Berkeley Computational Nanoscience Class Tools

Tools for UC Berkeley Computational Nanoscience course, Spring 2009

Launch Tool

This tool version is unpublished and cannot be run. If you would like to have this version staged, you can put a request through HUB Support.

Archive Version 1.94
Published on 10 Feb 2009, unpublished on 13 Feb 2009 All versions

doi:10.4231/D3ZP3W04J cite this

This tool is closed source.

Category

Tools

Published on

Abstract

This toolkit complements the Berkeley Computational Nanoscience class lecture series. This set of simulation tools has been developed for use with a course at [http://mint.physics.berkeley.edu/compnano/Home.html U.C. Berkeley], taught by [http://mint.physics.berkeley.edu/CNG/JeffG.html Jeffrey Grossman] with TA David Strubbe, which provides students with the fundamentals of computational problem-solving techniques that are used to understand and predict properties of nanoscale systems. Emphasis is placed on how to use simulations effectively, intelligently, and cohesively to predict properties that occur at the nanoscale for real systems. The course is designed to present a broad overview of computational nanoscience and is therefore suitable for both experimental and theoretical researchers. These tools will continue to be updated throughout the Spring term of 2009. The following simulations are run by the tool: * Averages and Error Bars * Molecular Dynamics (Lennard-Jones) * Molecular Dynamics (LAMMPS) * Monte Carlo (Hard Sphere) * Monte Carlo (Ising Model) * Quantum Chemistry (GAMESS) * Density Functional Theory (Siesta) * Quantum Monte Carlo (QWalk) Any questions, comments, difficulties should be directed to David or Jeff.

Credits

Development Team: David Strubbe, Daniel Richards, Elif Ertekin, Jeff Grossman.

Cite this work

Researchers should cite this work as follows:

  • daniel richards, Elif Ertekin, Jeffrey C Grossman, David A Strubbe (2023), "Berkeley Computational Nanoscience Class Tools," https://nanohub.org/resources/ucb_compnano. (DOI: 10.4231/D3ZP3W04J).

    BibTex | EndNote

Tags

  1. ab initio
  2. atomistic modeling and simulation
  3. band structure
  4. chemistry
  5. computational chemistry
  6. computational materials science
  7. computational science/engineering
  8. density functional theory (DFT)
  9. GAMESS
  10. ising model
  11. LAMMPS
  12. Lennard-Jones potential
  13. materials science
  14. MIT Atomic-Scale Modeling Toolkit
  15. molecular dynamics (MD)
  16. molecular simulations
  17. Monte Carlo
  18. nanoelectronics
  19. nanomaterials
  20. NCN@Berkeley Supported
  21. NCN Group - Materials Science
  22. quantum chemistry
  23. Quantum ESPRESSO
  24. quantum Monte Carlo
  25. QWalk
  26. SIESTA