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采用机器人辅助动态单滴微萃取和液相色谱-串联质谱法测定废水中的对羟基苯甲酸酯。

Determination of parabens in wastewater samples via robot-assisted dynamic single-drop microextraction and liquid chromatography-tandem mass spectrometry.

机构信息

São, Carlos Institute of Chemistry, University of São Paulo, São Carlos, São Paulo, Brazil.

出版信息

Electrophoresis. 2022 Aug;43(15):1567-1576. doi: 10.1002/elps.202100390. Epub 2022 May 26.

Abstract

Dynamic single-drop microextraction (SDME) was automatized employing an Arduino-based lab-made Cartesian robot and implemented to determine parabens in wastewater samples in combination with liquid chromatography-tandem mass spectrometry. A dedicated Arduino sketch controls the auto-performance of all the stages of the SDME process, including syringe filling, drop exposition, solvent recycling, and extract collection. Univariate and multivariate experiments investigated the main variables affecting the SDME performance, including robot-dependent and additional operational parameters. Under selected conditions, limit of detections were established at 0.3 µg/L for all the analytes, and the method provided linear responses in the range between 0.6 and 10 µg/L, with adequate reproducibility, measured as intraday relative standard deviations (RSDs) between 5.54% and 17.94%, (n = 6), and inter-days RSDs between 8.97% and 16.49% (n = 9). The robot-assisted technique eased the control of dynamic SDME, making the process more feasible, robust, and reliable so that the developed setup demonstrated to be a competitive strategy for the automated extraction of organic pollutants from water samples.

摘要

采用基于 Arduino 的自制笛卡尔机器人自动化动态单滴微萃取 (SDME),并结合液相色谱-串联质谱法用于测定废水中的对羟基苯甲酸酯。专门的 Arduino 草图控制 SDME 过程所有阶段的自动执行,包括注射器填充、液滴暴露、溶剂回收和萃取物收集。单变量和多变量实验研究了影响 SDME 性能的主要变量,包括机器人相关和其他操作参数。在选定的条件下,所有分析物的检测限均建立在 0.3μg/L 以下,该方法在 0.6 至 10μg/L 范围内提供了线性响应,具有足够的重现性,以日内相对标准偏差 (RSD) 在 5.54%至 17.94%(n=6)之间,和日间 RSD 在 8.97%至 16.49%(n=9)之间进行测量。机器人辅助技术简化了动态 SDME 的控制,使该过程更可行、更稳健和更可靠,因此所开发的装置被证明是从水样中自动提取有机污染物的一种有竞争力的策略。

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