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 classification 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.