We combine molecular simulation, molecular thermodynamics, and artificial intelligence (AI) to connect physical & chemical phenomena at the atomistic scale with macroscopic performance in energy and environmental applications.
We build and deploy high-throughput digital workflows (e.g., CoRE MOF Tools, AIM) to curate, screen and evaluate thousands of nanoporous materials, creating digital twins for accurate and rapid performance prediction.
We build foundational platforms like CoRE MOF DB, PACMAN, MOFClassifier and GWP-estimator to enable autonomous discovery of next-generation materials and chemical systems.
We investigate the fundamentals of adsorption (e.g., BET analysis), diffusion, and reaction dynamics to design and understand materials and chemicals for carbon capture, conversion and energy storage.
Latest News & Highlights
2025/12 Guobin (구오빈 자오) joined MACE group (PI: Xiaoyan Li) in the Department of Chemistry at the National University of Singapore as a Postdoc.
2025/11 Muhammad (하산 무하마드), Sunghyun (윤성현), and Yu (첸유)'s paper was published online in Computer Physics Communications
2025/11 Changdon (신창돈) and Sunghyun (윤성현)'s paper was published online in Molecular Systems Design & Engineering
2025/10 Prof. Chung quoted in the ChemistryWorld article.
2025/10 Yu (첸유) and Guobin (구오빈 자오)'s paper was published online in Langmuir.
2025/08 Sunghyun (윤성현), Guobin (구오빈 자오), and Yeji (이예지)'s paper was published online in Separation and Purification Technology
2025/08 Guobin (구오빈 자오), Pengyu (팡유 자오)'s paper on MOFClassifier was published online in the Journal of the American Chemical Society
2025/05 Guobin (구오빈 자오), Sunghyun (윤성현), and Haewon (김해원)'s paper on CoRE MOF DB was published online in Matter
2025/02 Sunghyun (윤성현)'s paper on techno-economic analysis of boil-off gas treatment using MOF was published in Chemical Engineering Journal