Highly crystalline core dominated the catalytic performance of carbon dot for cyclohexane to adipic acid reaction

Carbon dots (CDs) have uniquely structural, physicochemical and photochemical properties, suggesting a promising platform for catalysis applications. The in-depth understanding of the structure-activity relationship in the CDs-based catalyst system needs to know the effect of the crystalline core on their catalytic performance. The efficient catalytic oxidation of cyclohexane is an urgent challenge in current chemical industry, in which, adipic acid (AA) plays an important role in industry for synthesis of nylon-6 and nylon-66. Here, we fabricated the pristine CDs by electrochemical etching graphite rod method and derived CDs with high crystalline core (CD-600, CD-800, and CD-1100) through a thermal treatment method in tube furnace. Furthermore, these CDs performed an outstanding catalytic performance for one-step synthesis of AA from cyclohexane. With the help of machine learning (ML), the deep correlations between features (structures of CDs, catalytic conditions) and catalytic performances were investigated by XGBoost (XGB) model. Then under the optimization and prediction of XGB, it was found that high crystalline core preceded the other features and CD-1100 could get the best conversion of 30.696% and selectivity to AA of 92.52% at reaction conditions of 130 °C, 1.5 MPa, and 10 h. This work pioneered the application of ML in industrial issues and demonstrated a comprehensive understanding on CDs as catalyst to realize one-step synthesis of AA.