Prof. Gerbrand Ceder lectures on Monte Carlo Simulations: Application to Lattice Models, Sampling Errors, Metastability.

1. Introduction and Case Studies
2. Potentials, Supercells, and Methodology
3. Potentials
4. First Principles Energy Methods
5. First Principles Energy Methods II
6. Technical Aspects of Density Functional Theory
7. Case Studies of DFT
8. Advanced DFT: Success and Failure
9. Finite Temperature
10. Molecular Dynamics I
11. Molecular Dynamics II
12. Molecular Dynamics III: First Principles
13. Simulations: Application to Lattice Models
14. Monte Carlo Simulation II and Free Energies
15. Free Energies and Physical Coarse-Graining
16. Model Hamiltonions
17. Ab-Initio Thermodynamics and Structure Prediction
18. Accelerated Molecular Dynamics
19. Case Studies: High Pressure

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. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure approaches, molecular dynamics, and Monte Carlo.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5107 (Atomistic Computer Modeling of Materials).