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

Large-Scale Refinement of Metal−Organic Framework Structures Using Density Functional Theory

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

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

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

Nanoengineering Metal–Organic Frameworks and Derivatives for Electrosynthesis of Ammonia

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

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

Flow diagram for the construction of CoRE MOF 2019 database

Leveraging Machine Learning for Metal–Organic Frameworks: A Perspective