Resources for Machine Learning in Materials
- Educational materials
- Modules and course plans for introductions to machine learning for materials scientists.
- ML curriculum
- Databases: Material’s property data sets and descriptors for easy exploration of machine learning.
The StructOpt app provides a general genetic algorithm based optimizer in python targeted at identifying stable atomic structures.
- MAST is an automated workflow manager and post-processing tool that focuses on diffusion and defect workflows using density functional theory. It interfaces primarily with the Vienna Ab-initio Simulation Package (VASP).
Diffusion Data App is a database of over 250 (and growing) impurity diffusion coefficients calculated with ab initio density functional theory. Includes hosts Mg, Al, Cu, Ni, Pd, Pt, and W.
MaterialsHUB is an online hub of applications for computational materials science research and education related to defects and diffusion. materialshub.org
AtomTouch is a 3D interactive mobile platform (e.g., phone, tablet) molecular simulation software tool for educational purposes.
- UW links: Project page, Online App, Source code on Github.
- IOS App – “AtomTouch” on Google play and iTunes
- Tool and educational material on BrainPOP