Catalyst Intelligence for Sustainable Chemical Engineering

Seokhyun Choung | Currently Postdoc at SNU RIAM.
Working on Building Catalyst Intelligence for next-generation catalyst discovery, to accelerate the transition to sustainable chemistry.

Core Research Areas

"It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong." - Richard Feynman

Catalyst Discovery

Active learning accelerates materials screening.

Multiscale Simulation

Graph neural networks enable atomic to nanoscale modeling. [Chem. Eng. J. 2024]

Experimental Realization

Theory-guided synthesis validates computational predictions. [Angew. Chem. 2025]

Selected Publications

(17+ peer-reviewed papers)

Rise of machine learning potentials in heterogeneous catalysis: Developments, applications, and prospects

Seokhyun Choung†, Wongyu Park†, Jinuk Moon†, Jeong Woo Han*

Chemical Engineering Journal 494 (2024) 152757

Accelerating Li-based battery design by computationally engineering materials

Sandip Maiti†, Matthew T. Curnan†, Kakali Maiti†, Seokhyun Choung, Jeong Woo Han*

Chem 9 (2023) 3415-3460

Highly Durable Rh Single Atom Catalyst Modulated by Surface Defects on Fe-Ce Oxide Solid Solution

Gunjoo Kim†, Seokhyun Choung†, Jae-eon Hwang, Yunji Choi, Seungeun Kim, Dongjae Shin, Jeong Woo Han*, Hyunjoo Lee*

Angewandte Chemie International Edition 64 (2025) e202421218

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