Strain engineering guided by machine learning
MRS Bulletin Materials News Podcast
Omar Fabián of MRS Bulletin interviews Ju Li of Massachusetts Institute of Technology about applying machine learning to elastic strain engineering of semiconductor materials at the nanoscale. The research team presents a framework for guiding strain engineering whereby materials properties and performance can be designed. Read the article in Proceedings of the National Academy of Sciences.