新型氧化铝基铁锰复合滤料制备及其深度除砷性能研究

    Preparation of a novel alumina-based iron-manganese composite filter material and investigation of its enhanced arsenic removal performance

    • 摘要: 当前河道水砷污染的复杂性与深度处理的高要求使得高效滤料的开发具有重要意义。本文采用水热法制备了一种新型氧化铝基铁锰复合滤料(RFM-3),并对其在含砷废水深度处理中的应用性能进行了系统研究。本文通过扫描电子显微镜(SEM)、X射线衍射(XRD)和傅里叶变换红外光谱(FT-IR)等技术手段,对滤料的形貌、晶体结构及表面化学状态进行了全面表征。研究结果表明,RFM-3具有纳米级颗粒负载结构,比表面积较大,表面羟基(—OH)在砷吸附过程中发挥主要作用。在初始砷浓度为0.5 mg/L的条件下,RFM-3对砷的去除率高达95.63%,并且在pH值4~10及高离子浓度环境下仍能保持高效的去除效果。此外,RFM-3经过10次再生循环后,吸附效率仅下降3%,动态模拟实验进一步证实了其出色的稳定性。综上所述,RFM-3作为一种新型砷吸附滤料,展现出高效、稳定的性能,具有广阔的实际应用前景。

       

      Abstract: Currently, the complexity and enhanced treatment requirements of arsenic contamination in river water highlight the critical need for efficient filter materials. In this paper, a novel alumina-based iron-manganese composite filter material(RFM-3) is synthesized via hydrothermal method and evaluated for its performance in treating arsenic-contaminated wastewater. Advanced characterization techniques, including scanning electron microscopy(SEM), X-ray diffraction(XRD), and Fourier-transform infrared spectroscopy(FT-IR), are employed to conduct a comprehensive characterization of the filter material’s morphology, crystalline structure, and surface chemistry. Results demonstrate that RFM-3 exhibited a nanostructured particle-supported configuration with a high specific surface area, where surface hydroxyl groups(—OH) play a dominant role in arsenic adsorption. RFM-3 achieves a significant arsenic removal rate of 95.63% at an initial arsenic concentration of 0.5 mg/L and maintained efficient removal across a pH value range of 4-10 and in environments with high ionic strength. Furthermore, the filter material retained its stability with only a 3% decrease in adsorption efficiency after undergoing 10 regeneration cycles, as confirmed by dynamic simulation experiments. In conclusion, RFM-3 is identified as a novel arsenic adsorbent with high efficiency and stability, showing considerable potential for practical applications.

       

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