
Applicationdriven CoDesign: Using Proxy Apps in the ASCR Materials CoDesign Center
31 May 2012  Online Presentations  Contributor(s): Jim Belak
Computational materials science is performed with a suite of applications that span the quantum mechanics of interatomic bonding to the continuum mechanics of engineering problems and phenomenon...
https://nanohub.org/resources/14149

Christopher Nixon
Christopher Nixon is currently an undergraduate student at the University of Illinois at UrbanaChampaign majoring in Sociocultural Anthropology, with a minor in Informatics. He was formerly a...
https://nanohub.org/members/28503

Computational Nanoscience, Homework Assignment 2: Molecular Dynamics Simulation of a LennardJones Liquid
14 Feb 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
The purpose of this assignment is to perform a full molecular dynamics simulation based on the Verlet algorithm to calculate various properties of a simple liquid, modeled as an ensemble of...
https://nanohub.org/resources/4052

Computational Nanoscience, Homework Assignment 3: Molecular Dynamics Simulation of Carbon Nanotubes
14 Feb 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
The purpose of this assignment is to perform molecular dynamics simulations to calculate various properties of carbon nanotubes using LAMMPS and Tersoff potentials.
This assignment is to be...
https://nanohub.org/resources/4054

Computational Nanoscience, Homework Assignment 4: HardSphere Monte Carlo and Ising Model
05 Mar 2008  Teaching Materials  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. ...
https://nanohub.org/resources/4134

Computational Nanoscience, Lecture 10: Brief Review, Kinetic Monte Carlo, and Random Numbers
25 Feb 2008  Teaching Materials  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...
https://nanohub.org/resources/4090

Computational Nanoscience, Lecture 11: Phase Transitions and the Ising Model
27 Feb 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
In this lecture, we present an introduction to simulations of phase transitions in materials. The use of Monte Carlo methods to model phase transitions is described, and the Ising Model is given...
https://nanohub.org/resources/4122

Computational Nanoscience, Lecture 12: InClass 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 spinspin correlation function for the the Ising model, correlation lengths, and critical slowing down. An inclass simulation of the 2D Ising...
https://nanohub.org/resources/4126

Computational Nanoscience, Lecture 17: TightBinding, and Moving Towards Density Functional Theory
21 Mar 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
The purpose of this lecture is to illustrate the application of the TightBinding method to a simple system and then to introduce the concept of Density Functional Theory. The motivation to...
https://nanohub.org/resources/4164

Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I
15 May 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
This lecture provides and introduction to Quantum Monte Carlo methods. We review the concept of electron correlation and introduce Variational Monte Carlo methods as an approach to going beyond...
https://nanohub.org/resources/4564

Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II
15 May 2008  Teaching Materials  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...
https://nanohub.org/resources/4566

Computational Nanoscience, Lecture 23: Modeling Morphological Evolution
15 May 2008  Teaching Materials  Contributor(s): Elif Ertekin, Jeffrey C Grossman
In this lecture, we present an introduction to modeling the morphological evolution of materials systems. We introduce concepts of coarsening, particlesize distributions, the...
https://nanohub.org/resources/4572

Computational Nanoscience, Lecture 26: Life Beyond DFT  Computational Methods for Electron Correlations, Excitations, and Tunneling Transport
16 May 2008  Teaching Materials  Contributor(s): Jeffrey B. Neaton
In this lecture, we provide a brief introduction to "beyond DFT" methods for studying excited state properties, optical properties, and transport properties. We discuss how the GW approximation...
https://nanohub.org/resources/4574

Computational Nanoscience, Lecture 27: Simulating Water and Examples in Computational Biology
16 May 2008  Teaching Materials  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...
https://nanohub.org/resources/4576

Computational Nanoscience, Lecture 28: WishList, Reactions, and XRays.
16 May 2008  Teaching Materials  Contributor(s): Jeffrey C Grossman, Elif Ertekin
After a brief interlude for class feedback on the course content and suggestions for next semester, we turn to modeling chemical reactions. We describe chainofstate methods such as the Nudged...
https://nanohub.org/resources/4578

Computational Nanoscience, Lecture 29: Verification, Validation, and Some Examples
16 May 2008  Teaching Materials  Contributor(s): Jeffrey C Grossman, Elif Ertekin
We conclude our course with a lecture of verification, and validation. We describe what each of these terms means, and provide a few recent examples of nanoscale simulation in terms of these...
https://nanohub.org/resources/4580

Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing
13 Feb 2008  Teaching Materials  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...
https://nanohub.org/resources/4035

Computational Nanoscience, Lecture 5: A Day of InClass Simulation: MD of Carbon Nanostructures
13 Feb 2008  Teaching Materials  Contributor(s): Jeffrey C Grossman, Elif Ertekin
In this lecture we carry out simulations inclass, with guidance from the instructors. We use the LAMMPS tool (within the nanoHUB simulation toolkit for this course). Examples include...
https://nanohub.org/resources/4037

Computational Nanoscience, Lecture 6: Pair Distribution Function and More on Potentials
13 Feb 2008  Teaching Materials  Contributor(s): Jeffrey C Grossman, Elif Ertekin
In this lecture we remind ourselves what a pair distribution function is, how to compute it, and why it is so important in simulations. Then, we revisit potentials and go into more detail...
https://nanohub.org/resources/4039

Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II
14 Feb 2008  Teaching Materials  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...
https://nanohub.org/resources/4056