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Ultrasound-assisted dispersive solid phase nanoextraction of selected personal care products in wastewater followed by their determination using high performance liquid chromatography-diode array detector.
Journal of Hazardous Materials ( IF 13.6 ) Pub Date : 2018-08-18 , DOI: 10.1016/j.jhazmat.2018.08.049
Anele Mpupa 1 , Geaneth P Mashile 1 , Philiswa N Nomngongo 1
Affiliation  

This study reports a rapid and simple method based on ultrasound-assisted dispersive solid phase nanoextraction (UA-SPNE) method for the extraction and preconcentration of selected personal care products using MPC@Al2O3-SiO2 nano adsorbent. A high performance liquid chromatograph equipped with a diode array detector (HPLC-DAD) was used to detect the analytes of interest. Experimental parameters affecting the extraction and preconcentration efficiency of the UA-SPNE (such as mass of adsorbent, extraction time, sample pH and eluent volume,) were optimized using fractional factorial design and response surface methodology based on central composite design. Under optimized conditions, the linear range for benzophenone, N,N-diethyl-3-methylbenzamide and trichlorocarbanilide were in the interval of LOQ-1000 μg L-1 with correlation coefficients ranged from 0.9907 to 0.9977. The limits of detection and limits of quantification were 0.066-0.096 μg L-1 and 0.22-0.32 μg L-1, respectively. The accuracy of the UA-SPNE/HPLC-DAD method was evaluated using spike recovery test and the recoveries were in the range of 98-107%. The repeatability and reproducibility of the method 0.8-1.0 % and 2.4-4.4%, respectively.

中文翻译:

超声辅助分散固相纳米萃取废水中的选定个人护理产品,然后使用高效液相色谱-二极管阵列检测器对其进行测定。

这项研究报告了一种基于MPS @ Al2O3-SiO2纳米吸附剂的超声辅助分散固相纳米萃取(UA-SPNE)方法对选定的个人护理产品进行萃取和预浓缩的快速简便的方法。配备有二极管阵列检测器(HPLC-DAD)的高效液相色谱仪用于检测目标分析物。使用分数阶乘设计和基于中心复合设计的响应面方法,优化了影响UA-SPNE萃取和预浓缩效率的实验参数(例如吸附剂质量,萃取时间,样品pH和洗脱液体积)。在最佳条件下,二苯甲酮,N,N-二乙基-3-甲基苯甲酰胺和三氯氨基甲酰苯胺在LOQ-1000μgL-1的区间内,相关系数在0.9907至0.9977之间。检测限和定量限分别为0.066-0.096μgL-1和0.22-0.32μgL-1。使用加标回收率测试评估UA-SPNE / HPLC-DAD方法的准确性,回收率在98-107%的范围内。该方法的重复性和重现性分别为0.8-1.0%和2.4-4.4%。
更新日期:2019-02-26
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