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Author

Cheng Zeng

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#machine learning Preprint Sep 2026

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models are a promising approach for solving this problem, but the prevalence of polymorphism, coupled with large unit cells and complex packing geometry, makes the molecular CS...

T. Egg, Harry W. Sullivan, Maya M. Martirossyan et al. · 0 citations
#generative ai Sep 2026

COFFlow: Building-Block-Based Generative Modeling for Two-Dimensional Covalent Organic Framework Discovery

Two-dimensional covalent organic frameworks (2D COFs) are promising porous materials with vast yet largely unexplored design space arising from diverse building blocks (BBs) and crystal topologies. Efficient crystal structure prediction (CSP) and inverse design of 2D COFs therefore remain highly challenging. Here, we...

Yuan-Hui Pan, Yun-Rui Yan, Cheng Zeng et al. · 0 citations

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