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3.320 Atomistic Computer Modeling of Materials

3.320 Atomistic Computer Modeling of Materials (Spring 2005, MIT OCW). Instructors: Professor Gerbrand Ceder and Professor Nicola Marzari. This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. (from ocw.mit.edu)

Lecture 08 - Case Studies of DFT

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Lecture 01 - Introduction and Case Studies

Lecture 02 - Potentials, Supercells, Relaxation, Methodology

Lecture 03 - Potentials 2: Potentials for Organic Materials and Oxides

Lecture 05 - First Principles Energy Methods: The Many-Body Problem

Lecture 06 - First Principles Energy Methods: Hartree-Fock and DFT

Lecture 07 - Technical Aspects of Density Functional Theory

Lecture 08 - Case Studies of DFT

Lecture 09 - Advanced DFT: Success and Failure; DFT Applications and Performance

Lecture 11 - Finite Temperature: Review of Statistical Mechanics and Thermodynamics

Lecture 13 - Molecular Dynamics I

Lecture 14 - Molecular Dynamics II

Lecture 15 - Molecular Dynamics III: First Principles

Lecture 17 - Monte Carlo Simulations: Application to Lattice Models, Sampling Errors, Metastability

Lecture 18 - Monte Carlo Simulations II and Free Energies

Lecture 19 - Free Energies and Physical Coarse-Graining

Lecture 20 - Model Hamiltonians

Lecture 22 - Ab-Initio Thermodynamics and Structure Prediction

Lecture 23 - Accelerated Molecular Dynamics

Lecture 25 - Case Studies: High Pressure, Conclusions