The main research direction of this laboratory is to use various computational methods (including Monte Carlo methods, molecular dynamics and quantum chemistry) and machine learning approaches to explore materials properties and to design new materials. The materials we study includes:

1. Two-dimensional materials for energy-related applications such as thermoelectric application or li-ion batteries.

2. Study the adsorption properties of porous materials including improving methods for determing their surface area and pore size distribution.

3. Applying machine learning methods to build predictive models to determine key elements of alloy corrosion resistance.