Jun, Byung-Moon Chae, Sung Ho Kim, Deokhwan Son, Changgil Kim, Tack-Jin Hong, Seok Won Yoon, Yeomin Chon, Kangmin Rho, Hojung 2025-04-25T07:30:17Z 2025-04-25T07:30:17Z 2025-04-25 2025-08 1383-5866 https://pubs.kist.re.kr/handle/201004/152329 Uranium contamination resulting from nuclear waste disposal poses significant environmental and health risks, necessitating the development of effective remediation strategies. In this study, we investigate the use of biocharbased adsorbents derived from coffee waste for the removal of U(VI) from acidic effluent produced by real uranium-contaminated soil through acid leaching, providing a novel solution to real-world contamination. Two biochars-pristine and ZnFe-modified-were synthesized, and their U(VI) adsorption performance was evaluated through a comprehensive analysis of their physicochemical properties. The biochar's adsorption performance was assessed under diverse experimental conditions, examining its isotherm, kinetic, and thermodynamic characteristics. Additionally, its behavior was analyzed in the presence of background cations, anions, and humic acid within a real acidic effluent containing U(VI). Despite the significantly larger surface area of ZnFe-modified biochar (1218.4 m2/g vs. 40.8 m2/g for pristine biochar), pristine biochar exhibited superior U(VI) adsorption capacity at pH 4. This enhancement was attributed to its negative surface charge, which promotes electrostatic interactions with the positively charged U(VI) ions. Conversely, the positive surface charge of ZnFe-modified biochar hindered U(VI) adsorption efficiency under similar conditions. Machine learning models, including Random Forest, XGBoost, and LightGBM, were employed to predict adsorption capacity and analyze key operational parameters. SHapley Additive exPlanations analysis identified initial uranium concentration, exposure time, and pH as the most critical factors. These findings underscore the novelty of using real uraniumcontaminated soil effluent and highlight pristine biochar as an effective, sustainable material for U(VI) removal. English Pergamon Press Ltd. Remediation of acidic effluents from Uranium-Contaminated soil using coffee Residue Biochar: A Combined experimental and Machine learning approach☆ Article 10.1016/j.seppur.2025.132844 1 Separation and Purification Technology, v.366 Separation and Purification Technology 366 Y scie scopus 001464430400001 2-s2.0-105001858942 Engineering, Chemical Engineering Article REMOVAL DECONTAMINATION Biochar Acidic effluent Uranium adsorption Machine learning