Arsenic removal from water using an acid-modified biochar

• Published in: Journal of molecular structure 2025-03, Vol.1324, p.140904, Article 140904
• Main Authors: Jaiswal, Vivek Kumar, Gupta, Arijit Dutta, Kushwaha, Rohit, Kumar, Rajneesh, Singh, Kiran, Singh, Harinder, Mohan, Devendra, Singh, Ram Sharan
• Format: Article
• Language: English
• Subjects: Acidic functional groups; Adsorption; ANN; Arsenic; Biochar; Tea waste
• ISSN: 0022-2860
• DOI: 10.1016/j.molstruc.2024.140904

•Tea waste biochar (TWB) and modified TWB (MTWB) was used for arsenic removal.•H3PO4-modified biochar exhibited a maximum adsorption capacity of 32 mg/g.•The adsorption equilibria data fitted well into the Freundlich isotherm model.•As(V) ions were held by weak Van der Waals forces of attraction via physisorption.•Topology network (4–7–1) showed strong experimental predicted arrangement.•There was no significant decrease in the removal efficiency till the first 5 cycles. Groundwater, constituting 97 % of global freshwater, is essential for domestic water supply. As the global population grows, securing safe drinking water remains a critical challenge. Therefore, it is essential to develop advanced technology for the effective reduction of arsenic (As) concentration from the environment. This study investigates the applicability of biochar derived from tea waste for As(V) ions adsorption from synthetic wastewater. The pristine biochar (tea waste biochar) was subsequently modified by H3PO4 (to produce acidic functional groups) via the wet impregnation method. X-ray diffraction (XRD) analysis revealed that acidic functional groups had been assimilated into the biochar's crystalline area. Brunauer–Emmett–Teller (BET) analysis exhibited a specific surface area of 6.85 m²/g of biochar, giving a maximum adsorption capacity of 33 mg/g for As(V) ions in solution. The adsorption equilibrium exhibited multi-layer adsorption, fitting well with the Freundlich isotherm model. Furthermore, an Artificial Neural Network (ANN) model was developed using an experimental dataset, achieving an optimal network topology with seven hidden neurons, demonstrating low mean squared error (MSE: 0.002287) and high correlation coefficient (R: 0.95869). The adsorption was feasible at all temperatures (based on ΔH), with maximum uptake capacity at 40°Ⅽ (based on ΔG°). Van der Waals forces, specifically weak molecular attraction forces, account for the adsorption of As(V). The modified biochar exhibited remarkable reusability (over 6 adsorption/desorption cycles) compared to TWB. This study confirms that tea waste biochar is a cost-effective, environment-friendly, and efficient adsorbent for removing arsenic from water. [Display omitted]