ChemFluor

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 used for potential high-throughput screening.<br>[1]<i>The ChemFluor.zip</i> is the platform based on python, which contain trained models, can be used for the prediction directly.[2]<i>Fingerprints_for_prediction.zip</i> is the fingerprints used in our work.[3]<i>Materials_Real-World_Problem.zip</i> is the molecules collected from recent published work and TD-DFT benchmark studies, which can be seen as real world problem. [4]The molecules are stored in the form of SMILES.<br><i>Alldata_SMILES.xlsx</i> contains all the molecules in our dataset as well as the references. <br>[5]ML-models we used in our paper have been saved and uploaded, as<i> model_in_paper.zip.</i>