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You are here: ToolsBerkeley Computational Nanoscience Class ToolsAbout

Berkeley Computational Nanoscience Class Tools

By Daniel Richards1, Elif Ertekin1, Jeffrey C Grossman2, David Strubbe1

1. University of California, Berkeley; 2. Massachusetts Institute of Technology;

Tools for UC Berkeley Computational Nanoscience course, Spring 2009

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Version 3.5 - published on 19 Jun 2009

DOI: 10254/nanohub-r3842.52 cite this

This tool is closed source.

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Description

This toolkit complements the Berkeley Computational Nanoscience class lecture series.

This set of simulation tools has been developed for use with a course at U.C. Berkeley, taught by 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 have been updated throughout spring term of 2009. The following simulations are run by the tool:

  • Averages and Error Bars
  • Molecular Dynamics (Lennard-Jones)
  • Molecular Dynamics (Carbon Nanostructures)
  • 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 Strubbe (2008), "Berkeley Computational Nanoscience Class Tools," DOI: 10254/nanohub-r3842.52.

    BibTex | EndNote

Tags
  1. ab initio
  2. band structure
  3. computational chemistry
  4. computational materials
  5. computational science/engineering
  6. density functional theory
  7. molecular simulations
  8. Monte Carlo
  9. nanoelectronics
  10. nanomaterials
  11. NCN Supported
  12. NCN@Berkeley Supported
  13. quantum Monte Carlo

Supporting Documents

[ none ]

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