Tags: computational science/engineering

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  1. Purdue School on High Performance and Parallel Computing

    Workshops | 24 Nov 2008 | Contributor(s):: Alejandro Strachan, Faisal Saied

    The goal of this workshop is to provide training in the area of high performance scientific computing for graduate students and researchers interested in scientific computing. The School will address current hardware and software technologies and trends for parallel computing and their...

  2. Thermoelectric Power Factor Calculator for Nanocrystalline Composites

    Tools | 18 Oct 2008 | Contributor(s):: Terence Musho, Greg Walker

    Quantum Simulation of the Seebeck Coefficient and Electrical Conductivity in a 2D Nanocrystalline Composite Structure using Non-Equilibrium Green's Functions

  3. SUGARCube - Cantilever

    Tools | 01 May 2008 | Contributor(s):: Fengyuan Li, Brandon Patterson, Jason Clark, yi zeng

    Cantilever modeling and simulation with different loads

  4. Northwestern University Initiative for Teaching Nanoscience

    Tools | 12 Aug 2008 | Contributor(s):: Baudilio Tejerina

    This package allows users to study and analyze of molecular properties using various electronic structure methods.

  5. Virtual Kinetics of Materials Laboratory: Spinodal Decomposition 3D

    Tools | 04 Aug 2008 | Contributor(s):: Michael Waters, R. Edwin Garcia, Alex Bartol

    Simulates the Time-Dependent Segregation of Two Chemical Components

  6. Virtual Kinetics of Materials Laboratory : Spinodal Decomposition

    Tools | 29 Jul 2008 | Contributor(s):: Michael Waters, Alex Bartol, Edwin Garcia

    Applies the Classic Cahn-Hilliard Equation to Simulate the Chemical Segregation of Two Phases (2D)

  7. Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I

    Teaching Materials | 15 May 2008 | 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 the mean field approximation. We describe briefly the Slater-Jastrow expansion of the wavefunction, and...

  8. Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II

    Teaching Materials | 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...

  9. Computational Nanoscience, Pop-Quiz

    Teaching Materials | 15 May 2008 | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    This quiz summarizes the most important concepts which have covered in class so far related to Molecular Dynamics, Classical Monte Carlo Methods, and Quantum Mechanical Methods.University of California, Berkeley

  10. Computational Nanoscience, Pop-Quiz Solutions

    Teaching Materials | 15 May 2008 | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    The solutions to the pop-quiz are given in this handout.University of California, Berkeley

  11. Computational Nanoscience, Lecture 23: Modeling Morphological Evolution

    Teaching Materials | 15 May 2008 | 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, particle-size distributions, the Lifshitz-Slyozov-Wagner model, thin film growth modes (Layer-by-Layer, Island growth, and Stranski-Krastanov), and...

  12. Computational Nanoscience, Lecture 26: Life Beyond DFT -- Computational Methods for Electron Correlations, Excitations, and Tunneling Transport

    Teaching Materials | 16 May 2008 | 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 to the self-energy corrects the quasiparticle excitations energies predicted by Kohn-Sham DFT. For...

  13. Computational Nanoscience, Lecture 27: Simulating Water and Examples in Computational Biology

    Teaching Materials | 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...

  14. Computational Nanoscience, Lecture 28: Wish-List, Reactions, and X-Rays.

    Teaching Materials | 16 May 2008 | 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 chain-of-state methods such as the Nudged Elastic Band for determining energy barriers. The use of empirical, QM/MM methods are described. We...

  15. Computational Nanoscience, Lecture 29: Verification, Validation, and Some Examples

    Teaching Materials | 16 May 2008 | 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 concepts.University of California, Berkeley

  16. Examples for QuaMC 2D particle-based device Simulator Tool

    Online Presentations | 10 May 2008 | Contributor(s):: Dragica Vasileska, Shaikh S. Ahmed, Gerhard Klimeck

    We provide three examples that demonstrate the full capabilities of QuaMC 2D for alternative device technologies.

  17. Computational Nanoscience, Lecture 19: Band Structure and Some In-Class Simulation: DFT for Solids

    Teaching Materials | 30 Apr 2008 | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    In this class we briefly review band structures and then spend most of our class on in-class simulations. Here we use the DFT for molecules and solids (Siesta) course toolkit. We cover a variety of solids, optimizing structures, testing k-point convergence, computing cohesive energies, and...

  18. Computational Nanoscience, Lecture 18.5: A Little More, and Lots of Repetition, on Solids

    Teaching Materials | 30 Apr 2008 | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    Here we go over again some of the basics that one needs to know and understand in order to carry out electronic structure, atomic-scale calculations of solids.

  19. Computational Nanoscience, Lecture 16: More and Less than Hartree-Fock

    Teaching Materials | 30 Apr 2008 | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    In the lecture we discuss both techniques for going "beyond" Hartree-Fock in order to include correlation energy as well as techniques for capturing electronic structure effects while not having to solve the full Hartree-Fock equations (ie, semi-empirical methods). We also very briefly touch upon...

  20. Computational Nanoscience, Lecture 15: In-Class Simulations: Hartree-Fock

    Teaching Materials | 30 Apr 2008 | Contributor(s):: Jeffrey C Grossman, Elif Ertekin

    Using a range of examples, we study the effect of basis set on convergence, the Hartree-Fock accuracy compared to experiment, and explore a little bit of molecular chemistry.