Screening and performance optimization of fungi for heavy metal adsorption in electrolytes.

The resource recovery and reuse of precious metal-laden wastewater is widely recognized as crucial for sustainable development. Superalloy electrolytes, produced through the electrolysis of superalloy scrap, contain significant quantities of precious metal ions, thereby possessing substantial potential for recovery value. This study first explores the feasibility of utilizing fungi to treat Superalloy electrolytes. Five fungi resistant to high concentrations of heavy metals in electrolytes (mainly containing Co, Cr, Mo, Re, and Ni) were screened from the soil of a mining area to evaluate their adsorption characteristics. All five fungi were identified by ITS sequencing, and among them, showed the best adsorption performance for the five heavy metals; therefore, we conducted further research on its adsorption characteristics. The best adsorption effect of Co, Cr, Mo, Re, and Ni was 37.09, 64.41, 47.87, 41.59, and 25.38%, respectively, under the conditions of pH 5, time 1 h, dosage 26.67 g/L, temperature 25-30°C, and an initial metal concentration that was diluted fivefold in the electrolyte. The biosorption of Co, Mo, Re, and Ni was better matched by the Langmuir model than by the Freundlich model, while Cr displayed the opposite pattern, showing that the adsorption process of for the five heavy metals is not a single adsorption mechanism, but may involve a multi-step adsorption process. The kinetics study showed that the quasi-second-order model fitted better than the quasi-first-order model, indicating that chemical adsorption was the main adsorption process of the five heavy metals in . Fourier transform infrared spectroscopy revealed that the relevant active groups, i.e., hydroxyl (-OH), amino (-NH), amide (- CONH), carbonyl (-C = O), carboxyl (-COOH), and phosphate (PO), participated in the adsorption process. This study emphasized the potential application of in the treatment of industrial wastewater with extremely complex background values.