Computational Materials Discovery Platform

Welcome

My lab aims at using computational and theoretical methods to develop new materials for applications in energy management, mass transport, information processing, and human health. My research area includes thermodynamics, statisical mechanics, computational chemistry, AI for science, polymer, interface, biomaterial, and nanotechnology. My team will develop multi-scale simulation models, machine learning/artificial intelligence (ML/AI) models, and theoretical methods to accelerate materials design. We will use High Performance Computers (HPCs) to help experimentalists solve materal develop problems. Through rigorous computation and interdisciplinary collaboration, my lab will have a broad impact in thermal physics, materials science, computational chemistry, physical chemistry, and data science.

Research Areas of Interest

Thermodynamics

Understand energy, temperature, entropy, and phase/state transition from molecular level to macroscopic scale. Develop theoretical methods to solve thermal physics problems.

Multi-scale simulations

Develop multi-scale computational methods, including ab initio, classical molecular dynamics (MD), coarse-grain (CG), Monte Carlo (MC), and hydrodynamic models.

ML/AI models

Integrate low-fidelity and high-quantity simulation dataset with high-fidelity and low-quantity experimental dataset to train ML/AI models, then apply physical rules to improve the accuracy.