Computational Nanoscience: An Emerging Tool for Exploring and Exploiting the Nanoscale

1
Computational Nanoscience An Emerging Tool for
Exploring and Exploiting the Nanoscale
Peter T. Cummings Department of Chemical
Engineering, Vanderbilt University and Nanomateria
ls Theory Institute and Chemical Sciences
DivisionOak Ridge National Laboratory Fall
Creek Falls Workshop on High-End Computing in
Science and Engineering Fall Creek Falls,
TN October 26-28, 2003
2
Acknowledgments

• Research support
• Division of Chemical Sciences, Office of Basic
  Energy Sciences, U.S. Department of Energy
• National Science Foundation Interfacial,
  Transport and Thermodynamics, NANO and Division
  of Materials Research
• National Energy Research Supercomputing Center
  (NERSC)
• Center for Computational Sciences, Oak Ridge
  National Laboratory
• Collaborators
• Clare McCabe (CSM), Milan Predota (Czech Academy
  of Sciences), Sharon Glotzer and John Keiffer
  (UMich), Matt Neurock (Virginia), David Keffer
  (U. Tenn), Shengting Cui (U. Tenn.)
• ORNL David Dean, Predrag Krstic, Jack Wells,
  Xiaoguang Zhang, Hank Cochran
• Yongsheng Leng (VU)
• Collin Wick (DOE Comp Sci Fellow from U. Minn.),
  Jose Rivera (U. Tenn), T. Ionescu (VU)

3
Outline of Talk

• Introduction
• Theory, Modeling and Simulation in Nanoscience
• ORNL Center for Nanophase Materials Science and
  Nanomaterials Theory Institute
• Algorithmic aside
• Molecular electronics
• Multiscale modeling
• Nanoconfined fluid rheology and structure
• Rheology of nanoconfined alkanes
• Classical Simulations of Carbon Nanotubes
• Sliding behavior of multiwall nanotubes
• Organic-inorganic nanocomposite materials
• Multiscale modeling
• Conclusions

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Introduction

• 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
• National Nanotechnology Initiative
• http//www.nano.gov
• 710 million approved by Congress for FY 2003.
• FY 2004-2006 request 2B

M. Roco, FY 2002 National Nanotechnology
Investment Budget Request
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Introduction

• Theory, modeling and simulation (TMS)
• Expected to play key role in nanoscale science
  and technology
• Nanotechnology Research Directions IWGN
  Workshop Report. Vision for Nanotechnology
  Research and Development in the Next Decade,
  edited by M.C. Roco, S. Williams, P. Alivisatos,
  Kluwer Academic Publisher, 2000
• Also available on-line at http//www.nano.gov
• Chapter 2, Investigative Tools Theory, Modeling,
  and Simulation, by D. Dixon, P. T. Cummings, and
  K. Hess
• Discusses issues and examples
• 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.go
  v/bes/Theory_and_Modeling_in_Nanoscience.pdf

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Introduction

• Heirarchy of methods relevant to nanoscale
  science and technology
• Connection to macroscale

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Introduction

• TMS advances over past 15 years relevant to
  nanoscience
• Moores Law
• Gordon Bell Prize 1Gflop/s in 1988 vs. 27
  Tflop/s in 2002
• More than four order of magnitude increase in 14
  years
• Explosion in application and utility of density
  functional theory
• Molecular dynamics on as many as billions of
  atoms
• Revolution in Monte Carlo methods (Gibbs
  ensemble, continuum configurational bias,
  tempering, etc)
• Extraordinarily fast equilibration of systems
  with long relaxation times
• New mesoscale methods (including dissipative
  particle dynamics and field-theoretic polymer
  simulation)
• Applicable to systems with long relaxation times
  and large spatial scales
• Quantum Monte Carlo methods for nearly exact
  descriptions of the electronic structures of
  molecules
• Car-Parrinello and related methods for ab initio
  dynamics
• Reactions, complex interfaces,

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Why is TMS so crucial to NSE?

• Interpretation of experiment
• Many experiments at the nanoscale require TMS to
  understand what is being measured

• Unlike bulk systems, large-scale
  manufacturability of nanoscale systems will
  require deep theoretical understanding
• Inherent strong dependence on spatial
  dimensions

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Center for Nanophase Materials SciencesOak Ridge
National Laboratory
Specializing in neutron science, synthesis
science, and theory/modeling/simulation

• Neutron Science
• Opportunity to assume world leadership using
  unique capabilities of neutron scattering to
  understand nanoscale materials and processes
• Synthesis Science
• Science-driven synthesis will be the enabler of
  new generations of advanced materials
• Theory/Modeling/Simulation
• The Nanomaterials Theory Institute
• Scientific thrusts in 10 multidisciplinary
  research focus areas
• Access to other major ORNL facilities
• Spallation Neutron Source
• High-Flux Isotope Reactor
• Began Sept, 2002
• 60M for building and equipment 18M/yr ongoing

SNS
HFIR
Center for Nanophase Materials Sciences
http//www.cnms.ornl.gov
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Examples

• Nanorheology NSF NANO
• Nanoconfined fluid rheology and structure
• Sliding double-walled carbon nanotubes
• Molecular electronics ORNL LDRD DOE Comp
  Nanoscience
• Structure of self-assembled monolayers
• Hybrid organic-inorganic nanocomposite materials
  NSF NIRT
• Polyhedral oligomeric silsequioxane (POSS)
  molecules
• Nanoscale complexity at metal oxide surfaces DOE
  NSET, NSF NIRT
• Planar interfaces and nanoparticles
• Fluids in nanopores ORNL LDRD
• Phase equilibria of water and water/carbon
  dioxide mixtures in single-walled carbon
  nanotubes
• Self-Assembly of Polyelectrolyte Structures in
  Solution From Atomic Interactions to Nanoscale
  Assemblies DOE NSET

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Algorithmic Aside

• Solve Newtons equations (or variation) for
  positions and velocities of atoms
• Solve 6N first-order non-linear differential
  equations numerically, where N is typically
  103-106 (as high as 109)
• Time step 10-15 s
• 1 ns 106 time steps, 1ms 109 time steps
• Numerically intensive
• Complexity measure atoms x time-steps
• Extreme values 1012-1014
• Protein folding for 1ms 104 x 109

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Algorithmic Aside

• Massively parallel molecular dynamics
• Domain decomposition - large systems
• Replicated data - long simulation times

• Scales well for homogeneous systems
• Difficult to program/implement
• Best suited to short-ranged forces

• Easily implemented
• Equally effective for short- and long-ranged
  forces
• Does not scale well for large numbers of molecules

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Algorithmic Aside

• Time-complexity bottleneck

Size is easy Time is hard
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Algorithmic Aside

• Algorithm/theory vs hardware
• David Landau, U. of Georgia

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Outline of Talk

• Introduction
• Theory, Modeling and Simulation in Nanoscience
• ORNL Center for Nanophase Materials Science and
  Nanomaterials Theory Institute
• Molecular electronics
• Multiscale modeling
• Nanoconfined fluid rheology and structure
• Rheology of nanoconfined alkanes
• Classical Simulations of Carbon Nanotubes
• Sliding behavior of multiwall nanotubes
• Organic-inorganic nanocomposite materials
• Multiscale modeling
• Conclusions

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Molecular Electronics

• Motivation
• Lithographic fabrication of solid-state
  silicon-based electronic devices that obey
  Moores law is reaching fundamental and physical
  limitations and becoming extremely expensive
• Self-assembled molecular-based electronic
  systems composed of many single-molecule
  devices may provide a way to construct future
  computers with ultra dense, ultra fast
  molecular-sized components
• Possibility of fabricating single-molecule
  devices proposed theoretically by Ratner
• Aviram and Ratner, "Molecular rectifiers," Chem.
  Phys. Letts., 29, 283 (1974)
• Landmark experiment
• Experimental measurement of conductance of
  1,4-benzenedithiol between Au contacts Reed et
  al., "Conductance of a Molecular Junction,"
  Science, 278, 252-254 (1997)

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Molecular Electronics

• Experimental uncertainties
• 30 papers by young experimental star at Bell
  Labs found to be fraudulent
• Experiments are difficult, usually not
  reproducible by other groups
• Established results are being questioned

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Molecular Electronics

• Experiment vs. theory
• 3 orders of magnitude difference

Reed et al., Science, 278, 252-254 (1997)
Di Ventra, et al., Phys. Rev. Letts., 84, 979-982
(2000).
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Molecular Electronics

• Closing the gap
• Cui et al. experiment
• Ensures bonded contact at each end of octanethiol
  molecule
• Conductance measured in integer increments
  corresponding to 1-5 contacts
• Single-molecule conductance inferred
• Reduces difference between theory and experiment
  to less then one order of magnitude

Cui, et al., Science, 294, 571-574 (2001)
Kipps, Science, 294, 536-537 (2001)
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Molecular Electronics

• Multi-level approach
• Ab initio calculations to characterize gold-BDT
  interaction
• Structure of self-assembled monolayer (SAM) of
  BDT on Au(111) surface
• Ab initio calculation of conductance using
  structure within SAM

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GEMC results
Condensed phase of benzenethiol molecules
adsorbed on 111 Au surface (T298K)
Structure of benzenethiol SAM by GEMC Lines
connecting sulfur-occup-ied sites show same
structure as STM
Structure of benzenethiol SAM by GEMC
Probabil-ity density of sulfur atom around sulfur
atom
High-resolution STM image of ordered structure of
benzenethiol SAM. From Wan et al., J. Phys.
Chem. B, 104 (2000) 3563-3569
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Molecular Dynamics

• Molecular configuration and BDT dynamics behavior
• Fully occupied Au(111) surface
• Structure on surface
• Partly influenced by details of Au-BDT
  interaction
• Dependent on basis function
• Largely determined by intermolecular excluded
  volume interactions
• Average tilt (?), azimuthal (?) and twist (?)
  angles quite independent of basis function

Well-ordered herringbone structure in 120
direction
Krstíc et al., Computational Chemistry for
Molecular Electronics, Comp. Mat. Res., in press
(2003) Leng et al., Structure and dynamics of
benzenedithiol monolayer on Au (111) surface, J.
Phys. Chem. B, in press (2003)
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Electronic Structure Calculations

• Significant advance in theory
• Closed form expression for transmission with
  semi-infinite leads
• Krstíc et al., Generalized conductance formula
  for multiband tight-binding model, PRB, 66,
  205319 (2002)
• Place pseudo-molecules between leads in
  calculation
• Consistency shows correctness

molecule 1
molecule 2
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Outline of Talk

• Introduction
• Theory, Modeling and Simulation in Nanoscience
• ORNL Center for Nanophase Materials Science and
  Nanomaterials Theory Institute
• Molecular electronics
• Multiscale modeling
• Nanoconfined fluid rheology and structure
• Rheology of nanoconfined alkanes
• Classical Simulations of Carbon Nanotubes
• Sliding behavior of multiwall nanotubes
• Organic-inorganic nanocomposite materials
• Multiscale modeling
• Conclusions

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Rheology of Confined Dodecane

• Experimentally see an increase in viscosity of
  the confined fluid of several orders of magnitude
  above the bulk value
• Dodecane confined between mica sheets at ambient
  conditions

Experimental bulk value
.
Hu et al., Phys. Rev.Letts., 66, 2758-2761 (1991)
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Hard Disk Drive Lubrication
http//alme1.almaden.ibm.com/sst/storage/hdi/inter
action.shtml
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Models and Methodology

• Intramolecular interactions
• Intermolecular interaction

Bond stretching
Bond bending
r
q
Torsional potential
f
Lennard-Jones
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Displacement under Constant Shear Stress

• Dodecane confined between mica sheets
• Six-layer gap (2.36 nm)
• Shear stress 2.8 x107 N/m2

Constant applied shear stress
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Sliding Behavior

• Dodecane confined between mica sheets
• Six-layer gap (2.36 nm)
• Shear stress 2.8 x107 N/m2

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Stick-Slip Behavior

• Dodecane confined between mica sheets
• Six-layer gap (2.36 nm)
• Shear stress 2.8 x106 N/m2

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Stick-Slip Behavior

• Dodecane confined between mica sheets
• Six-layer gap (2.36 nm)
• Shear stress 2.8 x106 N/m2

270 ps
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Comparison of Simulation and Experiment

• Strain rate dependent viscosity for confined
  dodecane

S. T. Cui, C. McCabe, P. T. Cummings, H. D.
Cochran, J. Chem. Phys., 118 (2003) 8941-8944
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Rheology of Confined Alkane Liquids

• Klein and Kumacheva, Science 269, 816 (1995) J.
  Chem. Phys. 108, 6996 (1998) ibid. 108, 7010
  (1998)
• OMCTS and cyclohexane confined between mica
  sheets in surface force apparatus
• When film thickness is six layers or less
• Dramatic increase in viscosity of six to seven
  orders of magnitude
• Ability to sustain a non-zero yield stress
  (solid-like behavior)
• When film thickness seven layers or more
• No yield stress (fluid-like behavior)

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Solidification Behavior

• Dodecane confined between mica sheets
• Liquid-like behavior for 7 layers of fluid or
  more (no yield stress)
• Solid-like behavior (yield stress 106 N/m2) at
  6 or less layers of confined fluid
• First simulation studies consistent with
  experiments of Klein
• Completely consistent with corresponding states
  theory for shift in freezing temperature under
  confinement
• Radhakrishnan et al., JCP, 112, 11048 (2000)

Cui et al., J. Chem. Phys., 114 (2001) 71897195
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Origin of Solidification Behavior
Dodecane
Dodecane
Dodecane
Dodecane
P lt 0.1 MPa
P 0.1 MPa rbulk
Mica
compress
Dodecane
P 0.1 MPa rconfined
Mica
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Origin of Solidification Behavior
At 0.1 MPa rbulk-liquid 0.75 g/cc rbulk-solid
0.84 g/cc
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Outline of Talk

• Introduction
• Theory, Modeling and Simulation in Nanoscience
• ORNL Center for Nanophase Materials Science and
  Nanomaterials Theory Institute
• Molecular electronics
• Multiscale modeling
• Nanoconfined fluid rheology and structure
• Rheology of nanoconfined alkanes
• Classical Simulations of Carbon Nanotubes
• Sliding behavior of multiwall nanotubes
• Organic-inorganic nanocomposite materials
• Multiscale modeling
• Conclusions

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Experimental

• Separating inner shells
• Cumings and Zetl, Science 289, 602 (2000).

Multiwalled Length 330 nm Dynamic Strength 0.43
MPa
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Experimental Antecedents

• Separating inner shells
• Yu, Yakobson, and Ruoff, J. Phys. Chem B, 104,
  8764 (2000).

Multiwalled Length 7,000 nm Dynamic Strength 0.08
MPa
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Theoretical predictions

• Oscillatory Behavior
• Zheng and Jiang, Phys. Rev. Lett. 88, 045503
  (2002).

lt-force
released
freq ? length-1
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This Work

• Molecular dynamics
• NVT ensemble
• Multiple time step algorithm (r-RESPA)
• Slow Time step of 2.2 fs
• T 298.15 K, vacuum
• Spherically truncated Lennard-Jones potential
• Cutoff radius of 13.6 Å
• Potential DRIEDING model
• Guo, Karasawa, and Goddard, Nature 351, 464
  (1991).
• Fully flexible model composed of Lennard-Jones
  sites.
• Used to predict packing structures in fullerenes,
  pure and doped carbon nanotubes

Rivera, J. L., McCabe, C., and Cummings, P. T.,
Nano Letters, 3 (2003) 1001-1005 Highlighted by
Phillip Ballin Nature Materials, June 12, 2003
43
This Work

• Systems Studied
• Double-wall carbon nanotube
• Chiral conformation (7,0) / (9,9)
• Incommensurate system
• Superlubricity
• Interlayer distance 0.34 nm
• Outer diameter 1.22 nm
• Lengths 12.21 - 98.24 nm

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Damped Oscillations - 24.56 nm
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Damped Oscillations - 24.56 nm
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Model Predictions
24.56 nm
12.21 nm
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Model Predictions
49.27 nm
36.92 nm
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Outline of Talk

• Introduction
• Theory, Modeling and Simulation in Nanoscience
• ORNL Center for Nanophase Materials Science and
  Nanomaterials Theory Institute
• Molecular electronics
• Multiscale modeling
• Nanoconfined fluid rheology and structure
• Rheology of nanoconfined alkanes
• Classical Simulations of Carbon Nanotubes
• Sliding behavior of multiwall nanotubes
• Organic-inorganic nanocomposite materials
• Multiscale modeling
• Conclusions

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Multiscale Modeling of Hybrid Nanostructured
Materials

• Polyhedral oligomeric silsesquioxanes (POSS)
• Initial focus on cubic POSS as basic nano
  building block
• (HSiO1.5)8
• Most experimental data
• Extremely versatile
• Functionalized in many ways
• Functionalization affects solubility,
  diffusivity, rheology,
• Cross-linked to create network structures
• Alloyed with polymer
• Nanocomposites
• Can be synthesized on large scale
• Hybrid Plastics

(RSiO1.5)8
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Multiscale Modeling of Hybrid Nanostructured
Materials

• NSF NIRT project DMR-0103399

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Ab initio studies of POSS

• Structure of POSS(H)8 cube

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Ab initio studies of POSS

• Low energy (4eV) collision of atomic O with a
  POSS
• Atomic O inserted in POSS structure
• Insertion in O-H bond (yielding a silanol)
• Torsional energy profile along dihedral angle
  Si-C-C-C in propyl- and butyl-POSS

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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
• Multiscale methods, electron transport dynamics,
  optical properties, self-validating forcefields,

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http//www.cnms.ornl.gov
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FOMMS 2003Keystone Resort, COJuly 6-11, 2003

• Second international conference in series
• Applications and theory of computational quantum
  chemistry and molecular simulation integrated
  with process and product design
• Topics of special interest include
• Nanoscale systems
• Molecular Materials Design
• Conceptual Chemical Process Design
• Molecular Scale Reaction Engineering
• Molecular Rheology
• Multiple Time Scale and Mesoscopic Simulation
  Techniques
• Future Trends in Molecular Modeling, Simulation
  and Design

http//www.mines.edu/Academic/chemeng/fomms