AI for Science
Machine learning, agentic discovery, large language models, and generative AI for chemical and materials discovery.
AI for Reticular Chemistry Lab
We integrate computational chemistry, molecular simulation, and artificial intelligence to understand and design reticular and porous materials for sustainability.
Research interests
Porous Materials
Reticular materials including MOFs, COFs, ZIFs, and related crystals for sustainability.
Computational Chemistry
Machine-learned atomic potentials, molecular simulations, density functional theory, and computational screening.
Selected publications
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