RESUMO
Preparative liquid chromatography is a technique for separating complex samples or isolating pure compounds from complex extracts. It involves eluting samples through a packed column and selectively collecting or isolating the separated bands in a sequence of fractions. Depending on the column length and the sample complexity, a large number of fractions may be obtained, making fraction collection a laborious and time-consuming process. Manual fraction collection is also tedious, error-prone, less reproducible, and susceptible to contamination. Several commercial and lab-made solutions are available for automated fraction collection, but most systems do not synchronize with the instrument detector and collect fractions at fixed volumes or time intervals. We have assembled a low-cost Arduino-based smart fraction collector that can record the signal from the UV-vis detector of the chromatography instrument and enable the automated selective collection of the targeted bands. The system consists of a robot equipped with position sensors and a 3-way solenoid valve that switches the column effluent between the waste or collection positions. By proper programming, an Arduino board records the detector response and actuates the solenoid valve, the position sensors, and the stepper motors to collect the target chromatographic bands.
RESUMO
A fast and environment-friendly analytical method was implemented to determine multiclass pesticides in river sediments. Twenty-three pesticides-organochlorine pesticides, organophosphorus pesticides, and triazines-were extracted via matrix solid-phase dispersion (MSPD) and analyzed by gas chromatography-tandem mass spectrometry (GC-MS/MS). Florisil demonstrated excellent analytes uptake capability as the extractant phase, with suitable selectivity for treating complex sediment samples. Under defined extraction conditions, the MSPD-GC-MS/MS method demonstrated robustness in the n inter-day analysis of sediments from different sources, providing limit of quantifications (LOQs) between 5 and 15 ng/g, linear responses in the range between LOQs and 150 ng/g, extraction recoveries of 71%-106%, and precision, assessed as relative standard deviation below 20%. The MSPD significantly reduced samples and solvents' consumption, providing critical environmental gains compared to traditional extraction methods like Soxhlet. Finally, the method was applied to analyze sediment samples from three different collection areas of the Subachoque River (Cundinamarca, Colombia), demonstrating a fast, efficient, confident, and profitable analytical tool for pollution control and monitoring in environmental samples. The method allowed us to determine the current use in Colombia of banned pesticides under the 2001 Stockholm Convention.
Assuntos
Praguicidas , Cromatografia Gasosa-Espectrometria de Massas/métodos , Compostos Organofosforados/análise , Praguicidas/análise , Rios , Extração em Fase Sólida/métodos , Espectrometria de Massas em Tandem/métodosRESUMO
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.