Research Topics

Alloy Design

Alloys are commonly used in daily life. We use experimental and modeling approaches to design new alloys for specific applications. Our designed alloys include low-temperature solder, high-temperature solder, aluminum alloy, ironmaking process, zinc-based alloys, etc.

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.

Electric current-induced effect

Electric current is found to form voids and hillocks, as well as the polarity effect. It is also found to induce the alloy supersaturation effect, the non-polarity effect, lattice deformation, electrorecrystallization, and grain rotation. These interesting phenomena inevitably has increased the charisma of electric current in the application of altering material microstructures. This project is dedicated to understand the fundamental of physical metallurgy under electric current and therefore extend these knowledge in the real application.