
Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II
15 May 2008   Contributor(s):: Jeffrey C Grossman, Elif Ertekin
This is our second lecture in a series on Quantum Monte Carlo methods. We describe the Diffusion Monte Carlo approach here, in which the approximation to the solution is not restricted by choice of a functional form for the wavefunction. The DMC approach is explained, and the fixed node...

Computational Nanoscience, Lecture 27: Simulating Water and Examples in Computational Biology
16 May 2008   Contributor(s):: Elif Ertekin, Jeffrey C Grossman
In this lecture, we describe the challenges in simulating water and introduce both explicit and implicit approaches. We also briefly describe protein structure, the Levinthal paradox, and simulations of proteins and protein structure using First Principles approaches and Monte Carlo...

Molecular modeling of lipid bilayer edge and hybridMCMD method: Implementation and application
29 Apr 2008   Contributor(s):: Yong Jiang
Introduction to mixed lipid systems, Hybrid Monte Carlo and MD (atomistic) algorithm for mixed lipid systems

Practical Introduction to the BioMOCA Suite
23 Apr 2008   Contributor(s):: David Papke
In this presentation, I describe how to use the online BioMOCA Suite. I explain how to prepare the .pqr input protein structure from a .pdb structure. I then explain in detail how to use each of the four subtools in the BioMOCA Suite.I do not cover in detail how the BioMOCA code works. If you...

biomoca
30 May 2006   Contributor(s):: Reza Toghraee, Umberto Ravaioli
Ion channel simulator

Computational Nanoscience, Homework Assignment 4: HardSphere Monte Carlo and Ising Model
05 Mar 2008   Contributor(s):: Elif Ertekin, Jeffrey C Grossman
In this assignment, you will explore the use of Monte Carlo techniques to look at (1) hardsphere systems and (2) Ising model of the ferromagneticparamagnetic phase transition in twodimensions. This assignment is to be completed following lecture 12 and using the "Hard Sphere Monte Carlo" and...

Computational Nanoscience, Lecture 10: Brief Review, Kinetic Monte Carlo, and Random Numbers
25 Feb 2008   Contributor(s):: Elif Ertekin, Jeffrey C Grossman
We conclude our discussion of Monte Carlo methods with a brief review of the concepts covered in the three previous lectures. Then, the Kinetic Monte Carlo method is introduced, including discussions of Transition State Theory and basic KMC algorithms. A simulation of vacancymediated diffusion...

Computational Nanoscience, Lecture 9: HardSphere Monte Carlo InClass Simulation
19 Feb 2008   Contributor(s):: Elif Ertekin, Jeffrey C Grossman
In this lecture we carry out simulations inclass, with guidance from the instructors. We use the HSMC tool (within the nanoHUB simulation toolkit for this course). The hard sphere system is one of the simplest systems which exhibits an orderdisorder phase transition, which we will explore with...

Computational Nanoscience, Lecture 7: Monte Carlo Simulation Part I
15 Feb 2008   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...

Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II
14 Feb 2008   Contributor(s):: Elif Ertekin, Jeffrey C Grossman
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...

BioMOCA Suite
04 Feb 2008   Contributor(s):: David Papke, Reza Toghraee, Umberto Ravaioli, Ankit Raj
Simulates ion flow through a channel.

Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing
13 Feb 2008   Contributor(s):: Jeffrey C Grossman, Elif Ertekin
In this lecture, we discuss various methods for finding the ground state structure of a given system by minimizing its energy. Derivative and nonderivative methods are discussed, as well as the importance of the starting guess and how to find or generate good initial structures. We also briefly...

MIT AtomicScale Modeling Toolkit
15 Jan 2008   Contributor(s):: daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley
Tools for AtomicScale Modeling

QWalk Quantum Monte Carlo Tutorial
15 Jun 2007   Contributor(s):: Lucas Wagner, Jeffrey C Grossman, Jeffrey B. Neaton, Ian Michael Rousseau
An accurate method to calculate the many body ground state of electrons

Illinois Tools: MOCA
28 Mar 2007   Contributor(s):: Mohamed Mohamed, Umberto Ravaioli, Nahil Sobh, derrick kearney, Kyeonghyun Park
2D Fullband Monte Carlo (MOCA) Simulation for SOIBased Device Structures

QuaMC2D
13 Mar 2006   Contributor(s):: Shaikh S. Ahmed, Dragica Vasileska
Quantumcorrected MonteCarlo electron transport simulator for twodimensional MOSFET devices.

Materials Science on the Atomic Scale with the 3D Atom Probe
08 Nov 2006 
Some of the key goals of materials science and technology are to be able to design a material from first principles, to predict its behaviour, and also to optimise the processing route for its manufacture. In recent years, these goals have come closer to realisation, thanks in part to the...

demons
31 Oct 2006   Contributor(s):: , , Paul Dodd, M. A. Stettler, Xufeng Wang, Gerhard Klimeck
Improved program consists of DEMON and SDEMON

Homework for Monte Carlo Method: High field transport in Bulk Si
06 Jan 2006   Contributor(s):: Muhammad A. Alam
This homework assignment is part of ECE 656 "Electronic Transport in Semiconductors" (Purdue University). It contains 10 problems which lead students through the simulation of highfield transport in bulk silicon.

Review of Several Quantum Solvers and Applications
11 Jun 2004   Contributor(s):: Umberto Ravaioli
Review of Several Quantum Solvers and Applications