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Overview of Computational Nanoscience: a UC Berkeley Course

Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II

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Last 12 Months: updated 01 Oct, 2008
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Avg. Review: 5.0 out of 5 stars
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Contributor(s) Elif Ertekin, Jeffrey C Grossman
University of California, Berkeley
Abstract

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 statistics, result interpretation, and error analysis is presented as well.

Credits Nanoscale Science and Engineering C242/Physics C203
University of California, Berkeley
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  • Ertekin, Elif; Grossman, Jeffrey C (2008), "Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II," http://www.nanohub.org/resources/4056/.

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Date posted 15 Feb, 2008
Type Teaching Materials
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  1. 5.0 out of 5 stars 

    Posted on 10 March, 2008 by Anonymous

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  • 9.6 Ranking Courses Part of: Overview of Computational Nanoscience: a UC Berkeley Course

    Overview of Computational Nanoscience: a UC Berkeley Course

    Type Courses
    Contributor(s) Jeffrey C Grossman, Elif Ertekin
    Date 01 Feb, 2008
    Avg. Rating 5.0 out of 5 stars  (4)
    Rate this

    This course will provide students with the fundamentals of computational problem-solving techniques that are used to understand and predict properties of nanoscale systems. Emphasis will be placed on how to use simulations effectively, intelligently, and cohesively to predict properties that occur …

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