CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening

2025/05/05 by Guobin Zhao, Logan M. Brabson, Saumil Chheda +23 · 1 voice · 8 citations
Chemistry · Materials Science · #Metal-Organic Frameworks: Synthesis and Applications #Machine Learning in Materials Science #X-ray Diffraction in Crystallography

paper · doi:10.1016/j.matt.2025.102140

Citations

• Configurational bias Monte Carlo: a new sampling scheme for flexible chains
• Vapor–liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen

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• Materials for thermochemical energy storage and conversion: attributes for low-temperature applications
• MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling
• Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture

Discussions

• The latest CoRE MOF database version is out! A curated experimental MOF database with machine-learned properties for integrated material-process screening, published in @cp-matter.bsky.social 🔗 doi.o [bsky, 31 points, 1 comments]