Search

Sample preparation frequently is considered the most critical stage of the analytical workflow. It affects the analytical throughput and costs; moreover, it is the primary source of error and possible sample contamination. To increase efficiency, productivity, and reliability, while minimizing costs and environmental impacts, miniaturization and automation of sample preparation are necessary. Nowadays, several types of liquid-phase and solid-phase microextractions are available, as well as different automatization strategies. Thus, this review summarizes recent developments in automated microextractions coupled with liquid chromatography, from 2016 to 2022. Therefore, outstanding technologies and their main outcomes, as well as miniaturization and automation of sample preparation, are critically analyzed. Focus is given to main microextraction automation strategies, such as flow techniques, robotic systems, and column-switching approaches, reviewing their applications to the determination of small organic molecules in biological, environmental, and food/beverage samples., (© 2023 Wiley-VCH GmbH.)

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., (© 2022 Wiley-VCH GmbH.)

By proper design of an innovative extraction device, a lab-made multipurpose autosampler was exploited in the automated performance of the dynamic large drops based microextraction. The pluses of this new analytical strategy were demonstrated in the determination of sulfonamides and fluoroquinolones in surface water samples, by direct immersion single drop microextraction (SDME) and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis. Operational autosampler features and critical experimental factors influencing SDME, including the extraction mode (static or dynamic), extraction, stirring rate, salt addition, drop size, number of cycles and drop exposition time, were comprehensively investigated using both univariate and multivariate optimization. The lab-made autosampler allowed to performance challenging dynamic and static large drop based SDMEs in an automated and effortless way and with minimal requirements of hardware and software. Large stable drops provided high surface area, enhancing the phase ratio and in consequence increasing the analytes uptake. The best extraction efficiencies were obtained as a result of the synergic interaction between the use of large drops and the automated dynamic mode of extraction. The developed method proved to be a reliable, sensitive, and robust analytical tool, with intraday RSDs ranging between 4.0 and 7.6% (n = 6), and interday RSDs between 4.8 and 9.3% (n = 6), and, LOD and LOQ in the range of 15-50 and 35-100 ng L -1 , respectively., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The present paper describes an original method for the online preconcentration and analysis of ring-substituted amphetamines in urine samples, used on the integration of robot-assisted hollow fiber liquid-phase microextraction (HF-LPME), high-performance liquid chromatography (HPLC), and fluorescence detection (FLD). A lab-made autosampler, actuating a 100-μL syringe and equipped with a three-way solenoid microvalve, allowed the acceptor phase to flow through and be withdrawn from the lumen fiber, enabling the automated online transference of the enriched acceptor phase for chromatographic analysis, through a six-port switching valve. The developed online HF-LPME-LC/FLD method demonstrated high analytical throughput and confidence, facilitating the efficient extraction and determination of the target analytes, with minimal solvent consumption and sample manipulation, in a straightforward way. Sample cleanup, analyte uptake, and analysis were carried out in 14.5 min. Under optimal conditions, automated online HF-LPME showed excellent linearity, precision, and trueness, obtaining intraday RSDs between 2.9 and 9.2% (n = 6) and interday RSDs between 5.3 and 9.3% (n = 6). Enrichment factors (EFs) ranged between 14.2 and 15.7, extraction recoveries (ERs) ranged between 17.7 and 19.5%, and the limits of detection (S/N = 3) were 2.0, 3.0, and 3.0 μg L -1 for MDA, MDMA, and MDEA, respectively. The method proved to be an effortless, rapid, reliable, and environment-friendly approach for the determination of drug abuse in urine samples. Graphical abstract.

A high-throughput and innovative setup has been developed to automate the online integration of single drop microextraction (SDME), liquid chromatography (LC) and high-resolution mass spectrometry (QqToF). SDME and LC were online hyphenated for the first time. SDME was carried out by a lab-made cartesian robot actuating a 100 μL syringe, equipped with a three-way solenoid microvalve that allowed the online transference of the enriched extract to the chromatographic system, through a six-port switching valve. The complete method, including the synchronized robot action, valves, and the analytical instruments, was controlled by an Arduino Mega board. The merits of the proposed setup were demonstrated by the triazines determination in coconut water samples. The most relevant extraction parameters, such as drop size, exposure time, stirring effect, salt addition and pH were systematically investigated. Under optimized conditions (60 μL drop volume and 10 min extraction time), the LC-UV enrichment factors (EF) and the extraction recoveries (ER) ranged between 15.2-18.4 and 11.4-13.8%, respectively. Using the SDME-LC-MS setup, the linear range, detection limit (S/N = 3) and precision (RSD, n = 6 at 0.25 μg L -1 level of concentration) were 0.25-25 μg L -1 , 0.10 μg L -1 and 16.8% for simazine; 0.25-25 μg L -1 , 0.05 μg L -1 and 14.7% for atrazine; and 0.25-25 μg L -1 , 0.05 μg L -1 and 18.5% for propazine, respectively. Although none of the analytes were detected in the evaluated commercial samples, the results indicate that the proposed online SDME-LC setup is a competitive analytical strategy for the determination of target organic compounds in complex matrices., (Copyright © 2019 Elsevier B.V. All rights reserved.)