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Tags: computational science/engineering

Resources (21-40 of 71)

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

    25 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4090

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

    27 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4122

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

    19 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4067

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

    14 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4056

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

    14 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4054

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

    14 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4052

  7. Computational Nanoscience, Lecture 1: Introduction to Computational Nanoscience

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

    In this lecture, we present a historical overview of computational science. We describe modeling and simulation as forms of "theoretical experiments" and "experimental theory". We also discuss...

    http://nanohub.org/resources/4045

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

    13 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4039

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

    13 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4037

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

    13 Feb 2008 | Teaching Materials | 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...

    http://nanohub.org/resources/4035

  11. Computational Nanoscience, Lecture 3: Computing Physical Properties

    11 Feb 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin

    In this lecture, we'll cover how to choose initial conditions, and how to compute a number of important physical observables from the MD simulation. For example, temperature, pressure, diffusion...

    http://nanohub.org/resources/4028

  12. Computational Nanoscience, Lecture 2: Introduction to Molecular Dynamics

    30 Jan 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin

    In this lecture, we present and introduction to classical molecular dynamics. Approaches to integrating the equations of motion (Verlet and other) are discussed, along with practical...

    http://nanohub.org/resources/3940

  13. Computational Nanoscience, Homework Assignment 1: Averages and Statistical Uncertainty

    30 Jan 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin

    The purpose of this assignment is to explore statistical errors and data correlation. This assignment is to be completed following lectures 1 and 2 using the "Average" program in the Berkeley...

    http://nanohub.org/resources/3935

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