Tags: computational materials

Resources (21-35 of 35)

  1. Computational Nanoscience, Lecture 12: In-Class Simulation of Ising Model

    28 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    This is a two part lecture in which we discuss the spin-spin correlation function for the the Ising model, correlation lengths, and critical slowing down. An in-class simulation of the 2D Ising Model is performed using the tool "Berkeley Computational Nanoscience Class Tools". We look at domain...

  2. Computational Nanoscience, Homework Assignment 4: Hard-Sphere Monte Carlo and Ising Model

    05 Mar 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    In this assignment, you will explore the use of Monte Carlo techniques to look at (1) hard-sphere systems and (2) Ising model of the ferromagnetic-paramagnetic phase transition in two-dimensions. This assignment is to be completed following lecture 12 and using the "Hard Sphere Monte Carlo" and...

  3. Computational Nanoscience, Lecture 10: Brief Review, Kinetic Monte Carlo, and Random Numbers

    25 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    We conclude our discussion of Monte Carlo methods with a brief review of the concepts covered in the three previous lectures. Then, the Kinetic Monte Carlo method is introduced, including discussions of Transition State Theory and basic KMC algorithms. A simulation of vacancy-mediated diffusion...

  4. Computational Nanoscience, Lecture 11: Phase Transitions and the Ising Model

    27 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    In this lecture, we present an introduction to simulations of phase transitions in materials. The use of Monte Carlo methods to model phase transitions is described, and the Ising Model is given as an example for modeling the ferromagnetic-paramagnetic transition. Some of the subtleties of...

  5. Computational Nanoscience, Lecture 9: Hard-Sphere Monte Carlo In-Class Simulation

    19 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    In this lecture we carry out simulations in-class, with guidance from the instructors. We use the HSMC tool (within the nanoHUB simulation toolkit for this course). The hard sphere system is one of the simplest systems which exhibits an order-disorder phase transition, which we will explore with...

  6. Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II

    14 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    In this lecture, we continue our discussion of Monte Carlo simulation. Examples from Hard Sphere Monte Carlo simulations based on the Metropolis algorithm and from Grand Canonical Monte Carlo simulations of fullerene growth on spherical surfaces are presented. A discussion of meaningful...

  7. Computational Nanoscience, Homework Assignment 3: Molecular Dynamics Simulation of Carbon Nanotubes

    14 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    The purpose of this assignment is to perform molecular dynamics simulations to calculate various properties of carbon nanotubes using LAMMPS and Tersoff potentials.This assignment is to be completed following lectures 5 and 6 using the "LAMMPS" program in the Berkeley Computational Nanoscience...

  8. Computational Nanoscience, Homework Assignment 2: Molecular Dynamics Simulation of a Lennard-Jones Liquid

    14 Feb 2008 | | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    The purpose of this assignment is to perform a full molecular dynamics simulation based on the Verlet algorithm to calculate various properties of a simple liquid, modeled as an ensemble of identical classical particles interacting via the Lennard-Jones potential.This assignment is to be...

  9. Computational Nanoscience, Lecture 6: Pair Distribution Function and More on Potentials

    13 Feb 2008 | | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    In this lecture we remind ourselves what a pair distribution function is, how to compute it, and why it is so important in simulations. Then, we revisit potentials and go into more detail including examples of typical functional forms, relative energy scales, and what to keep in mind when...

  10. Computational Nanoscience, Lecture 5: A Day of In-Class Simulation: MD of Carbon Nanostructures

    13 Feb 2008 | | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    In this lecture we carry out simulations in-class, with guidance from the instructors. We use the LAMMPS tool (within the nanoHUB simulation toolkit for this course). Examples include calculating the energy per atom of different fullerenes and nantubes, computing the Young's modulus of a...

  11. Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing

    13 Feb 2008 | | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    In this lecture, we discuss various methods for finding the ground state structure of a given system by minimizing its energy. Derivative and non-derivative methods are discussed, as well as the importance of the starting guess and how to find or generate good initial structures. We also briefly...

  12. Dynamics on the Nanoscale: Time-domain ab initio studies of quantum dots, carbon nanotubes and molecule-semiconductor interfaces

    31 Jan 2008 | | Contributor(s):: Oleg Prezhdo

    Device miniaturization requires an understanding of the dynamical response of materials on the nanometer scale. A great deal of experimental and theoretical work has been devoted to characterizing the excitation, charge, spin, and vibrational dynamics in a variety of novel materials, including...

  13. MIT Atomic-Scale Modeling Toolkit

    15 Jan 2008 | | Contributor(s):: daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley

    Tools for Atomic-Scale Modeling

  14. Session 4: Discussion

    20 Dec 2007 |

    Discussion led by Mark Allendorf, Sandia National Laboratory.

  15. Excellence in Computer Simulation

    19 Dec 2007 | | Contributor(s):: Mark Lundstrom, Jeffrey B. Neaton, Jeffrey C Grossman

    Computational science is frequently labeled as a third branch of science - equal in standing with theory and experiment, and computational engineering is now an essential component of technology development and manufacturing. The successes of computational science and engineering (CSE) over the...