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Computational Nanoscience, Lecture 5: A Day of In-Class Simulation: MD of Carbon Nanostructures
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13 Feb 2008 | | 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 calculating the energy per atom of different fullerenes and nantubes, computing the Young's modulus of a...
Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing
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 importance of the starting guess and how to find or generate good initial structures. We also briefly...
Computational Nanoscience, Lecture 3: Computing Physical Properties
11 Feb 2008 | | 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 coefficient, and pair distribution function will be highlighted. We will also discuss briefly the use...
Overview of Computational Nanoscience: a UC Berkeley Course
01 Feb 2008 | | 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...
Computational Nanoscience, Lecture 2: Introduction to Molecular Dynamics
30 Jan 2008 | | 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 considerations such as choice of timestep. A brief discussion of interatomic potentials (the pair potential and...
Computational Nanoscience, Homework Assignment 1: Averages and Statistical Uncertainty
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 Computational Nanoscience Toolkit.University of California, Berkeley
MIT Atomic-Scale Modeling Toolkit
15 Jan 2008 | | Contributor(s):: daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley
Tools for Atomic-Scale Modeling
Opening Remarks: Excellence in Computer Simulation
03 Jan 2008 | | Contributor(s):: Mark Lundstrom
Opening remarks for the one-day forum, "Excellence in Computer Simulation," which brought together a broad set of experts to reflect on the future of computational science and engineering.
Excellence in Computer Simulation
19 Dec 2007 | | 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...