Identification of the reaction network for the synthesis of adipic acid using machine learning coupling with target factor analysis

Abstract This study investigated the reaction network of the oxidation of cyclohexanone with nitric acid through machine learning (ML) model coupling with target factor analysis (TFA). Experiments for the synthesis of adipic acid (AA) were carefully designed and carried out in a microreactor system. An artificial neural network (ANN) model was applied and optimized by training on experimental data. To assess the established ANN model, a comparison between the predicted concentrations of the products and those calculated with the power law kinetic model was implemented. TFA was then performed on both the experimental data and the data simulated by ANN for identifying the candidate reactions and finding out the temperature boundaries. Based on the identification results of the reaction network, the kinetic characteristics of this oxidation process under various operational conditions were further researched through the incremental approach and simultaneous approach.