What is the role of simulation in nanoscience research?

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1 ChE/MSE 557 Intro part 2 What is the role of simulation in nanoscience research? 1

2 Opportunities for Simulation Simulation Simulation complements both experiment and theory. Extends window of observation Helps interpret experimental results Provides tests of new theories and predictions for experiment 2

3 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! 3

4 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. 4

5 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 5

6 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. 6

7 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. 7

8 Simulating Materials Phenomena After choosing a model, choose a method. 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). 8

9 Simulation of Soft Matter What are the challenges? 9

Computational Challenges of Soft Matter Polymers, foams, emulsions, surfactants, liquid crystals, gels, DNA, colloids, proteins, connective tissue, membranes, cells, Is soft special?

10 Computational Challenges of Soft Matter Polymers, foams, emulsions, surfactants, liquid crystals, gels, DNA, colloids, proteins, connective tissue, membranes, cells, Is soft special? 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 No one (or two) methods will suffice! 10

11 Brief Overview Simulation methods for soft materials 11

12 Simulation Methods for Soft Materials Time Scale (sec) sec milli micro nano pico femto Electronic Structure - MO & DFT Ab initio MD Quantum MC Ab Initio Angstroms nanometers microns mm Molecular Simulation Length Scale Mesoscale Simulation Molecular dynamics Monte Carlo Macroscale Simulation CFD Mech Finite element Brownian Dynamics Lattice Boltzmann Cellular Automata DPD DDFT meters 12

13 Ab initio methods 13

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 S. T. Cui, C.

14 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 S. T. Cui, C. McCabe, P. T. Cummings, H. D. Cochran, and S. Granick, preprint 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, ,

15 Monte Carlo simulation bacteriophage HK 97 Simulated Structure T = 7l N = 72 T = 7d N = 72 rhesus rotavirus T = 13l N = 132 Simulated Structure T = 13d N = 132 Murine Polyoma Simulated Structure virus Bursal disease virus Simulated Structure Nanoscience Soft Materials The Computational Glotzer University of Michigan ChE/MSE 557 Fall

16 Brownian dynamics simulations Self-assembly of tethered nano building blocks Zhang, Horsch, Lamm, Glotzer, Nano Letters, ChE/MSE 557 Fall

17 Dissipative Particle Dynamics Surfactant self-assembly on nanostructured surfaces length red,yellow = 4,4 red:yellow = 1:1 length red,yellow = 4,7 red:yellow = 1:1 Chetana Singh ChE/MSE 557 Fall

C. Glotzer, 1999 S.C. Glotzer, 1995 - photonic devices - scaffolds for

18 Field Theoretic Methods for Soft Matter 3-d Patterning at the Nanoscale Nanotemplating B.P. Lee, J.F. Douglas, SCG Nanofillers B.P. Lee, J.F. Douglas, & S.C. Glotzer, 1999 S.C. Glotzer, photonic devices - scaffolds for molecular electronics, tissue growth - high strength nanocomposites 18

19 Simulation Methods for Soft Materials Time Scale (sec) sec milli micro nano pico femto We ll learn about strategies for bridging length and time scales Electronic Structure - MO & DFT Ab initio MD Quantum MC Ab Initio Angstroms nanometers microns mm Molecular Simulation Length Scale Mesoscale Simulation Molecular dynamics Monte Carlo Macroscale Simulation CFD Mech Finite element Brownian Dynamics Lattice Boltzmann Cellular Automata DPD DDFT meters 19

Holy Grail: In silico nano-scale design From

principles Atomistic Molecular/mesoscale

20 Holy Grail: In silico nano-scale design From molecular processes to macroscopic properties Mesoscale Macroscale Example: Designed polymer nanocomposite First principles Atomistic Molecular/mesoscale Seamless linking of nanoscale processes to macroscopic properties. 20

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012 K. Kremer Max Planck Institute for Polymer Research, Mainz Overview Simulations, general considerations