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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 22 - Ab-Initio Thermodynamics and Structure Prediction


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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