We establish a machine learning-based method to predict emission/absorption wavelength and PLQY of organic fluorescent materials.A platform has been establised for experimenters to use, as well as use
The 3 786 315 neutral singlet molecules without any atomic charges (formal or real) composed of only H, C, N, O, F and S that belong to GDBChEMBL. Data only proposed for the reproducibility of th
This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI desc
Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization ap
