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Shu-Tian Liang

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#machine learning Preprint Oct 2026

ActMOF: Mapping Reticular Synthesis through Active Learning

Reticular chemistry allows metal-organic frameworks (MOFs) to be designed from their building units, yet their synthesis remains constrained by sparse experimental data, noisy crystallization outcomes, and the absence of benchmarks for comparing active-learning strategies. While data-driven approaches such as Bayesian...

Hong-Rui Sheng, Shu-Tian Liang, Reid Coyle et al. · 0 citations