top of page

Multiscale AI for Clean Energy

Developing and ultilizing AI/ML-accelerated MD/KMC theoretical methods to bridge the gap between theoretical modeling and experimental practices in clean energy conversion, utilization, and storage.

download.jfif
image.png

About MACE LAB

At MACE LAB, we advance multiscale simulation methods by integrating artificial intelligence (AI), machine learning (ML), molecular dynamics (MD), coarse-grained modeling, and quantum chemistry calculations.​

Our research focuses on interface chemistry and surface engineering for next-generation clean energy materials. We investigate environment-responsive reaction networks, nanomaterial dynamics, and the rational design of functional materials—bridging theory and practice through intelligent computation.

Picture10_edited.jpg
Picture9.png

We are dedicated to fostering a research environment founded on fairness and integrity, strengthened by collaboration and mutual respect, and driven by a shared pursuit of excellence and meaningful impact.

Department of Chemistry, National University of Singapore, Singapore 117543

+65-94705136

Copyright © Xiaoyan Li research group 2025

bottom of page