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MSE 498 Lesson 14: MD
17 Mar 2015 | | Contributor(s):: Andrew Ferguson
This new course will give students hands-on experience with popular computational materials science and engineering software through a series of projects in: electronic structure calculation (e.g., VASP), molecular simulation (e.g., GROMACS), phase diagram modeling (e.g., Thermo-Calc), finite...
MSE 498 Lesson 15: MD
MSE 498 Lesson 16: FEM
MSE 498 Lesson 17: FEM
MSE 498 Lesson 18: CALPHAD
MSE 498 Lesson 19: CALPHAD
MSE 498 Lesson 1: CMSE
MSE 498 Lesson 2: bash
MSE 498 Lesson 3: bash
[Illinois] CNST 2012: Nanostructured Silicon Optical Materials as Multifunctional Cell Culture Substrates
02 Jun 2013 | | Contributor(s):: Kris Killian
Multiscale Manufacturing of Fractal Structures
28 Mar 2013 | | Contributor(s):: Charalabos (Haris) Doumanidis
This lecture overviews the philosophy and background of the presenter’s research group in thermomechanical materials processing and manufacturing process modeling and control by scanned distributed-parameter, dynamic adaptive techniques. It also elaborates on his current investigations in random...
Exascale Co-design for Materials in Extreme Environments: Heterogeneous Algorithms for Heterogeneous Architectures
30 May 2012 | | Contributor(s):: Timothy C. Germann
Computational materials scientists have been among the earliest and heaviest users of leadership-class supercomputers. The codes and algorithms which have been developed span a wide range of physical scales and have been useful not only for gaining scientific insight, but also as testbeds for...
Nanotribology, Nanomechanics and Materials Characterization Studies
08 Jun 2009 | | Contributor(s):: Bharat Bhushan
Fundamental nanotribological studies provide insight to molecular origins of interfacial phenomena including adhesion, friction, wear and lubrication. Friction and wear of lightly loaded micro/nano components are highly dependent on the surface interactions (few atomic layers). Nanotribological...
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...