Bioengineered iron nanoparticles for arsenic remediation: Unraveling the adsorption-oxidation-fixation pathway via SHAP-interpretable machine learning and LC-AFS speciation tracking

Green one-pot synthesis of Ib-FeNPs using Ipomoea batatas leaf extract. • Organic-Fe cooperation supports adsorption, partial oxidation, and fixation. • SHAP analysis of SVR and RF identifies dosage as the dominant predictor. • Fixed-bed treatment removes about 80% of arsenic from real acid mine drainage. Arsenic-contaminated wastewater poses a persistent threat to public health and ecological safety, while conventional remediation materials often involve trade-offs among performance, sustainability, and economic feasibility. Here, biomolecule-coated iron-based nanoparticles (Ib-FeNPs) were synthesized from Ipomoea batatas ( I. batatas ) leaf extract through a green one-pot route for the simultaneous removal of As(III) and As(V). In a mixed‑arsenic system, Ib-FeNPs achieved removal efficiencies of 92.4% for As(III) and 100.0% for As(V) after 360 min at a dosage of 0.3 g·L −1 . These values exceeded those obtained with bare FeNPs (10.3% and 60.1%), the isolated capping layer (21.5% and 92.0%), and their physical mixture (26.5% and 83.8%). Time-resolved liquid chromatography-atomic fluorescence spectrometry detected the partial conversion of initially added As(III) to As(V). Analysis of the As 3d X-ray photoelectron spectra identified both species on the reacted material. A decrease in the surface Fe(III) fraction accompanied by an increase in Fe(II) was consistent with the participation of Fe-containing sites in redox processes. The component and physical-mixture controls showed that assembly of the Fe-containing phase and plant-derived coating improved simultaneous arsenic removal. Material characterization revealed Fe-containing surface environments and organic functional groups. Liquid chromatography-quadrupole time-of-flight mass spectrometry identified 18 major plant-derived biomolecules. Six regression algorithms were compared using a four-factor experimental dataset, and SHapley additive explanations (SHAP) were applied to the selected models to assess the contributions of operating variables to predicted removal efficiencies within the investigated range. Together, these findings support an adsorption-oxidation-fixation pathway at the process level. Ib-FeNPs also showed good reusability over five cycles and achieved 80.0% total arsenic removal in a fixed-bed experiment with acid mine drainage (AMD). Overall, Ib-FeNPs provide a plant-mediated platform for arsenic-contaminated water remediation, while the integrated machine-learning and characterization framework offers a transferable approach to developing bio-nano adsorbents from underutilized biomass. Download: Download high-res image (131KB) Download: Download full-size image