Periodate activation by a Fenton sludge biochar for enhanced tetracycline degradation: Identification of key factors through machine learning

An innovative composite catalyst for enhanced tetracycline (TC) degradation was synthesized by combining Fenton sludge from wastewater treatment with bagasse, advancing the concept of “waste for waste” by efficiently utilizing the industrial by-products. The catalyst, in conjunction with periodate technology, exhibited TC degradation rates above 92 % in a broad pH range (3–11) and complex aqueous matrices. A comprehensive investigation was conducted to examine the impact of the catalyst quality, solution pH, contaminant concentration, and the presence of common anions on TC degradation. Iron oxide with a nanoblock structure, predominantly present as Fe₃O₄ according to X-ray diffraction (XRD) analysis, was uniformly distributed on the surface of folded biochar. X-ray photoelectron spectroscopy (XPS) analysis further indicated the presence of both Fe²⁺ and Fe³⁺ in the composite catalyst. The TC degradation process was hindered by the presence of SO₄²⁻, H₂PO₄⁻, CO₃²⁻, and citrate ions, leading to the depletion of hydroxyl radicals and the formation of citrate in the system. In terms of oxidation mechanisms, electron paramagnetic resonance (EPR) and free radical trapping experiment identified the active species involved in TC degradation, arranged in the order according to their degradation activity: ¹O₂ > O₂⁻ > IO₃/IO₄ > OH. The iodate/periodate conversion experiments confirmed that no reactive iodine species or iodination by-products were generated in the system. Additionally, four machine learning (ML) models were applied to validate the catalyst’s synthesis procedure, predicting the factors of influence and identifying key variables. The optimal conditions for material preparation were determined using bidirectional partial dependence analysis (PDP), revealing a pyrolysis temperature range of 583–661 °C, a Fenton iron sludge/bagasse ratio of 1.75–3, and a binder ratio spanning from 0 to 12.5 %. These parameters were subsequently applied to optimize the synthesized material toward enhanced performance. The findings obtained in this study not only open new pathways for the resourceful utilization of Fenton iron sludge but also underscore the transformative potential of ML in advancing materials science.