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NCN Nanomaterials: Simulation Tools for Education
02 Jun 2009 |
Please find an updated list of materials related simulation tools and resources at the Materials Science Education Group.
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SUGARCube - Netlist Input Tool
15 Jul 2008 | | Contributor(s):: Fengyuan Li, Jason Clark
Simulate the user input netlist by SUGAR2.0
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ECE 612 Lecture 21: On Becoming a True Technology Developer
02 Dec 2008 | | Contributor(s):: Mark Lundstrom
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Purdue School on High Performance and Parallel Computing
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...
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Thermoelectric Power Factor Calculator for Nanocrystalline Composites
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
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SUGARCube - Cantilever
01 May 2008 | | Contributor(s):: Fengyuan Li, Brandon Patterson, Jason Clark, yi zeng
Cantilever modeling and simulation with different loads
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Northwestern University Initiative for Teaching Nanoscience
12 Aug 2008 | | Contributor(s):: Baudilio Tejerina
This package allows users to study and analyze of molecular properties using various electronic structure methods.
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Virtual Kinetics of Materials Laboratory: Spinodal Decomposition 3D
04 Aug 2008 | | Contributor(s):: Michael Waters, R. Edwin Garcia, Alex Bartol
Simulates the Time-Dependent Segregation of Two Chemical Components
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Virtual Kinetics of Materials Laboratory : Spinodal Decomposition
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)
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Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I
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...
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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...
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Computational Nanoscience, Pop-Quiz
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
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Computational Nanoscience, Pop-Quiz Solutions
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
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Computational Nanoscience, Lecture 23: Modeling Morphological Evolution
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...
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Computational Nanoscience, Lecture 26: Life Beyond DFT -- Computational Methods for Electron Correlations, Excitations, and Tunneling Transport
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...
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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...
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Computational Nanoscience, Lecture 28: Wish-List, Reactions, and X-Rays.
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...
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Computational Nanoscience, Lecture 29: Verification, Validation, and Some Examples
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
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Examples for QuaMC 2D particle-based device Simulator Tool
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.
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Computational Nanoscience, Lecture 19: Band Structure and Some In-Class Simulation: DFT for Solids
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...