Teaching
1. “Mathematics for Materials Science”: covering mathematical techniques necessary for understanding of materials science: mathematical description for the geometries of nanostructures; symmetry operations, group theory; fractal growth; ordinary and partial differential equations; fourier analysis and transformations; data fitting.
Synopsis
1) Mathematics for Plato polygon
2) Mathematics for cage and tube
3) Mathematics for helix and spiral structures
4) Fractal growth of materials
5) Symmetry and group theory
6) Eigenvalues and eigenvectors
7) Fourier analysis and transformations
8) Mathematics for data fitting
2.“Computational materials”
Advances in computing power and in computational methodology make materials simulation and design more and more powerful and indispensable. Simulation not only can provide essential understandings for existing experiments, but also can disclose and predict the structure and properties of new materials. Simulation, experiment and theory have become the three supporting pillars for modern science and technology. This course is designed to introduce some basic methods and theories for computational materials science.
Synopsis
1) Atomic potentials
2) Molecular dynamics simulation
3) Mote Carlo simulation
4) Simulated annealing
5) Molecular orbital theory
6) Plane wave pseudo-potential theory
7) Density functional theory
8) Ab initio molecular dynamics
