Machine Learning for Defect Analysis in Materials Simulations
- Construction of Feature Vectors from Materials Structure Data
- Support Vector Machine for defect classification
- Greater than 99% accuracy in clasification of point and extended defects
The python-based machine learning module identifies and classifies different point and extended defects in crystal structure data generated by atomistic simulations, by learning information about local atomic structure.
Published on December 9th, 2018
Last updated on April 8th, 2021