Atomistic View of Materials: Modeling & Simulation
An introduction to the fundamental physics required to describe materials at the molecular level. Course will include modeling and simulations.
In “Atomistic View of Materials: Modeling & Simulation” students will be introduced to the fundamental physics required to describe materials in terms of electrons and atoms, learn how these processes relate to macroscopic behavior and become familiar with advanced modeling and simulation techniques that enable quantitative predictions.
The course will make extensive use of cloud computing using nanoHUB.org as well as its features for collaboration and publishing. Students will perform ab initio calculations using density functional theory and other advanced techniques as well as molecular dynamics simulations.
- The quantum mechanics of bonding and electronic structure
- Atoms, molecules and crystals
- Electronic structure calculations
- Hartree-Fock & post-Hartree-Fock methods
- Density functional theory
- Beyond density functional theory
- Response function predictions and electronic structure for molecules, crystals and hybrid materials
- Classical and statistical mechanics
- Hamilton’s formalism of classical mechanics
- Normal modes and phonons
- Statistical mechanics (classical, Bose-Einstein, and Fermi-Dirac)
- Molecular dynamics simulations
- Interatomic potentials for various classes of materials (e.g. embedded atom model, ReaxFF)
- Computing the thermo-mechanical response of materials
- Kinetic theory and Boltzmann equation
- Dynamics with Implicit Degrees of Freedom
- Coarse grained simulations of molecular materials
- Two temperature model and electronic thermal transport
Atomistic simulations of electrochemical reactions
By the end of the course, students are expected to be able to i) design, perform and analyze computer experiments using electronic and atomistic simulation techniques appropriate for the problem at hand, ii) be able to extract materials properties from the simulations; iii) recognize the approximations and estimate the level of accuracy to be expected from each modeling technique, and iv) be able to critically read the current scientific literature on computational modeling and simulation of materials.