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超声辅助壳聚糖浸渍 Ni-Fe 层状双氢氧化物生物吸附剂对 As(III)的吸附:优化研究和人工智能建模。

Ultrasonication expedited As(III) adsorption onto chitosan impregnated Ni-Fe layered double hydroxide biosorbent: Optimization studies and artificial intelligence modelling.

机构信息

Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, 201313, India.

Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico.

出版信息

Environ Res. 2022 Sep;212(Pt A):113184. doi: 10.1016/j.envres.2022.113184. Epub 2022 Mar 28.

DOI:10.1016/j.envres.2022.113184
PMID:35358544
Abstract

Chitosan intercalated Ni-Fe layered double hydroxide (Ni-Fe LDH/Ch), prepared by co-precipitation was examined for adsorptive elimination of arsenic (III). Energy Dispersive X-ray analysis, X-ray diffraction, Fourier Transform Infrared spectroscopy, Scanning Electron Microscopy, and Dynamic Light Scattering validated the successful synthesis of the composite with enhanced adsorption sites. Maximal As(III) removal was obtained at adsorbent dose 1 gL, pH 7, ultrasonication time 30 min, temperature 298 K, and initial arsenic concentration 50 mgL. The experimentally obtained values fit the Langmuir isotherm and pseudo-second-order dynamics well (R > 0.98), while thermodynamic evaluation confirmed exothermic and spontaneous reaction (ΔG = -8.13 kJ mol). Further, adaptive neuro-fuzzy inference system and artificial neural network successfully predicted As(III) removal percentage with a high correlation coefficient (R > 0.94) and low statistical errors (MSE< 0.002, AARE< 0.063). The prepared material successfully brought down arsenic level by 62% in a natural water sample and showed good reusability up to 5 consecutive treatment cycles. The results recommended that Ni-Fe LDH/Ch has ample potential for arsenic remediation, and further investigations can be carried out for large-scale applications.

摘要

壳聚糖插层镍铁层状双氢氧化物(Ni-Fe LDH/Ch)通过共沉淀法制备,用于吸附去除砷(III)。能量色散 X 射线分析、X 射线衍射、傅里叶变换红外光谱、扫描电子显微镜和动态光散射验证了复合材料的成功合成,并具有增强的吸附位点。在吸附剂剂量为 1 g/L、pH 值为 7、超声时间为 30 min、温度为 298 K 和初始砷浓度为 50 mg/L 的条件下,砷(III)的去除率达到最大值。实验获得的值很好地符合朗缪尔等温线和拟二级动力学(R>0.98),而热力学评价证实了这是一个放热和自发的反应(ΔG=-8.13 kJ/mol)。此外,自适应神经模糊推理系统和人工神经网络成功地预测了砷(III)去除率,具有很高的相关系数(R>0.94)和低的统计误差(MSE<0.002,AARE<0.063)。该制备材料成功地将天然水样中的砷含量降低了 62%,并在 5 次连续处理循环中表现出良好的可重复使用性。结果表明,Ni-Fe LDH/Ch 在砷修复方面具有巨大的潜力,可进一步进行大规模应用的研究。

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