Link to Canvas
Links to lecture materials are below. Each lecture covers a big topic, and generally it takes several academic lectures to cover each of them.
Useful books related to the course are placed here
Lecture 1 – Basic introduction to quantum physics: reminder about de Broglie wave function, Max Born hypothesis, Heisenberg uncertainty principle, Schrödinger equation
Lecture 2 – Introduction to materials properties: Structure of materials, Drude model of metals, Hall effect, Thermal conductivity, Fermi-Dirac distribution, Sommerfeld theory
Lecture 3 – Quantum chemical methods: Density of electronic states, Bloch’s theorem, Hartree approximation, Hartree-Fock method, DFT, Kohn-Sham equations, Brillouin zone, Pseudopotentials
Lecture 3a – Spin-orbit coupling in DFT
Lecture 4 – Classical molecular dynamics: Born-Oppenheimer approximation, Molecular mechanics, Interatomic potentials, Force fields, ML potentials, Molecular dynamics, Monte-Carlo
Lecture 5 – Computational prediction of materials: How to predict materials, Crystal structure and properties, Idea of global optimization, Crystal structure prediction methods, Local optimization, USPEX
Lecture 6 – Mechanical properties of materials: Small deformation of solid state, Mechanical stresses, Hook’s law, Elastic constants, Elastic moduli, Stress-strain diagram, AI for hardness
Lecture 7 – AI and ML in materials science: General concepts of AI, Algorithms of AI, Examples where and how AI applied to solve general issues of computational materials science
Lecture 8 - Machine learning interatomic potentials: classical potentials vs. machine learning
Tutorials on Quantum ESPRESSO are placed here. Be aware! to complete metaGGA calculations one need to compile QE with libxc library, which is not a trivial issue.