Materials

Materials Science

Overview

Computational materials science, simulation, and property prediction.

Key Tools

• VASP: Density functional theory (DFT) calculations
• Gaussian: Quantum chemistry
• LAMMPS: Molecular dynamics
• Pymatgen: Python materials genomics
• ASE: Atomic simulation environment
• Materials Project API: Materials property database

Common Workflows

DFT Property Calculation

1. Structure optimization (VASP/Gaussian)
2. Electronic structure (band structure, DOS)
3. Mechanical properties (elastic constants)
4. Optical properties (dielectric function)
5. Thermodynamic properties (phonon, free energy)

Materials Screening

1. Query databases (Materials Project, AFLOW, OQMD)
2. Filter by target properties
3. DFT verification of candidates
4. Experimental validation

Machine Learning for Materials

• Crystal graph neural networks (CGCNN, MEGNet)
• Composition-based models (Magpie, Roost)
• Active learning for experimental design
• Transfer learning from large pre-trained models

Databases