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Tags: computational materials

Resources (1-20 of 36)

  1. Application-driven Co-Design: Using Proxy Apps in the ASCR Materials Co-Design 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...

    http://nanohub.org/resources/14149

  2. Computational Nanoscience, Homework Assignment 2: Molecular Dynamics Simulation of a Lennard-Jones 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...

    http://nanohub.org/resources/4052

  3. 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...

    http://nanohub.org/resources/4054

  4. Computational Nanoscience, Homework Assignment 4: Hard-Sphere 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) hard-sphere systems and (2) Ising model of the ferromagnetic-paramagnetic phase transition in two-dimensions. ...

    http://nanohub.org/resources/4134

  5. 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...

    http://nanohub.org/resources/4090

  6. 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...

    http://nanohub.org/resources/4122

  7. Computational Nanoscience, Lecture 12: In-Class 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 spin-spin correlation function for the the Ising model, correlation lengths, and critical slowing down. An in-class simulation of the 2D Ising...

    http://nanohub.org/resources/4126

  8. Computational Nanoscience, Lecture 17: Tight-Binding, 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 Tight-Binding method to a simple system and then to introduce the concept of Density Functional Theory. The motivation to...

    http://nanohub.org/resources/4164

  9. Computational Nanoscience, Lecture 18: Density Functional Theory and some Solid Modeling

    21 Mar 2008 | Teaching Materials | Contributor(s): Elif Ertekin, Jeffrey C Grossman

    We continue our discussion of Density Functional Theory, and describe the most-often used approaches to describing the exchange-correlation in the system (LDA, GGA, and hybrid functionals). We...

    http://nanohub.org/resources/4166

  10. 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...

    http://nanohub.org/resources/4564

  11. 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...

    http://nanohub.org/resources/4566

  12. 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, particle-size distributions, the...

    http://nanohub.org/resources/4572

  13. 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...

    http://nanohub.org/resources/4574

  14. 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...

    http://nanohub.org/resources/4576

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

    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 chain-of-state methods such as the Nudged...

    http://nanohub.org/resources/4578

  16. 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...

    http://nanohub.org/resources/4580

  17. 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 non-derivative methods are discussed, as well as the...

    http://nanohub.org/resources/4035

  18. Computational Nanoscience, Lecture 5: A Day of In-Class Simulation: MD of Carbon Nanostructures

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

    In this lecture we carry out simulations in-class, with guidance from the instructors. We use the LAMMPS tool (within the nanoHUB simulation toolkit for this course). Examples include...

    http://nanohub.org/resources/4037

  19. 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...

    http://nanohub.org/resources/4039

  20. 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...

    http://nanohub.org/resources/4056

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