Abstract
The paper presents the results of the synthesis and study of iron oxide-based sorbents (Fe (x) O (y) -NPs) obtained from iron removal station sludge by exothermic combustion in solution using glycine, urea, citric acid, and urotropine as reducing agents. X-ray phase analysis revealed that the phase composition depends on the nature of the reducing agent and temperature: at 300-500 °C, the magnetite content reached 97-99% for citric acid and urea, whereas when using glycine, the Fe(3)O(4) fraction did not exceed 30%. The point of zero charge values shifted to the alkaline region with increasing synthesis temperature, reaching 8.8 at 700 °C. The specific surface area for methylene blue was up to 186 m(2)/g, but the calculated values exceeded the BET data by 3.5-4 times due to multilayer sorption on the functionalized surface, which is consistent with the FTIR spectra. The oil sorption capacity (OSC) of the synthesized sorbents reached 6.1 g/g (glycine, 500 °C), which is comparable to or exceeds the indicators of a number of natural and commercial sorbents. After five sorption-regeneration cycles at 800 °C, the OSC decreased by only 15.7%, confirming the stability of the material. The constructed polynomial and machine learning models (CatBoost, XGBoost) provided high accuracy of OSC prediction (R (2) = 1.0), which demonstrates the promise of machine learning for optimizing synthesis conditions.