Author

Dong Hyeon Mok

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Preprint Jul 2026

CatRetriever: Contrastive Representation Learning for Slab-to-Bulk Retrieval in Generative Catalyst Discovery

CatRetriever provides a scalable route for connecting catalyst generative models with physically plausible and adsorption energy compatible bulk catalyst discovery, and is extended into an adsorption energy targeted bulk discovery pipeline that combines bulk retrieval, generative search space expansion, and adsorption...

Jungho Oh, Woosung Kim, Dong Hyeon Mok et al. · 0 citations

Preprint Jul 2026

Symbolic Predicate-Guided Language Agents for Inverse Design of Perovskite Oxides

This work introduces a domain specific language (DSL)-guided strategy to improve the reasoning and design capability of LLM agents by translating natural language design rules into symbolic predicates encoded in a predefined chemistry DSL, and developed a multi-agent materials design framework.

Dong Hyeon Mok, Seoin Back, Victor Fung et al. · 0 citations

Preprint Jul 2026

Catalyst Diffusion Transformer: Generative Inverse Design of Heterogeneous Catalysts

CatDiT is presented, a unified framework for inverse catalyst design that generates valid and novel structures ranging from intermetallic alloys to oxide surfaces and establishes CatDiT as a practical and scalable approach for property-directed catalyst inverse design and targeted catalyst generation.

Hayoung Doo, Dong Hyeon Mok, S. Back et al. · 0 citations