion of systems with long relaxation times
New generation Force Fields transferable force fields: TraPPE
Quantum Monte Carlo methods for nearly exact descriptions of the electronic structures of molecules
New mesoscale methods (including dissipative particle dynamics and field-theoretic polymer simulation) Applicable to systems with long relaxation times and large spatial scales
Finite elements simulations: Gusev at ETH (MatSim)
Hybrid methods (Fraajie)
Trieste, 20 A pril, 2010 - slide 16 Maurizio Fermeglia – MO SE - UNITS
Molecular Modeling: innovative approaches
Mesoscale simulation
Dissipative Particle Dynamics – Mesoscopic Particle based model Solve dynamical equations of motion for positions, velocities of beads in the Langevin
dynamics
Mesoscale Dynamics (MesoDyn) - Mesoscopic Field based model Dynamic mean-field density functional theory coupled with Langevin equation of
motion
Both require the definition of beads and bead interaction energies
Flow and continuum mechanics models
Solve PDA and continuum models including hydrodynamic description and phenomena occurring at macroscopic level Finite elements simulation
Starting from a grid definition
To be applied for nano-materials a detailed description of the properties at mesoscale level is needed
Trieste, 20 A pril, 2010 - slide 17 Maurizio Fermeglia – MO SE - UNITS
What is Molecular Simulation
Molecular simulation is a computational “experiment” conducted on a molecular model
Could be a single molecule (computational quantum chemistry)
Could involve O (10) – O (106) molecules
Computational quantum chemistry generally provides results for isolated or pairs of molecules Geometry
Thermochemistry
Frequencies
Anything associated with electronic structure
Trieste, 20 A pril, 2010 - slide 18 Maurizio Fermeglia – MO SE - UNITS
What is Molecular Simulation?
Molecular dynamics provides results for a system of molecules undergoing dynamic (deterministic)
motion Generates many configurations which are
averaged to provide measurements
Forces are used to evolve the system
The system is dynamic !!!
Alder e Wainwright 1957 - 1959
Monte Carlo provides results for a
system molecules undergoing stochastic motions Generates an ensemble average with no
element of time
Variation of energy is computed
1953 - Metropolis et al. in Los Alamos
Trieste, 20 A pril, 2010 - slide 19 Maurizio Fermeglia – MO SE - UNITS
Simulation Force Fields
Intramolecular forces
4
Trieste, 20 A pril, 2010 - slide 20 Maurizio Fermeglia – MO SE - UNITS
Simulation Force Fields
Intermolecular forces
Trieste, 20 A pril, 2010 - slide 21 Maurizio Fermeglia – MO SE - UNITS
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Trieste, 20 A pril, 2010 - slide 22 Maurizio Fermeglia – MO SE - UNITS
Definition of mesoscale
Does “mesoscale” have a precise meaning?
… has to do with equilibration
All the degrees of freedom
Of the smaller scale down
When seen from THAT scale
i.e. they have a relaxation time which is much shorter
than the time scale of interest
Generic definition: any intermediate scale at which
the phenomena at the next level down can be regarded as
always having equilibrated
at which new phenomena emerge
new phenomena with their own relaxation times
Trieste, 20 A pril, 2010 - slide 23 Maurizio Fermeglia – MO SE - UNITS
Molecular Dynamics Dissipative Particle Dynamics
ForceField based calculations
Soft potentials calculations
Fi = f (aii, aij, …, rc )
From atoms … to beads
Trieste, 20 A pril, 2010 - slide 24 Maurizio Fermeglia – MO SE - UNITS
Mesoscale Modelling Techniques
Trieste, 20 A pril, 2010 - slide 25 Maurizio Fermeglia – MO SE - UNITS
Continuum mesoscale methods: particle based methods
Diffusive and hydrodynamic particulate methods
Dissipative particle dynamics (DPD)
It is possible to coarse – grain a system without moving into a lattice
5
Trieste, 20 A pril, 2010 - slide 26 Maurizio Fermeglia – MO SE - UNITS
DPD: Equations of motion Dynamics: an extension of MD, with a short-ranged, soft, pair-wise force law
i and j label DPD „beads‟, and a ij is an interaction parameter between „beads‟ of type i and j
Polymeric materials are modeled by connecting beads by harmonic springs
Trieste, 20 A pril, 2010 - slide 27 Maurizio Fermeglia – MO SE - UNITS
Continuum mesoscale methods: free energy functional methods
An alternative to particulate or lattice techniques: MESODYNE
Evolution of the distribution of the order parameter, i.e.
densities or orientations
Free energy includes both ideal contributions (from non-
interacting parts of system) and non-ideal terms (representing interactions)
The intrachain correlations is described by a Gaussian chain
model is used because it allows a factorization of the interactions
hence is computationally very efficient
The noninteracting Gaussian chains are hence the ideal
system, interchain, i.e., non-bonded, interactions are treated as non-ideal
Interchain reactions enter into the effective external potential
Trieste, 20 A pril, 2010 - slide 28 Maurizio Fermeglia – MO SE - UNITS
Mesodyn Approach
Trieste, 20 A pril, 2010 - slide 29 Maurizio Fermeglia – MO SE - UNITS
Aqueous Pluronics L64 structures PEO-PPO-PEO block copolymers
Triblock Poly(ethylene oxide)-Poly(propylene oxide)
nonionic surfactant
used in detergency, dispersion stabilisation, lubrication, drug delivery etc
Predicted mesosphases: (a) (70% ) lamellar
(b) (60%) bicontinuous
(c) (55%) hexagonal
(d) (50%) micellar
Excellent agreement with experiments.
Same parameters also give correct predictions for other Pluronics.
Trieste, 20 A pril, 2010 - slide 30 Maurizio Fermeglia – MO SE - UNITS
Input parameters for Mesoscale simulation (MesoDyn or Dissipative Particle Dynamics)
The parameters for MesoDyn are 1. the bead size and Gaussian chain architecture
2. the bead mobilities M,
3. the effective Flory-Huggins interactions ij
Obtained by molecular modeling tools: bead size and Gaussian chain architecture: by MD
from characteristic ratio (C) in terms of Kuhn length
mobility: by Molecular Dynamics
Bead self diffusion coefficients
FH interactions: by Molecular Dynamics
Differences in non bonded energies between bulk and isolated
chain
Coslanich A, Fermeglia M, Ferrone M, Martinelli L, Pricl S, FOMMS 2003 and Cimtec 2004
Trieste, 20 A pril, 2010 - slide 31 Maurizio Fermeglia – MO SE - UNITS
Rapporto caratteristico
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200
N
Cin
f(%
)
Parameter 1: bead length, chain architecture
Molecular dynamics NPT runs on homo polymers C∞ calculation for the three
species
Monomer length
Kuhn lenght
Chain architecture
Polymer C∞ at 298 lk nm
PMMA 6.5
(exp 6.0-9.0)
2.259
PC 7.95
(exp 8.10)
8.370
22
0
2 NLnlCr
NLr max
6
Trieste, 20 A pril, 2010 - slide 32 Maurizio Fermeglia – MO SE - UNITS
Parameter 2: Bead self-diffusion coefficients
Molecular dynamics NPT runs on the polymers Slope of the MSD vs. time
Einstein equation D = b-1 M
Bead self-diffusion coefficient is necessary Input to MesoDyn
Conversion of the mesoscopic dimensionless time step (t ) to an effective time scale
t is the adimensional time step (integration algorithm)
h is the grid dimension
tMh 21bt
Self Diffusion coeff. 1543.1h
lk
Fermeglia M., Pricl S., Chem. Eng. Comm., 1267, 2003
N
i
iit
rtrdt
d
ND
1
2)0()(lim
6
1
MSD vs Time (LDPE)
y = 0,0388x + 3,2678
0
5
10
15
20
0 100 200 300 400
Time [ps]
MS
D [
A2]
Trieste, 20 A pril, 2010 - slide 33 Maurizio Fermeglia – MO SE - UNITS
Parameter 3: F-H interaction parameter chi
Molecular dynamics NPT and NVT runs
monmix V
RT
E
c
mix
coh
pure
coh
pure
cohmix
V
E
V
E
V
EE
2
2
1
1
isolated
nb
periodic
nbcoh EEE
Fermeglia, M. and Pricl S., AIChE J., 2619 (45), 1999
Trieste, 20 A pril, 2010 - slide 34 Maurizio Fermeglia – MO SE - UNITS
From Mesoscale to macroscale •Mechanical Prop. •Swelling •Thermal Prop.
•Electrical prop. •Transport prop. •…
•Component properties •Interactions
•Mesoscale parameters
Molecular Modeling
•Morphology – Phase behavior •Composition and density •Geometry of inclusions •Distribution of inclusions
Finite Elements Modeling
Mesoscale Modeling
Trieste, 20 A pril, 2010 - slide 35 Maurizio Fermeglia – MO SE - UNITS
Dissipative Particle Dynamics
Soft potentials calculations
Fi = f (aii, aij, …, rc )
Characteristic
dimension of
mesoscopic system
Micro - FEM Simulation
FEM Analysis:
Macroscopic properties
From beads … to micro
Trieste, 20 A pril, 2010 - slide 36 Maurizio Fermeglia – MO SE - UNITS
Fixed and variable grid Micro FEM
Fixed grid
Mesoprop
Variable
grid Palmyra
Mesoscale
DPD Mesodyn
Atomistic
MD o MC
Physical Prop.
Physical Prop.
Trieste, 20 A pril, 2010 - slide 37 Maurizio Fermeglia – MO SE - UNITS
Fixed and variable grid micro FEM
Interfacing Palmyra and MesoDyn Palmyra: each finite element = one phase , with property tensor Pi
MesoDyn: each element contains mixture of phases, conc. Ci
Geometry: map MesoDyn cubic elements to Palmyra tetrahedrons
Laplace equation is solved for electric conductance, diffusion and permeability
Local deformation allow the calculation of mechanical prop
7
Trieste, 20 A pril, 2010 - slide 38 Maurizio Fermeglia – MO SE - UNITS
Variable Grid micro FEM
MATSIM Palmyra
Variable grid
Trieste, 20 A pril, 2010 - slide 39 Maurizio Fermeglia – MO SE - UNITS
Barrier effect
MMT: prediction of permeability P=DK D=diffusivity, K=solubility
Important factors (A.Gusev,
H.Lusti, ):
Aspect ratio a
a = diameter/height quat
The larger the diameter, the longer the O2 path
Per cent of MMT in the system
Permeability
P/P0= realtive permeability
x=af
FEM simulation (Palmyra)
Examples and applications
Trieste, 20 A pril, 2010 - slide 41 Maurizio Fermeglia – MO SE - UNITS
Nano-structured materials
Trieste, 20 A pril, 2010 - slide 42 Maurizio Fermeglia – MO SE - UNITS
Automotive rear lamps
Rear lamp of the FIAT Idea
Different possibilities: PC/ABS blends are promising
PC: transparency, good mechanical properties
ABS: reflecting properties, lower viscosity
Polymer Clay nanocomposite Improve Mechanical properties
EU directive for the end-of-life treatment of vehicles (2000/53CE) before 2015 95% of industrial plastic scraps have to be recycled in all vehicles.
Side view Front view
Year 2006
Material recycle
Energy recovery
Material landfilled
Year 2015 (predicted)
Material recycle
Energy recovery
Material landfilled
Trieste, 20 A pril, 2010 - slide 43 Maurizio Fermeglia – MO SE - UNITS
Polymer – Layered Silicate Nanocomposites
Montmorillonite
~ 1
nm
100 - 500 nm
8
Trieste, 20 A pril, 2010 - slide 44 Maurizio Fermeglia – MO SE - UNITS
Polymer – Layered Silicate Nanocomposites
Intercalation vs Exfoliation
D.R. Paul et al., Polymer 49 (2008) 3187-3204
Trieste, 20 A pril, 2010 - slide 45 Maurizio Fermeglia – MO SE - UNITS
Polymer – Layered Silicate Nanocomposites
Organic Modifiers
~ 1 nm
Trieste, 20 A pril, 2010 - slide 46 Maurizio Fermeglia – MO SE - UNITS
Polymer – Layered Silicate Nanocomposites
Organic Modifiers 2 ÷ 4 nm
Quats
Trieste, 20 A pril, 2010 - slide 47 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100
nm
Molecular
Dynamics
(MD)
1 μm
~ 1 nm
~ 3 nm
Trieste, 20 A pril, 2010 - slide 48 Maurizio Fermeglia – MO SE - UNITS
Multicarbon layers of quats
The quat layer is thicker for larger quats
M3C6 -
smallest
M2(C18)2 -
largest
Trieste, 20 A pril, 2010 - slide 49 Maurizio Fermeglia – MO SE - UNITS
Predicted Binding energy vs. quat volume V
()
()
(∆)
6MMT/nylonbind
E
6/quatnylonbind
E
MMT/quatbind
E
9
Trieste, 20 A pril, 2010 - slide 50 Maurizio Fermeglia – MO SE - UNITS
(nylon-quat) + (nylon-MMT) binding energies vs. quat volume V
Trieste, 20 A pril, 2010 - slide 51 Maurizio Fermeglia – MO SE - UNITS
The role of alkyl tails on exfoliation
Decreasing platelet-platelet
attraction Increasing access for nylon-
silicate contacts Decreasing no. of nylon-alkyl
interactions Fornes T.D., Hunter D.L., Paul D.R., Macromolecules 2004, 37, 1793-1798
Trieste, 20 A pril, 2010 - slide 52 Maurizio Fermeglia – MO SE - UNITS
The role of alkyl tails on exfoliation TEM photomicrographs nylon 6 - MMT effect of compatibilizer A M4
B M3 (C18)
C M2 (C18)2
Fornes T.D., Hunter D.L., Paul D.R., Macromolecules 2004, 37, 1793-1798
Un-exfoliated clay
Well-exfoliated clay
Un-exfoliated clay +
dispersed platelets
Trieste, 20 A pril, 2010 - slide 53 Maurizio Fermeglia – MO SE - UNITS
Influence of alkyl tail number Tail Number - Binding PM
0.00
0.01
0.02
0.03
0.04
0.05
0.06
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
M2(C18)2 M3C18
Tail Number - Binding PQ
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
Tail Number - Binding PM
0.00
0.01
0.02
0.03
0.04
0.05
0.06
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
Scocchi G., 2009, Multiscale S imulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Trieste, 20 A pril, 2010 - slide 54 Maurizio Fermeglia – MO SE - UNITS
Influence of alkyl tail length
Tail Length - Eff. Binding
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
M3C12 M3C18
Tail Length - Binding PM
0.00
0.01
0.02
0.03
0.04
0.05
0.06
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
Tail Length - Binding PQ
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
Scocchi G., 2009, Multiscale S imulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Trieste, 20 A pril, 2010 - slide 55 Maurizio Fermeglia – MO SE - UNITS
Scocchi G., 2009, Multiscale S imulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Influence of hydroxyethyl groups
EtOH - Binding PM
0.00
0.01
0.02
0.03
0.04
0.05
0.06
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
MC18(EtOH)2 M3C18
EtOH - Binding PM
0.00
0.01
0.02
0.03
0.04
0.05
0.06
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
EtOH - Binding PQ
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
PA6 PET PP PE
Polymer
Bin
din
g E
ne
rgy
(k
ca
l/m
ol*
a)
10
Trieste, 20 A pril, 2010 - slide 56 Maurizio Fermeglia – MO SE - UNITS
Thermodynamics and spacing NVT Molecular Dynamics simulations for calculating the binding energies in
polymer-surfactant-MTM systems
NPT Molecular Dynamics simulation for predicting the equilibrium spacing (basal spacing) between the
MTM platelets as a function of surfactants
Toth R., Coslanich A, Ferrone M, Fermeglia M, Pricl S, Miertus S, Chiellini E, Polymer, 45: 8075 -8083 (2004)
Trieste, 20 A pril, 2010 - slide 57 Maurizio Fermeglia – MO SE - UNITS
Simulated basal spacing
System Calc. (Å) Exp. (Å)
MMT/20A M2(C18)2
24.9 24.2
MMT/30B MC18C2OH 19.3 18.5
MMT standard cation-exchange capacity CEC = 90 meq/100g
20A 30B smaller than 20A
Trieste, 20 A pril, 2010 - slide 58 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100
nm
Molecular
Dynamics
(MD)
1 μm
~ 1 nm
~ 3 nm
Trieste, 20 A pril, 2010 - slide 59 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100
nm
Molecular
Dynamics
(MD)
1 μm
~ 1 nm
~ 3 nm
Trieste, 20 A pril, 2010 - slide 60 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100 nm
Molecular
Dynamics
(MD)
Dissipative Particle
Dynamics (DPD)
1 μm
~ 1 nm
~ 3 nm
Trieste, 20 A pril, 2010 - slide 61 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100 nm
Molecular
Dynamics
(MD)
Dissipative Particle
Dynamics (DPD)
1 μm
~ 1 nm
~ 3 nm
~ 15 nm
11
Trieste, 20 A pril, 2010 - slide 62 Maurizio Fermeglia – MO SE - UNITS
Beads definition for M3C18:
ijijjjjjiiii
tot
sysEnEnEnE 2
From MD to DPD
Calculation of DPD parameters from MD (method 2)
For the system PA6 – quat – MMT
MD simulations NVT (500ps – 298 K - 10 conformations)
Estimation of Binding Energies
Calcualtion of energy per bead aij
Scocchi, Posocco, Fermeglia &
Pricl, J. Phys. Chem. B,
(2007), 111, 2143
Trieste, 20 A pril, 2010 - slide 63 Maurizio Fermeglia – MO SE - UNITS
DPD simulation for PCN
Calculation of DPD parameters from MD (method 2) For the system PA6 – quat – MMT
MD simulations NVT (500ps – 298 K - 10 conformations)
Estimation of Binding Energies
Calcualtion of energy per bead aij
DPD model to predict morpholgy of PCN stack Basal spacing from MD (or from
experiments)
Density distribution between the platelets is calcualted
Morphology is transferred to microFEm (variable grid) Calulation of mechanical properties,
barrier properties,…
Scocchi et al., Fluid Phase
Equilibria, (2007), 261, 366
Trieste, 20 A pril, 2010 - slide 64 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100
nm
Molecular
Dynamics
(MD)
Dissipative Particle
Dynamics (DPD)
1 μm
~ 1 nm
~ 3 nm
~ 15 nm
Trieste, 20 A pril, 2010 - slide 65 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1
nm
10 nm 100
nm
Molecular
Dynamics
(MD)
Dissipative Particle
Dynamics (DPD)
1 μm
~ 1 nm
~ 3 nm
~ 15 nm
~ 120 nm
Trieste, 20 A pril, 2010 - slide 66 Maurizio Fermeglia – MO SE - UNITS
Modeling and Simulation Methods
1 nm 10 nm 100 nm
Molecular
Dynamics
(MD)
Dissipative Particle
Dynamics (DPD)
1 μm
~ 1 nm
~ 3 nm
~ 15 nm
~ 120 nm
Finite Elements
Method (FEM)
~ 0.3 μm
Trieste, 20 A pril, 2010 - slide 67 Maurizio Fermeglia – MO SE - UNITS
T. D. Fornes, D. L.Hunter, D. R. Paul, Macromolecules 37 (2004) 1793-1798
Property calcualtion for the PCN
Properties calculated
Young modulus
Barrier properties
Scocchi et al., Fluid Phase
Equilibria, (2007), 261, 366
12
Trieste, 20 A pril, 2010 - slide 68 Maurizio Fermeglia – MO SE - UNITS
microFEM simulation for PCN Different degree of exfoliation
1.9 vol % MMT
4.5 W % MMT
Trieste, 20 A pril, 2010 - slide 69 Maurizio Fermeglia – MO SE - UNITS
PA6 – M2(C18)2 – CEC90
exp
1.20
1.25
1.30
1.35
1.40
1.45
1.50
1.55
1.60
1.65
1.70
A B C D E F
Decreasing Exfoliation Degree >>>
E/E
m
Cation Exchange
Capacity: 90
meq/100g
M2(C18)
2
PA6
T .D Fornes et al., Polymer 42 (2002) 5915
Scocchi G., 2009, Multiscale Simulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Trieste, 20 A pril, 2010 - slide 70 Maurizio Fermeglia – MO SE - UNITS
PP – M2(C18)2 – CEC90
M2(C18)
2
exp
1.60
1.65
1.70
1.75
1.80
1.85
1.90
A B C D E F
Decreasing Exfoliation Degree >>>
E/E
m
PP
M. T . Ton-That et al., Polym Eng Sci 44 (2004) 1212
Cation Exchange
Capacity: 90
meq/100g
Scocchi G., 2009, Multiscale Simulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Trieste, 20 A pril, 2010 - slide 71 Maurizio Fermeglia – MO SE - UNITS
PP – M2(C18)2 – CEC120
M2(C18)
2
PP
exp
1.40
1.50
1.60
1.70
1.80
1.90
2.00
A B C D E F
Decreasing Exfoliation Degree >>>
E/E
m
C. Deshmane et al., Mat. Sci. Eng. 458 (2007) 150
Cation Exchange
Capacity: 120
meq/100g
Scocchi G., 2009, Multiscale Simulation of Polymer-Clay Nanocomposites, phd Thesis, University of Trieste
Trieste, 20 A pril, 2010 - slide 72 Maurizio Fermeglia – MO SE - UNITS
Model performance
Mechanical properties Young module (E / E°)
Loading of MMT 4.6 wt %
The model … Effect of the surface modifier
Cation Exchange Capacity considered in the model
Degree of exfoliation is considered in the model
Good agreement with experiments
System Calcualted
data E/E°
Exp. Literature
data E/E°
Exp. Project
data E/E°
CEC
meq/100g
PA6 – C20A 1.53 1.55 - 90
PA6 – M3C18 1.68 1.71 - 90
PA6 – C30B 1.65 1.63 1.63 90
PP – PpgMA – C20A 1.55 1.53 1.44 90
PP – PpgMA – C15A 1.52 1.51 1.44 120
Trieste, 20 A pril, 2010 - slide 73 Maurizio Fermeglia – MO SE - UNITS
… also for ABS - MMT Previous scale results and experiments:
ABS with MMT creates domains: MMT sheets packed in layers (spacing ≈ 3nm)
Only SAN enters MMT layers creating “stacks”
Islands of rubber phase outside the stacks
SAN
(1)
The stack
(2)
The bulk
Young‟s module of B-SAN and SAN from previous simulations**
2 FEM simulations (total MMT is 2%):
1) The stack (MMT platelet in SAN matrix)
2) The complete nanocomposite (stacks into a matrix of rubber islands + SAN)
Young‟s modulus of the stack
is obtained form 1° s imulation
stack
**MMT Young modulus from A.R. Pawley et.al., American Mineralogist (2002) 87, 1172–1182 *H.A. Stretz et al. / Polymer 46 (2005) 3818–3830
P. Cosoli, G. Scocchi, S. Pricl, M. Fermeglia, Microporous and Mesoporous Materials, 107: 169-179, 2008. .
13
Trieste, 20 A pril, 2010 - slide 74 Maurizio Fermeglia – MO SE - UNITS
… also for ABS MMT – system.
Young Modulus [GPa] 3,15
(2,416 Young‟s modulus of the blend)
Bulk Modulus [GPa] 4,42
Poisson ratio 0,38
Dependence of E/E0 over aspect ratio
0
2
4
6
8
10
12
14
16
0 50 100 150 200
a
E/E
0 .
Results of mechanical properties
Results are in an acceptable range (H.A. Stretz et al. / Polymer 46 (2005) 3818–3830)
Influence of aspect ratio and loading
E does not change if a>70 Aspect ratio a=Ø/l;
E0=E bulk(=E blend); E=E nanocomposite
x=const
The behavior is linear
E/E0 dependence over MMT % (x)
0
2000
4000
6000
8000
10000
12000
0 1 2 3 4 5 6
x
E/E
0.
x=%MMT
P. Cosoli, G. Scocchi, S. Pricl, M. Fermeglia, Microporous and Mesoporous Materials, 107: 169-179, 2008. . Trieste, 20 A pril, 2010 - slide 75 Maurizio Fermeglia – MO SE - UNITS
Software used
Atomistic simulationa
Material Studio 4.x – Discover
FF: COMPASS
Mesoscale simualtion
Material Studio 4.x – DPD
Material Studio 4.x – MEsodyn (ABS)
microFEM
Material Studio 4.x – Mesoprop (fixed grid)
MATSIM Palmyra (variable grid)
Trieste, 20 A pril, 2010 - slide 76 Maurizio Fermeglia – MO SE - UNITS
Nano-structured materials
Trieste, 20 A pril, 2010 - slide 77 Maurizio Fermeglia – MO SE - UNITS
MULTISCALE SIMULATION OF HYBRID ORGANIC-INORGANIC (O/I) NANOCOMPOSITES
DESIGN OF NANOFILLED MULTIFUNCTIONAL MATERIALS BY MULTISCALE SIMULATION
Automotive industry: rear/front lamps with LED technology
Fiat Automotive Industry, Italy Cima Nanotech, Israel SOL-GEL, Israel Fraunhofer Institute Bremen, Germany
University of Padova, Italy E. Hala Laboratory of Thermodynamics, Czech Republic Neotech, Germany Dymax, Germany
1. Refractive index improvement with ZnS and TiO2 nanoparticles
2. Mechanical properties
Industrial Application
Trieste, 20 A pril, 2010 - slide 78 Maurizio Fermeglia – MO SE - UNITS
I-O composite materials
Type I
Type II
Semi, Full, Covalent Interpenetrating Network (IPN)
Trieste, 20 A pril, 2010 - slide 79 Maurizio Fermeglia – MO SE - UNITS
Atomistic simulation for the GPTMS matrix: improvement of refractive index
Single molecules of hydrolyzed GPTMS
Bond analysis and individuation of reactive
sites
Creation of a new bond and elimination of the water molecule from the system
(3-Glycidoxypropyl)trimethoxysile (GPTMS)
14
Trieste, 20 A pril, 2010 - slide 80 Maurizio Fermeglia – MO SE - UNITS
Filmato
Atomistic simulation for the GPTMS matrix: reactive MD
Geometry optimization
Molecular dynamics
Bond analysis Individuation of reactive sites of
condensation (max 3 each step)
Creation of a new Si-O-Si bond
Elimination of the water
molecule from the system
Trieste, 20 A pril, 2010 - slide 81 Maurizio Fermeglia – MO SE - UNITS
Mechanical Properties - Young’s modulus E 2.1 GPa (1- 4 GPa) @ 0.93
a (-) E calc (GPa)
E exp (GPa)
0.30 0.028 0.024
0.50 0.063 0.072
0.70 0.880 0.910
0.90 2.066
0.93 2.103
Young modulus as function of a
Experiments from Guglielmi, Martucci, Brusatin,
UNIPD
Trieste, 20 A pril, 2010 - slide 82 Maurizio Fermeglia – MO SE - UNITS
The hybrid O/I system with ZnS
Atomistic simulation for estimating mesoscale parameters
Trieste, 20 A pril, 2010 - slide 83 Maurizio Fermeglia – MO SE - UNITS
Rings
0 4 8 12
Pro
babili
ty
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Atomistic simuls
DPD
Mesoscale parameter estimation: architecture
ZnS Nanoparticles Covered by MPTMS
“Effectively” as ICOSAHEDRON (13 DPD
Particles)
GPTMS representation
Beads of 4-8 and 12 rings
ZnS+MPTMS vs. Particle Representation of GPTMS Networking
DPD
4-Ring (4 GPTMS)
8-Ring (8 GPTMS)
DP
D
DP
D
12-Ring (12 GPTMS)
DPD DPD
DPD
Trieste, 20 A pril, 2010 - slide 84 Maurizio Fermeglia – MO SE - UNITS
Mesoscale parameter estimation: interactions
5 independent configuration for each system
Energy calculation average of trajectories
BAtot
AB EEEE int
Trieste, 20 A pril, 2010 - slide 85 Maurizio Fermeglia – MO SE - UNITS
Mesoscale: 2% nanoparticle loading
Reactive DPD mesoscale simulation results DPD combined with fractional particle approach
ZnS covered by 25% MPTMS GPTMS not visible
Density field (left) isodensity surface (right)
M. Lisal, J. K. Brennan, W. R. Smith, J. Chem. Phys. 125, 16490
(2006).
15
Trieste, 20 A pril, 2010 - slide 86 Maurizio Fermeglia – MO SE - UNITS
Fixed grid MicroFEM simulation
GPTMS-MPTMS-ZnS system
Mechanical properties as function of volume loading NP = 15%
Calc Exp Calc Exp
Volume loading (%) 2 15
Young’s modulus (GPa) 4.08 4.20 9.25 10.3
Poisson ratio (-) 0.265 0.257
Shear modulus (GPa) 1.59 3.6
Bulk modulus (GPa) 2.9 6.4
Density (g/cm3) 1.411 1.782
Matrix Young’s Module: 2.10 GPa at a =o.93
Experiments from Guglielmi, Martucci, Brusatin,
UNIPD Trieste, 20 A pril, 2010 - slide 87 Maurizio Fermeglia – MO SE - UNITS
TiO2 - anatase
Trieste, 20 A pril, 2010 - slide 88 Maurizio Fermeglia – MO SE - UNITS
Software used
Atomistic simulationa
Material Studio 4.x – Discover
FF: COMPASS
Scripting in MS
Mesoscale simualtion
Material Studio 4.x – DPD
Reactive DPD (developed within MULTIPRO)
microFEM
Material Studio 4.x – Mesoprop
Trieste, 20 A pril, 2010 - slide 89 Maurizio Fermeglia – MO SE - UNITS
Self-Assembly of Nanoparticle Mixtures in
Lamellar Diblock Copolymers Experimental evidence (Chiu et al. JACS 2005)
Polymer: poly styrene-b-2 vinyl pyridine
Figure 1: PS coated gold nanoparticles: PSD distribution
Figure 2a: PS-PVP with PS coated nanoparticles: nanoparticles segregates in the center of the PS domains
Figure 2c: PS-PVP with particles coated with PS-PVP: nanoparticles are located mainly at the interfaces.
Figure 1 Figure 2a Figure 2c
Chiu, J.J, Bumjoon J.K., Kramer E.J. Pine, D.J., JACS, 2005, 127, 5036
Trieste, 20 A pril, 2010 - slide 90 Maurizio Fermeglia – MO SE - UNITS
The system: symmetric diblock copolymer poly(styrene-b-2 vinyl pyridine) (PS-PVP)
Nanoparticles covered by PS or PVP or mixture of PS and PVP icosahedral structure
neutral, central DPD bead
surrounded by 12 DPD beads
of type A (PS), or B (PVP)
A and B at the vertex of the
icosahedron
90 Fermeglia, M., Posocco P., Maly M., Pricl S., IEC, (2008)
Trieste, 20 A pril, 2010 - slide 91 Maurizio Fermeglia – MO SE - UNITS
Lamellae: A or B covering
Repulsive forces between
nanoparticles and corresponding blocks weak and identical aAA=25
and aAB =39.84
remarkable tendency to segregate to the center of the corresponding
domain;
perfect agreement with the
corresponding experimental evidences.
91
16
Trieste, 20 A pril, 2010 - slide 92 Maurizio Fermeglia – MO SE - UNITS
Lamellae: A or B covering
Repulsive forces between
nanoparticles and corresponding blocks weak and identical aAA=25
and aAB =39.84
remarkable tendency to segregate to the center of the corresponding
domain;
perfect agreement with the
corresponding experimental evidences.
92 Trieste, 20 A pril, 2010 - slide 93 Maurizio Fermeglia – MO SE - UNITS
Lamellae: A or B covering
Repulsive forces between
nanoparticles and corresponding blocks weak and identical aAA=25
and aAB =39.84
remarkable tendency to segregate to the center of the corresponding
domain;
perfect agreement with the
corresponding experimental evidences.
93
Segregation inside the domains
Enthalpic positive effect (similar interactions);
Entropic positive effect: the chains
can accommodate the particles without substantial deformations.
The particle localization results in a
decrease of their translational entropy;
Trieste, 20 A pril, 2010 - slide 94 Maurizio Fermeglia – MO SE - UNITS 94
Lamellae: equal mixture of homogeneous A and B covering (A6B6(h))
An opposite trend: the
nanoparticles locate at the interfaces between the A-B
blocks Same if the particle is only covered by A (other
beads are neutral)
Trieste, 20 A pril, 2010 - slide 96 Maurizio Fermeglia – MO SE - UNITS 96
Lamellae: excess of A or B covering A1B11
A particle distribution utterly similar to the case of full A
(or B) coverage is obtained.
Trieste, 20 A pril, 2010 - slide 97 Maurizio Fermeglia – MO SE - UNITS
Lamellae: the hybrid behavior: A3B9(h) and A3B9(r)
The maxima of the nanoparticle density are located between the centers of the compatible lamellas and the block interfaces. Same if the particle is only covered by A (other beads are neutral)
97 Trieste, 20 A pril, 2010 - slide 98 Maurizio Fermeglia – MO SE - UNITS 98
Cylinders: A and B covering only: 5% loading
Particles segregate in the middle of the domain (similar as
the lamellae case)
17
Trieste, 20 A pril, 2010 - slide 99 Maurizio Fermeglia – MO SE - UNITS
Cylinders: A and B covering with 3% loading
Decreasing the particle loading much less perturbation
of the cylindrical geometry (particles in the middle of the domains)
99 Trieste, 20 A pril, 2010 - slide 100 Maurizio Fermeglia – MO SE - UNITS
Cylinders: equal mixture of homogeneus A and B covering (A6B6(h)): 3% loading
The morphology is preserved
Nanoparticles location at the interface.
100
Trieste, 20 A pril, 2010 - slide 101 Maurizio Fermeglia – MO SE - UNITS
Cylinders: equal mixture of homogeneus A and B covering (A6B6(h)) 5% loading
Destruction of the hexagonal geometry of the matrix, well-oriented lamellar morphology, particles are ultimately segregated at the block interfaces
101 Trieste, 20 A pril, 2010 - slide 102 Maurizio Fermeglia – MO SE - UNITS
One single A-type bead is sufficient to lead all particles to
locate themselves at the interfaces between the blocks.
Opposite to the lamellar case
102
A1B11 B12
Cylinders: excess of A or B covering (A1B11)
Trieste, 20 A pril, 2010 - slide 103 Maurizio Fermeglia – MO SE - UNITS
Compatibility of CNT with polymers
MD simulation FH parameter for polymers
NCT and NPT simulation for CNT
De bundling energies Estimating FH parameter for
CNT
Experimental data for CNT-Poly(m-phenylenevinylene) (PmPV) composites for CNTs of diameters ranging between 1.35 and 1.55 nm. (Dalton, A. B., et al., J. Phys. Chem. B, 104, 10012, (2000)).
consistent with strong hydrophobicity known for all CNTs (Note: δ water ~ 47.9 (J/cm3)1/2
Solub. Parameter
Trieste, 20 A pril, 2010 - slide 104 Maurizio Fermeglia – MO SE - UNITS
Mesoscale morphology of polymer CNT: DPD
A. Maiti, J.T. Wescott and P. Kung, Molecular Simulation 31, 143 (2005).
Stiffness of the CNT is considered in
DPD
PMMA + CNT (10,10) left
PMMA + CNT (15,15) right with and
without compatibilizer
18
Trieste, 20 A pril, 2010 - slide 105 Maurizio Fermeglia – MO SE - UNITS
Macroscopic simulation by FEM
Average electric conductance in the XY plane versus vol%
CNT for A10-, B10-, A6B14-and A10B10- CNT composites.
A. Maiti, J. T. Wescott and G. Goldbeck-Wood, Int. J. Nanotechnology, 2, No. 3, (2005)
Trieste, 20 A pril, 2010 - slide 106 Maurizio Fermeglia – MO SE - UNITS
Conclusions
Theory, modeling and simulation (TMS) play vital
role in nanoscale science and engineering Interpretation of experiments
Design of experiments
Characterization and design of nanostructured materials
Design and control of manufacture
TMS in nanoscale science and engineering Typically requires many different techniques
Future advances in field will result from development of additional methods
Reverse mapping multiscale methods, electron transport
dynamics, optical properties, self-validating forcefields,…
Trieste, 20 A pril, 2010 - slide 107 Maurizio Fermeglia – MO SE - UNITS
Further reading and materials
Slides in the MOSE web sites
PDF of most of MOSE publications
An introductory paper
MOSE.UNITS.IT Trieste, 20 A pril, 2010 - slide 108 Maurizio Fermeglia – MO SE - UNITS
MOSE – THE MOVIE