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Application of cuckoo optimization algorithm-artificial neural network method of zinc oxide nanoparticles-chitosan for extraction of uranium from water samples

机译:杜鹃优化算法-人工神经网络方法研究氧化锌纳米粒子-壳聚糖在水样中提取铀的应用

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摘要

In this study, a solid phase extraction using the new sorbent (zinc oxide nanoparticles-chitosan) has been developed for preconcentration and determination of trace amount of uranium from water samples. Hybrid modeling of cuckoo optimization algorithm-artificial neural network (COA-ANN) has been employed to develop the model for simulation and optimization of this method. The 1-(2-pyridylazo)-2-naphthol (PAN) was used as chelating agent The pH, volume of elution solvent, mass of zinc oxide nanoparticles-chitosan, concentration of PAN, flow rate of sample and elution solvent were the input variables, while recovery of uranium was the output. At the optimum conditions, the limit of detections and enrichment factor were 0.5 μg L~(-1) and 125, respectively for the uranium. The developed procedure was then applied to the extraction and determination of uranium from water samples.
机译:在这项研究中,已经开发了一种使用新型吸附剂(氧化锌纳米粒子-壳聚糖)的固相萃取技术,用于对水样品中的痕量铀进行预浓缩和测定。布谷鸟优化算法-人工神经网络(COA-ANN)的混合模型已被用于开发该方法的仿真和优化模型。使用1-(2-吡啶基偶氮)-2-萘酚(PAN)作为螯合剂。输入pH值,洗脱溶剂的体积,氧化锌纳米颗粒-壳聚糖的质量,PAN的浓度,样品的流速和洗脱溶剂变量,而铀的回收是产出。在最佳条件下,铀的检出限和富集因子分别为0.5μgL〜(-1)和125。然后将开发的程序应用于从水样中提取和测定铀。

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