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Illinois PHYS 466, Lecture 13: Brownian Dynamics
08 Apr 2009 | Contributor(s):: David M. Ceperley
Brownian DynamicsLet’s explore the connection between Brownian motion and Metropolis Monte Carlo. Why? Connection with smart MC Introduce the idea of kinetic Monte Carlo Get rid of solvent degrees of freedom and have much longer time steps.Content: Local Markov process General Form of Evolution...
Illinois PHYS 466, Lecture 12: Random Walks
30 Mar 2009 | Contributor(s):: David M. Ceperley
Random WalksToday we will discuss Markov chains (random walks), detailed balance and transition rules. These methods were introduced by Metropolis et al. in 1953 who applied it to a hard sphere liquid. It is one of the most powerful and used algorithmsContent: Equation of State Calculations by...
Illinois PHYS 466, Lecture 11: Importance Sampling
20 Mar 2009 | Contributor(s):: David M. Ceperley
Importance samplingToday We will talk about the third option: Importance sampling and correlated samplingContent: Importance Sampling Finding Optimal p*(x) for Sampling Example of importance sampling What are allowed values of a? What does infinite variance look like? General Approach to...
Illinois PHYS 466, Lecture 10: Sampling
20 Mar 2009 | Contributor(s):: David M. Ceperley, Omar N Sobh
Fundamentals of Monte CarloWhat is Monte Carlo? Named at Los Alamos in 1940’s after the casino. Any method which uses (pseudo)random numbers> as an essential part of the algorithm. Stochastic - not deterministic! A method for doing highly dimensional integrals by sampling the integrand. Often a...
Illinois PHYS 466, Lecture 8: Temperature and Pressure Controls
03 Mar 2009 | Contributor(s):: David M. Ceperley
Temperature and Pressure ControlsContent: Constant Temperature MD Quench method Brownian dynamics/Anderson thermostat Nose-Hoover thermostat (FS 6.1.2) Nose-Hoover thermodynamics Effect of thermostat Comparison of Thermostats Constant pressure or constant volume Constant Pressure (FS 6.2)...
Illinois PHYS 466, Lecture 6: Scalar Properties and Static Correlations
Scalar Properties, Static Correlations and Order ParametersWhat do we get out of a simulation? Static properties: pressure, specific heat, etc. Density Pair correlations in real space and Fourier space Order parameters and broken symmetry: How to tell a liquid from a solid Dynamical properties...
Illinois PHYS 466, Lecture 7: Dynamical Correlations & Transport Coefficients
02 Mar 2009 | Contributor(s):: David M. Ceperley
Dynamical correlations and transport coefficientsDynamics is why we do molecular dynamics! Perturbation theory Linear-response theory Diffusion constants, velocity-velocity auto correlation fct. Transport coefficients Diffusion: Particle flux Viscosity: Stress tensor Heat transport: energy...
Illinois PHYS 466, Lecture 5: Interatomic Potentials
18 Feb 2009 | Contributor(s):: David M. Ceperley
Interatomic Potentials Before we can start a simulation, we need the model! Interaction between atoms and molecules is determined by quantum mechanics But we don’t know V(R)!Content: The electronic-structure problem Born-Oppenheimer (1927) Approximation Semi-empirical potentials Atom-Atom...
Illinois ECE 598EP Lecture 3.1 - Hot Chips: Electrons and Phonons
17 Feb 2009 | | Contributor(s):: Eric Pop, Omar N Sobh
Electrons and Phonons
Illinois Center for Cellular Mechanics: Discovery through the Computational Microscope
11 Feb 2009 | | Contributor(s):: Klaus Schulten
Computational MicroscopeAll-atom molecular dynamics simulations have become increasingly popular as a toolto investigate protein function and dynamics. However, researchers are usuallyconcerned about the short time scales covered by simulations, the apparentimpossibility to model large and...
Illinois PHYS 466, Lecture 4: Molecular Dynamics
05 Feb 2009 | | Contributor(s):: David M. Ceperley
Molecular Dynamics What to choose in an integrator The Verlet algorithm Boundary Conditions in Space and time Reading assignment: Frenkel and Smit Chapter 4 Content: Characteristics of simulations The Verlet Algorithm Higher Order Methods? Quote from Berendsen Long-term stability of Verlet...
Illinois ECE 598EP Lecture 1 - Hot Chips: Atoms to Heat Sinks
out of 5 stars
29 Jan 2009 | | Contributor(s):: Eric Pop
IntroductionContent: The Big Picture Another CPU without a Heat Sink Thermal Management Methods Impact on People and Environment Packaging cost IBM S/390 refrigeration and processor packaging Intel Itanium and Pentium 4packaging Graphics Cards Under/Overclocking Environment A More Detailed Look...
Illinois PHYS 466, Lecture 3: Basics of Statistical Mechanics
31 Jan 2009 | | Contributor(s):: David M. Ceperley
Basics of Statistical Mechanics Review of ensembles Microcanonical, canonical, Maxwell-Boltzmann Constant pressure, temperature, volume,… Thermodynamic limit Ergodicity (see online notes also) Reading assignment: Frenkel and Smit pgs. 1-22.Content: The Fundamentals according to Newton “Molecular...
Illinois MatSE 280 Introduction to Engineering Materials, Lecture 9: Mechanical Failures
09 Jan 2009 | | Contributor(s):: Duane Douglas Johnson, Omar N Sobh
Mechanical Failure: temperature, stress, cyclic and loading effectISSUES TO ADDRESS... How do cracks that lead to failure form? How is fracture resistance quantified? How do the fracture resistances of the different material classes compare? How do we estimate the stress to fracture? How do...
Illinois MatSE485/Phys466/CSE485 - Atomic-Scale Simulation
27 Jan 2009 | | Contributor(s):: David M. Ceperley
THE OBJECTIVE is to learn and apply fundamental techniques used in (primarily classical) simulations in order to help understand and predict properties of microscopic systems in materials science, physics, chemistry, and biology. THE EMPHASIS will be on connections between the simulation results...
Illinois PHYS 466, Lecture 1: Introduction
28 Jan 2009 | | Contributor(s):: David M. Ceperley
Introduction to Simulation Content: Why do simulations? Moore's law Two Simulation Modes Dirac, 1929 Challenges of Simulation: Physical and mathematical underpinnings Complexity Estimation of Computer Time and Size Challenges of Simulation: Multi-scale computational materials research Short...
DragonflyTV Nano – Using the Power of Television to Introduce Middle School Children to Nanotechnology
15 Jan 2009 | | Contributor(s):: Richard Hudson, Joan Freese, Angie Prindle, Lisa Regalla
DragonflyTV is a PBS science series for children, broadcast nationwide and on the internet. DragonflyTV models authentic science inquiry through its unique approach: In each episode, ordinary kids conduct their own inquiry-based investigations, modeling the inquiry process and communicating the...
Thermoelectric Power Factor Calculator for Superlattices
18 Oct 2008 | | Contributor(s):: Terence Musho, Greg Walker
Quantum Simulation of the Seebeck Coefficient and Electrical Conductivity in 1D Superlattice Structures using Non-Equilibrium Green's Functions
Illinois MatSE 280 Introduction to Engineering Materials, Lecture 7: Mechanical Properties
15 Dec 2008 | | Contributor(s):: Duane Douglas Johnson, Omar N Sobh
Mechanical PropertiesWhy Mechanical Properties? Need to design materials that will withstand applied load and in-service uses for ... Space exploration, Bridges for autos and people, skyscrapers, MEMS devices, Space elevator?Content: Stress and strain Elastic and Plastic Deformation of Metals...
Illinois MATSE 280 Introduction to Engineering Materials, Lecture 6: Diffusion in Solids
19 Nov 2008 | | Contributor(s):: Duane Douglas Johnson, Omar N Sobh
Diffusion in SolidsISSUES TO ADDRESS... How does diffusion occur? How can the rate of diffusion be predicted forsome simple cases? How does diffusion depend on structure and temperatureContent Diffusion- Steady and Non-Steady State Simple Diffusion Inter-diffusion Self-diffusion...