Study shows enhanced arsenic removal in water using a novel composite fiber, implying effective pollution treatment methods.
Conventional adsorbents for water arsenic pollution treatment suffer from agglomeration, difficult recovery, and insufficient active sites. To solve these problems, in this study, we prepared a CTAB-modified ferroferric oxide-sepiolite composite fiber (PAN-Sep@Fe₃O₄) supported on polyacrylonitrile (PAN) using coprecipitation and electrospinning technologies. We systematically investigated the material's adsorption performance for As(V) under different conditions, including pH, adsorbent loading, coexisting ions, and adsorption-desorption cycles. Its structural and physicochemical properties were characterized by SEM, XRD, FT-IR, XPS, and VSM. Results indicate that the material exhibits a dense reticular mesoporous structure and superparamagnetism with an average pore size of 14.54 nm and a saturation magnetization of 21.89 emu g⁻¹, which facilitates magnetic separation and recovery. The adsorption process conforms to the Langmuir isotherm model and the pseudo-second-order kinetic model, indicating chemisorption-dominated monolayer adsorption as the primary mechanism. The maximum adsorption capacity at 313 K reached 87.48 mg g⁻¹. Thermodynamic analysis parameters indicated ΔG < 0, ΔH < 0, and ΔS > 0, confirming adsorption as an exothermic, entropy-driven spontaneous process. The adsorption mechanism involves oxidation of Fe²⁺ on the Fe₃O₄ surface to Fe³⁺, which then forms Fe-O-As coordination bonds with AsO₄³⁻. The Si-O framework and surface hydroxyl groups of sepiolite synergistically immobilize arsenic through chelation and electrostatic interactions. After five adsorption-desorption cycles, the removal efficiency remained above 98%, with good tolerance to coexisting ions. This composite fiber combines high adsorption efficiency, convenient magnetic recovery, and excellent formability, providing a practical technical solution for treating arsenic(V)-contaminated water bodies with potential for engineering applications.
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Zhu et al. (2026) studied this question.
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