▎ 摘　　要

Noble metal-free heterogeneous catalysts are highly desired for selective and solvent-free oxidation reactions. However, their practical application has been greatly restricted by their moderate activity. Herein, the scalable synthesis of a noble metal-free (Fe,Co,Ni,Cu)(3)O-4 medium entropy oxide (MEO) catalyst and its grafting on reduced graphene oxide (rGO) is detailed. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses confirm the formation of a high entropy spinel oxide phase with inclusions of CuO particles as a secondary phase. This MEO@rGO catalyst exhibits excellent performance for solvent-free aerobic oxidation of toluene, with 18.2% conversion after 4 hours and over 90% selectivity for benzaldehyde, outperforming all previously reported catalysts, including those based on noble metals. A thorough analytical investigation reveals that the outstanding MEO@rGO activity is related to a synergistic effect between the multiple different cations in the MEO, its abundant oxygen vacancies and the active sites on rGO. In addition, four robust machine learning models including adaptive boosting-support vector regression (SVR), Random Forest, K-nearest neighbor and Extra tree are applied to predict selectivity. The Adaboost-SVR model best fits all the experimental data with an average absolute relative error of 0.09%. The proposed model is reliable as an effective predictor for selectivity and has great potential to be used in the chemical and petrochemical industries.