Combining machine learning and quantum chemical calculations for high-throughput virtual screening of thermally activated delayed fluorescence molecular materials: the impact of selection strategy and structural mutations
Chunyun Tu, Weijiang Huang, Sheng Liang, Kui Wang, Qin Tian, Wei Yan
Abstract
= 9. Hence, in a sense, the 'optimal' skeletons seem unique and useful in realizing low energy gaps. With these observations and the development of related HTVS software, we expect to provide insight and tools to the research community of HTVS of molecular (TADF) materials.
Topics & Concepts
ThroughputHigh-throughput screeningSelection (genetic algorithm)FluorescenceVirtual screeningQuantum chemicalChemistryMaterials scienceComputer scienceMolecular dynamicsMoleculeArtificial intelligenceComputational chemistryBiochemistryPhysicsOrganic chemistryTelecommunicationsQuantum mechanicsWirelessMachine Learning in Materials ScienceOrganic Light-Emitting Diodes ResearchMolecular Junctions and Nanostructures