Work

Preparation of iron-based Fenton-like catalysts using sufficient pyrolysis method: Rapid evaluation of performance, prediction of performance by machine learning, and characterization

Year: 2025

Type: article

Abstract: Preparation of Fenton sludge into magnetic biochar is a promising direction for resource utilization. In this study, iron-based Fenton-like catalysts were prepared by sufficient pyrolysis with catalyst performance evaluation according to their volatile matter and low-valent iron content. Machine learning models were then applied to predict catalyst performance and elucidated key controlling factors. The best-performing catalyst could remove 82% of TOC and 98% of chroma in treating real MBR effluent of landfill leachate. EDS and XRD analysis results confirmed abundant zero-valent iron loaded on catalyst, and VSM measurements yielded saturation magnetization of 54.89 emu/g, indicating facile magnetic recovery. The volatile matter and low-valent iron content of each catalyst were linearly correlated to the TOC/chroma removal rate with an R 2 approximately 0.82∼0.86, suggesting that the catalyst performance could be roughly assessed. Comparison of SVR and XGBoost models showed that XGBoost provided superior prediction, with R 2 and RMSE values of 0.999 and 0.132 for chroma removal, and 0.999 and 0.149 for TOC removal rate, respectively. Finally, the marginal contribution of the input features to the predicted results of the XGBoost model was quantified and visualized using the Shapley Additive exPlanations Plot, revealing that pyrolysis temperature was the most important factor. These methods and conclusions provide new strategies for the research and application of iron-based Fenton-like catalysts, and are conducive to engineering applications.

Source: Results in Engineering

DOI: 10.1016/j.rineng.2025.106610