ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT

ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived Partial Atomic Charges and

ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived Partial Atomic Charges and Descriptors for Machine Learning

Molecules, Free Full-Text

Recent trends on density functional theory–assisted calculations of structures and properties of metal–organic frameworks and metal–organic frameworks-derived nanocarbons, Journal of Materials Research

MOF-GRU: A MOFid-Aided Deep Learning Model for Predicting the Gas Separation Performance of Metal–Organic Frameworks

PDF) Inverse design of metal-organic frameworks for direct air capture of CO2 via deep reinforcement learning

ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived Partial Atomic Charges and Descriptors for Machine Learning

J. Compos. Sci., Free Full-Text

Ultrathin water-stable metal-organic framework membranes for ion separation

Recent advances in computational modeling of MOFs: From molecular simulations to machine learning - ScienceDirect

Integrating stability metrics with high-throughput computational screening of metal–organic frameworks for CO2 capture

The top 10 most common a) organic; and b) inorganic substructures in

The Chemistry of Metal-Organic Framework Materials Virtual Issue

ARC–MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived Partial Atomic Charges and Descriptors for Machine Learning

Nanoengineering Metal–Organic Frameworks and Derivatives for Electrosynthesis of Ammonia