Find information on common issues.
Ask questions and find answers from other users.
Suggest a new site feature or improvement.
Check on status of your tickets.
3 min Research Talk: AFM And EBSD Cross-Comparison Analysis Tool
31 Jan 2019 | | Contributor(s):: Andrew Martin Krawec
This talk describes an approach to analyzing the crystal structure using data collected from AFM and EBSD scans to build an accurate image of the crystal structure and orientation in the ceramic
3 min Research Talk: Analysis of Radiation Induced Segregation in Fe-Cr-Al Alloys
31 Jan 2019 | | Contributor(s):: Timothy Joe Pownell
This presentation gives an overview of the results and tool that were developed from data on Radiation Induced Segregation of the prospective cladding material Fe-Cr-Al.
3 min Research Talk: Predicting and Optimizing Solar Cell Performance with Material/Surface Characteristics
31 Jan 2019 | | Contributor(s):: Yiheng Zhu
Photovoltaic simulation tools can be utilized to predict device performance before fabrication and experimentation, streamline research processes, and interpret experimental results. Therefore, we developed ContourPV, which simulates various combinations of values of different device...
Application-driven Co-Design: Using Proxy Apps in the ASCR Materials Co-Design Center
31 May 2012 | | 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 specific models in between. In this talk, we will review this suite and the motifs used in each of the...
Computational Nanoscience, Homework Assignment 2: Molecular Dynamics Simulation of a Lennard-Jones Liquid
out of 5 stars
14 Feb 2008 | | 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 identical classical particles interacting via the Lennard-Jones potential.This assignment is to be...
Computational Nanoscience, Homework Assignment 3: Molecular Dynamics Simulation of Carbon Nanotubes
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 completed following lectures 5 and 6 using the "LAMMPS" program in the Berkeley Computational Nanoscience...
Computational Nanoscience, Homework Assignment 4: Hard-Sphere Monte Carlo and Ising Model
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...
Computational Nanoscience, Lecture 10: Brief Review, Kinetic Monte Carlo, and Random Numbers
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...
Computational Nanoscience, Lecture 11: Phase Transitions and the Ising Model
27 Feb 2008 | | 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 as an example for modeling the ferromagnetic-paramagnetic transition. Some of the subtleties of...
Computational Nanoscience, Lecture 12: In-Class Simulation of Ising Model
28 Feb 2008 | | 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 Model is performed using the tool "Berkeley Computational Nanoscience Class Tools". We look at domain...
Computational Nanoscience, Lecture 17: Tight-Binding, and Moving Towards Density Functional Theory
21 Mar 2008 | | 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 mapping from a wavefunction to a density-based description of atomic systems is provided, and the necessary...
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...
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...
Computational Nanoscience, Lecture 23: Modeling Morphological Evolution
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...
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...
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...
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...
Computational Nanoscience, Lecture 29: Verification, Validation, and Some Examples
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
Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing
13 Feb 2008 | | 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 importance of the starting guess and how to find or generate good initial structures. We also briefly...
Computational Nanoscience, Lecture 5: A Day of In-Class Simulation: MD of Carbon Nanostructures
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 calculating the energy per atom of different fullerenes and nantubes, computing the Young's modulus of a nanotube...