Author

C. Rao

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Preprint Oct 2026

MOFFieldBench: A Machine Learning Benchmark for Continuous Electronic Fields in Metal-Organic Frameworks

Machine-learning models for metal-organic frameworks (MOFs) predominantly rely on atomic structures, whereas electron-density (ED) and electrostatic-potential (ESP) fields remain underexplored as scalable learning representations. These continuous fields encode complementary spatial and electronic information relevant...

Zhao-Lin Hu, He-He Fan, Chen-Hao Rao et al. · 0 citations

Preprint Jul 2026

Large language model agents accelerate inverse design of metal-organic frameworks for gas separation

LEMO Agent is presented, a large-language-model agent framework for closed-loop inverse design of gas-separation MOFs in MOFid space that enriches high-performing candidates, improves predicted separation performance, and maintains broad chemical and topological diversity.

Zhaolin Hu, Hehe Fan, Wangyihan Guo et al. · 0 citations