The overall workflow of our HTVS process is schematized in Figure . With 278 bidentate ligands collected from previously published experimental studies on Ir(III) complex, millions of candidate molecules are constructed using stk and further optimized via density functional tight binding approach (GFN2-xTB). A structure rationality filter is then introduced to filter out unphysical structures based on atomic distances and/or ligand angles. As such, around 1.6 million candidates are constructed, of which the coordinates and symbols are served as Uni-Mol inputs as well as the initial guesses for QM calculations, while the energies of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) at GFN2-xTB level are served as labels for Uni-Mol pre-training task. Due to the high computational cost of QM calculations, they are only carried out on 1468 randomly selected molecules with less than 61 heavy atoms from the candidate pool. The number of heavy atoms of the whole candidate pool ranges from 22 to 157, and the overall distribution can be seen in Figure . Four QM predicted properties, HOMO, LUMO, the adiabatic excitation energy of T 1 , and the photoluminescence quantum yield (PLQY), are utilized to fine-tune the pre-trained model. All electronic structure calculations are performed with quantum chemistry packages Gaussian16 47 and ORCA, while the photophysical properties including emission spectra and various rate constants are calculated via the thermal vibration correlation function (TVCF) method in the molecular material property prediction package MOMAP. The accuracy of our QM calculation process is validated by comparing the theoretical predicted adiabatic excitation energy and PLQY with the corresponding experimental values on ten selected molecules (as listed in Table ). The molecular structures of these ten molecules are provided in Figure .