Synergistic biochar and Serratia marcescens tackle toxic metal contamination: A multifaceted machine learning approach.

Metal contamination in soil poses environmental and health risks requiring effective remediation strategies. This study introduces an innovative approach of synergistically employing biochar and bacterial inoculum of Serratia marcescens to address toxic metal (TM) contamination. Physicochemical, enzymatic, and microbial analyses were conducted, employing integrated biomarker response (IBR) and machine-learning approaches for toxicity estimation. The combined application significantly reduced the Cd, Cr, and Pb concentrations by 71.6, 31.2, and 57.1%, respectively, while the Cu concentration increased by 85% in the individual Serratia marcescens treatment. Biochar enhanced microbial biomass by 33-44% after 25 days. Noteworthy physicochemical improvements included a 44.7% increase in organic content and a decrease in pH and electrical conductivity. The K⁺ and Ca2⁺ concentrations increased by 196.9 and 21.6%, respectively, while the Mg2⁺ content decreased by 86.4%. Network analysis revealed intricate relationships, displaying direct and indirect negative correlations between metals and soil physicochemical parameters. The IBR index values indicated effective mitigation of TM toxicity in Serratia marcescens and biochar with individual and combined treatments. Binary classification demonstrated high sensitivity (80.1%) and specificity (80.5%) in identifying TM-contaminated soil. These findings indicate significant biochar- and Serratia marcescens-induced impacts on toxic metal availability, physicochemical properties, and enzymatic activities in metal-contaminated soil, suggesting that blending soil with biochar and microorganisms is an effective remediation strategy.

Synthesis and Characterization of Fe-TiO2 Nanomaterial: Performance Evaluation for RB5 Decolorization and In Vitro Antibacterial Studies.

A photocatalytic system for decolorization of double azo reactive black 5 (RB5) dye and water disinfection of E. coli was developed. Sol gel method was employed for the synthesis of Fe-TiO2 photocatalysts and were characterized using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy dispersive X-ray analysis (EDX), transmission electron microscopy (TEM), diffuse reflectance spectroscopy (DRS) and Brunauer-Emmett-Teller (BET) analysis. Results showed that photocatalytic efficiency was greatly influenced by 0.1 weight percent iron loading and 300 °C calcination temperature. The optimized reaction parameters were found to be the ambient temperature, working solution pH 6.2 and 1 mg g-1 dose to completely decolorize RB5. The isotherm studies showed that RB5 adsorption by Fe-TiO2 followed the Langmuir isotherm with maximum adsorption capacity of 42.7 mg g-1 and Kads 0.0079 L mg-1. Under illumination, the modified photocatalytic material had higher decolorization efficiency as compared to unmodified photocatalyst. Kinetic studies of the modified material under visible light irradiation indicated the reaction followed the pseudo-first-order kinetics. The illumination reaction followed the Langmuir-Hinshelwood (L-H) model as the rate of dye decolorization increased with an incremental increase in dye concentration. The L-H constant Kc was 1.5542 mg L-1∙h-1 while Kads was found 0.1317 L mg-1. The best photocatalyst showed prominent percent reduction of E. coli in 120 min. Finally, 0.1Fe-TiO2-300 could be an efficient photocatalyst and can provide a composite solution for RB5 decolorization and bacterial strain inhibition.