Projects

Machine learning applications in materials science

Machine learning is recently considered as a powerful tool for deciphering complex physics of materials science. We've employed this method to predict the effective charge in electromigration effect. Our paper is recommended by Citrine Informatics! We are also working on Sn-based solder design, high entropy alloy (HEA) design, etc by using this method.