Overview of Computational Nanoscience: a UC Berkeley Course
01 Feb 2008 | Courses | Contributor(s): Jeffrey C Grossman, Elif Ertekin
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 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.
Excellence in Computer Simulation
19 Dec 2007 | Workshops | 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 past two-three decades have been substantial, but at the beginning of a new century, it is useful to reflect on what has been accomplished, on how computational science and engineering are evolving, and ...
Computational Nanoscience, Lecture 7: Monte Carlo Simulation Part I
15 Feb 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin
The purpose of this lecture is to introduce Monte Carlo methods as a form of stochastic simulation. Some introductory examples of Monte Carlo methods are given, and a basic introduction to relevant concepts in statistical mechanics is presented. Students will be introduced to the Metropolis approach to Monte Carlo simulation. Using Metropolis as an example, these lectures also introduce the comcepts of balance and detailed balance, and what "efficient sampling" means.
MIT Atomic Scale Modeling Toolkit
15 Jan 2008 | Tools | Contributor(s): daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley
Tools for Atomic Scale Modeling
Computational Nanoscience, Lecture 12: In-Class Simulation of Ising Model
28 Feb 2008 | Teaching Materials | 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 wall formation at low temperature, and the phase transition for the anti-ferromagnetic and ferromagnetic system.
University of California, Berkeley