Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow, 226 001, India.
Environ Sci Pollut Res Int. 2012 Nov;19(9):3914-24. doi: 10.1007/s11356-012-1005-y. Epub 2012 Jun 8.
The present study aims to investigate the EDTA catalyzed reduction of nitrate (NO (3) (-) ) by zero-valent bimetallic (Fe-Ag) nanoparticles (ZVBMNPs) in aqueous medium and to enumerate the effect of temperature, solution pH, ZVBMNPs dose and EDTA concentration on NO (3) (-) reduction. Batch experimental data were generated using a four-factor Box-Behnken design. Optimization modeling was performed using the response surface method for maximizing the reduction of NO (3) (-) by ZVBMNPs. Significance of the independent variables and their interactions were tested by the analysis of variance and t test statistics. The model predicted maximum reduction capacity (340.15 mg g(-1) NO (3) (-) ) under the optimum conditions of temperature, 60 °C; pH 4; dose, 1.0 g l(-1); and EDTA concentration, 2.0 mmol l(-1) was very close to the experimental value (338.62 mg g(-1)) and about 16 % higher than the experimentally determined capacity (291.32 mg g(-1)). Study demonstrated that ZVBMNPs had higher reduction efficiency than Fe(0) nanoparticles for NO (3) (-) . EDTA significantly enhanced the NO (3) (-) reduction by ZVBMNPs. The EDTA catalyzed reduction of NO (3) (-) by ZVBMNPs can be employed for the effective decontamination of water.
本研究旨在探讨乙二胺四乙酸(EDTA)催化零价双金属(Fe-Ag)纳米粒子(ZVBMNPs)在水介质中还原硝酸盐(NO3-)的反应,并研究温度、溶液 pH 值、ZVBMNPs 剂量和 EDTA 浓度对 NO3-还原的影响。通过四因素 Box-Behnken 设计生成批实验数据。采用响应面法对优化模型进行了最大化 ZVBMNPs 还原 NO3-的建模。通过方差分析和 t 检验统计数据测试了自变量及其相互作用的显著性。在温度为 60°C、pH 值为 4、剂量为 1.0 g/L 和 EDTA 浓度为 2.0 mmol/L 的最佳条件下,该模型预测了最大还原能力(340.15 mg/g NO3-),非常接近实验值(338.62 mg/g),比实验确定的容量(291.32 mg/g)高约 16%。研究表明,ZVBMNPs 比 Fe(0)纳米粒子具有更高的 NO3-还原效率。EDTA 显著提高了 ZVBMNPs 对 NO3-的还原效率。ZVBMNPs 与 EDTA 协同还原 NO3-可用于有效净化水。