·B-H HTE dataset: Yield dataset in % unit obtained by HTE approach with 3955 reactions, including 15 aryl halides, 22 additives, 4 Pd catalysts, and 3 bases.

·S-M HTE dataset: Yield dataset in % unit comprising 7 quinolines, 4 indazoles, 12 ligands, 8 bases, 6 solvents, and a total of 5760 reactions were acquired by the HTE platform.

·A-T HTE dataset: The exponential relationship that exists between enantiomeric excess value and free energy differential (ΔΔG) between the transition structures leading to each enantiomer. Therefore, the dataset records the ΔΔG value in kcal/mol unit of 1075 reactions acquired via HTE approach, containing 5 imines, 5 thiols, and 43 chiral phosphoric acid (CPA) catalysts, to test the enantioselectivity prediction ability of the model.

·SNAr literature-based dataset: A collection of activation energy in kcal/mol unit from 37 cases of literature including 443 reactions involving 119 substrates, 83 nucleophiles, and 17 solvents.

#Buchwald–Hartwig数据集的源文献
Ahneman, D. T.; Estrada, J. G.; Lin, S.; Dreher, S. D.; Doyle, A. G. Predicting Reaction Performance in C–N Cross-Coupling Using Machine Learning. Science 2018, 360, 186–190.
#suzuki数据集的源文献
Perera, D.; Tucker, J. W.; Brahmbhatt, S.; Helal, C. J.; Chong, A.; Farrell, W.; Richardson, P.; Sach, N. W. A Platform for Automated Nanomole-Scale Reaction Screening and Micromole-Scale Synthesis in Flow. Science 2018, 359, 429–434.
#亲核芳香族取代反应数据集的源文献
Jorner, K.; Brinck, T.; Norrby, P.-O.; Buttar, D. Machine Learning Meets Mechanistic Modelling for Accurate Prediction of Experimental Activation Energies. Chem. Sci. 2021, 12, 1163–1175.
#denmark数据集的源文献
Zahrt, A. F.; Henle, J. J.; Rose, B. T.; Wang, Y.; Darrow, W. T.; Denmark, S. E. Prediction of Higher-Selectivity Catalysts by Computer-Driven Workflow and Machine Learning. Science 2019, 363, eaau5631.