ChE/MSE 557 Intro part 2 - University of Michigan erjank/Lectures/557/557-Lecture1b-Intro.¢  Intro part

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  • ChE/MSE 557 Fall 2006 1Computational Nanoscience of Soft Materialssglotzer@umich.edu

    ChE/MSE 557 Intro part 2

    What is the role of simulation in nanoscience research?

  • ChE/MSE 557 Fall 2006 2Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Opportunities for Simulation

    • Simulation – Extends window of observation

    – Helps interpret experimental results – Provides tests of new theories

    and predictions for experiment

    Simulation complements both experiment and theory.

  • ChE/MSE 557 Fall 2006 3Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Opportunities for Simulation: 2006

    • Enormous gains in computer – Speed -

    • processors, bus, memory access – Memory – Storage – Affordability – Accessibility – Ease of use

    Computer simulation is not just for the selected few anymore: it’s mainstream!

  • ChE/MSE 557 Fall 2006 4Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Model vs. Method

    • Using computational science to study materials phenomena involves both a model and a method.

    – The model captures the essential features of the phenomena we wish to describe.

    – The simulation method is what we use to study the model.

    – Sometimes, the model and the method are intertwined and considered together in a simulation approach.

  • ChE/MSE 557 Fall 2006 5Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Modeling Materials Phenomena

    • How do we describe (i.e. make a model for) a material or a phenomenon? – E.g.

    • flow of DNA through a membrane • interaction of a dendrimer with a cell wall • clay particles dispersed in a polymer • crystallization of a liquid within a nanopore • nanotubes aligned on polymer-templated microchip • DNA-tethered nanocrystal in solution • Nanocolloidal assembly • …

  • ChE/MSE 557 Fall 2006 6Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Modeling Materials Phenomena

    • There are many possible levels of description; choosing among them depends on your goals and on the available tools.

    • In building a model, we must make decisions, either explicitly or implicitly, about what is important for the questions we seek to answer.

  • ChE/MSE 557 Fall 2006 7Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Modeling Materials Phenomena

    specific

    numerical

    stochastic

    microscopic

    discrete

    qualitative

    general

    analytical

    deterministic

    macroscopic

    continuous

    quantitative

    No “best” model. Depends on the question, and on the investigator. Different standards for success.

  • ChE/MSE 557 Fall 2006 8Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Simulating Materials Phenomena

    • Choosing which simulation method to use depends on the level of description of the model, the phenomena we wish to study, and the questions we seek to answer.

    • Some of the simulation methods used to study soft matter are also used to study hard matter, and some are special to soft matter (usually those at the mesoscale).

    After choosing a model, choose a method.

  • ChE/MSE 557 Fall 2006 9Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Simulation of Soft Matter

    What are the challenges?

  • ChE/MSE 557 Fall 2006 10Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Computational Challenges of Soft Matter

    Soft materials are computationally challenging due to : • Wide range of length scales: Å - mm • Wide range of time scales: fs - years

    – Complex nature of individual molecules – Hierarchical, cooperative nature of structure and assembly – Formation from complex liquid state – Can be far from equilibrium – Often amorphous – Viscoelasticity -> complex response

    • Interfaces • Dissimilar materials

    Is “soft” special?

    Polymers, foams, emulsions, surfactants, liquid crystals, gels, DNA, colloids, proteins, connective tissue, membranes, cells, …

    No one (or two) methods will suffice!

  • ChE/MSE 557 Fall 2006 11Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Brief Overview

    Simulation methods for soft materials

  • ChE/MSE 557 Fall 2006 12Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Simulation Methods for Soft Materials Ti

    m e

    Sc al

    e (s

    ec )

    Length Scale

    pic o

    Angstroms nanometers microns mm

    Ab Initio

    metersfe mt

    o na

    no mi

    cr o

    mi lli

    se c Macroscale

    Simulation

    Electronic Structure - MO & DFT Ab initio MD Quantum MC

    Mesoscale Simulation Finite

    element

    Molecular Simulation

    Brownian Dynamics Lattice Boltzmann Cellular Automata DPD DDFTMolecular dynamics

    Monte Carlo

    CFD Mech

  • ChE/MSE 557 Fall 2006 13Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Ab initio methods

  • ChE/MSE 557 Fall 2006 14Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Molecular Dynamics for Soft Matter

    • EA/UA Atom MD E.g. Lubrication

    in nanoscale gaps For dodecane between mica - 6 orders increase in µ - 7 orders lower for

    transition to Newtonian flow

    • Coarse-grained MD E.g. nano-filled polymer melt – Molecular packing and dynamics near nanoparticle surface – Effect of np/polymer interactions on processing parameters

    Starr, Schroder, Glotzer, PRE 64, 021802-1, 2001

    S. T

    . C ui

    , C . M

    cC ab

    e, P

    . T . C

    um m

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    , H.

    D . C

    oc hr

    an , a

    nd S

    . G ra

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    , p re

    pr in

    t

    !

    ˙ "

  • ChE/MSE 557 Fall 2006 15Computational Nanoscience of Soft Materialssglotzer@umich.edu

    T = 7d N = 72

    T = 13d N = 132

    T = 7l N = 72

    T = 13l N = 132

    bacteriophage HK 97 Simulated Structure

    rhesus rotavirus Simulated Structure

    Murine Polyoma virus

    Simulated Structure

    Bursal disease virus

    Simulated Structure

    The Glotzer Group @ University of Michigan http://viperdb.scripps.edu

    Monte Carlo simulation

  • ChE/MSE 557 Fall 2006 16Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Brownian dynamics simulations

    Self-assembly of tethered nano building blocks

    Zhang, Horsch, Lamm, Glotzer, Nano Letters, 2003.

  • ChE/MSE 557 Fall 2006 17Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Dissipative Particle Dynamics

    Surfactant self-assembly on nanostructured surfaces

    length red,yellow = 4,7 red:yellow = 1:1

    length red,yellow = 4,4 red:yellow = 1:1

    Chetana Singh

  • ChE/MSE 557 Fall 2006 18Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Field Theoretic Methods for Soft Matter

    3-d Patterning at the Nanoscale Nanotemplating

    “Nanofillers”

    S.C. Glotzer, 1995

    B. P.

    L ee

    , J .F

    . D ou

    gl as

    , &

    S. C.

    G lo

    tz er

    , 1 99

    9

    B.P. Lee, J.F. Douglas, SCG 1998.

    - photonic devices - scaffolds for molecular electronics, tissue growth - high strength nanocomposites

  • ChE/MSE 557 Fall 2006 19Computational Nanoscience of Soft Materialssglotzer@umich.edu

    We’ll learn about strategies for bridging length and time scales

    Simulation Methods for Soft Materials Ti

    m e

    Sc al

    e (s

    ec )

    Length Scale

    pic o

    Angstroms nanometers microns mm

    Ab Initio

    metersfe mt

    o na

    no mi

    cr o

    mi lli

    se c Macroscale

    Simulation

    Electronic Structure - MO & DFT Ab initio MD Quantum MC

    Mesoscale Simulation Finite

    element

    Molecular Simulation

    Brownian Dynamics Lattice Boltzmann Cellular Automata DPD DDFTMolecular dynamics

    Monte Carlo

    CFD Mech

  • ChE/MSE 557 Fall 2006 20Computational Nanoscience of Soft Materialssglotzer@umich.edu

    Holy Grail: “In silico” nano-scale design

    From molecular processes to macroscopic properties

    Mesoscale

    Atomistic

    Macroscale

    Molecular/mesoscale

    Example: “Designed” polymer nanocomposite

    First principles

    • Seamless linking of nanoscale processes to macroscopic properties.