A hybrid MOF screening workflow combining UFF and the PFP machine-learned potential, validated against DFT, identifies seven promising MOFs for humidity-tolerant ethylene capture.
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Towards Accurate and Scalable High-throughput MOF Adsorption Screening: Merging Classical Force Fields and Universal Machine Learned Interatomic Potentials
A hybrid MOF screening workflow combining UFF and the PFP machine-learned potential, validated against DFT, identifies seven promising MOFs for humidity-tolerant ethylene capture.