Cambridge Structural Database
Emerging8papers using it
2023first seen
The Cambridge Structural Database is a comprehensive repository of crystallographic data containing information on mononuclear transition metal complexes, used to evaluate ligand properties and assign net charges for computational studies.
Papers using Cambridge Structural Database (8)
- A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid EstimationThe BOS-Lig Dataset: Accurate Ligand Charges from a Consensus Approach for 66,810 Experimentally Synthesized LigandsThe BOS-TMC Dataset: DFT Properties of 159k Experimentally Characterized Transition Metal Complexes Spanning Multiple Charge and Spin StatesReadMOF: Structure-Free Semantic Embeddings from Systematic MOF Nomenclature for Machine LearningAccelerated Organic Crystal Structure Prediction with Genetic Algorithms
and Machine LearningAccelerating Material Property Prediction using Generically Complete
Isometry InvariantsPhysics-informed generative model for drug-like molecule conformersCarbNN: A Novel Active Transfer Learning Neural Network To Build De Novo
Metal Organic Frameworks (MOFs) for Carbon Capture