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Teaching Materials (1-20 of 24)

1. Manual for Archimedes, the GNU Monte Carlo simulator

   Teaching Materials | 25 Jun 2012 | Contributor(s):: Jean Michel D Sellier

   Please, feel free to download the manual of Archimedes.Archimedes is the GNU package for semiconductor device simulations that has been released for the first time on 2005 under GPL. It has been created by Jean Michel D. Sellier who is, since then, the leader of the project and the main...

2. Test for Monte Carlo Learning Module

   Teaching Materials | 30 Jul 2011 | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

   this is a test for the MC Learning Module.

3. Monte Carlo and Path Integral Formulation

   Teaching Materials | 30 Jun 2011 | Contributor(s):: Dragica Vasileska

   This set of handwritten notes is part of the Semiconductor Transport class.

4. Single Particle and Ensemble Monte Carlo Method

   Teaching Materials | 30 Jun 2011 | Contributor(s):: Dragica Vasileska

   This set of handwritten notes is part of the Semiconductor Transport class.

5. Manual for the Generalized Bulk Monte Carlo Tool

   Teaching Materials | 24 Jun 2011 | Contributor(s):: Raghuraj Hathwar, Dragica Vasileska

   This manual describes the physics implemented behind the generalized bulk Monte Carlo tool.

6. Generalized Monte Carlo Presentation

   Teaching Materials | 20 Jun 2011 | Contributor(s):: Dragica Vasileska

   This presentation goes along with the Bulk Monte Carlo tool on the nanoHUB that calculates transients and steady-state velocity-field characteristics of arbitrary materials such as Si, Ge, GaAs, GaN, SiC, etc. The tool employs a non-parabolic bandstructure.

7. High Field Transport and the Monte Carlo Method for the Solution of the Boltzmann Transport Equation

   Teaching Materials | 23 Jul 2010 | Contributor(s):: Dragica Vasileska

   This set of slides first describes the path-integral solution of the BTE and then discusses in details the Monte Carlo Method for the Solution of the Boltzmann Transport Equation.

8. Atomistic Simulations of Reliability

   Teaching Materials | 06 Jul 2010 | Contributor(s):: Dragica Vasileska

   Discrete impurity effects in terms of their statistical variations in number and position in the inversion and depletion region of a MOSFET, as the gate length is aggressively scaled, have recently been researched as a major cause of reliability degradation observed in intra-die and die-to-die...

9. Bulk Monte Carlo: Implementation Details and Source Codes Download

   Teaching Materials | 01 Jun 2010 | Contributor(s):: Dragica Vasileska, Stephen M. Goodnick

   The Ensemble Monte Carlo technique has been used now for over 30 years as a numerical method to simulate nonequilibrium transport in semiconductor materials and devices, and has been the subject of numerous books and reviews. In application to transport problems, a random walk is generated to...

10. From Semi-Classical to Quantum Transport Modeling: Particle-Based Device Simulations

    Teaching Materials | 10 Aug 2009 | Contributor(s):: Dragica Vasileska

    This set of powerpoint slides series provides insight on what are the tools available for modeling devices that behave either classically or quantum-mechanically. An in-depth description is provided to the approaches with emphasis on the advantages and disadvantages of each approach. Conclusions...

11. Band Structure Lab: First-Time User Guide

    Teaching Materials | 15 Jun 2009 | Contributor(s):: Abhijeet Paul, Benjamin P Haley, Gerhard Klimeck

    This document provides useful information about Band Structure Lab. First-time users will find basic ideas about the physics behind the tool such as band formation, the Hamiltonian description, and other aspects. Additionally, we provide explanations of the input settings and the results of the...

12. Homework Assignment for Bulk Monte Carlo Lab: Velocity vs. Field for Arbitrary Crystallographic Orientations

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    Teaching Materials | 21 Aug 2008 | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

    User needs to calculate and compare to experiment the velocity field characteristics for electrons in Si for different crystalographic directions and 77K and 300K temperatures.

13. Homework Assignment for Bulk Monte Carlo Lab: Arbitrary Crystallographic Direction

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    Teaching Materials | 20 Aug 2008 | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

    This exercise teaches the users how the average carrier velocity, average carrier energy and vally occupation change with the application of the electric field in arbitrary crystalographic direction

14. Bulk Monte Carlo Code Described

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    Teaching Materials | 01 Jul 2008 | Contributor(s):: Dragica Vasileska

    In this tutorial we give implementation details for the bulk Monte Carlo code for calculating the electron drift velocity, velocity-field characteristics and average carrier energy in bulk GaAs materials. Identical concepts with minor details apply to the development of a bulk Monte Carlo code...

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

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    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...

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

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    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...

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

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    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...

18. Computational Nanoscience, Homework Assignment 4: Hard-Sphere Monte Carlo and Ising Model

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    Teaching Materials | 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) hard-sphere systems and (2) Ising model of the ferromagnetic-paramagnetic phase transition in two-dimensions. This assignment is to be completed following lecture 12 and using the "Hard Sphere Monte Carlo" and...

19. Computational Nanoscience, Lecture 10: Brief Review, Kinetic Monte Carlo, and Random Numbers

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    Teaching Materials | 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 vacancy-mediated diffusion...

20. Computational Nanoscience, Lecture 9: Hard-Sphere Monte Carlo In-Class Simulation

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    Teaching Materials | 19 Feb 2008 | Contributor(s):: Elif Ertekin, Jeffrey C Grossman

    In this lecture we carry out simulations in-class, 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 order-disorder phase transition, which we will explore with...