Journal of separation science最新文献

This study introduces an innovative method for continuous multistage liquid–liquid extraction. Addressing challenges like coalescence and settling times that limit efficiency makes centrifugal partition extraction a promising technique for continuous product separation. It combines the benefits of a mixer-settler cascade with centrifugal extractors in one compact apparatus. The working principle is based on centrifugal partition chromatography, where two immiscible liquid phases are contacted inside a rotor, one serving as the mobile phase and the other as the stationary phase. In centrifugal partition extraction, both phases are mobile. The rotating apparatus allows dispersion and reduces settling time compared with static settlers, with its 300 times higher acceleration. To overcome constructional challenges, a novel concept, termed counter-current centrifugal extraction, is introduced in this work. Thereby, the primary objective is to validate the hypothesis that the process is feasible with a modified rotor design consisting of 10 chambers connected by individual ducts. Combined with alternating pump directions, this enables a pseudo-continuous counter-current flow. A proof of concept is investigated using computational fluid dynamics. The methodologies employed yield valuable insights into hydrodynamic performance. Based on these simulations, an optimized geometry for the flow area is developed, where 100% of the total chamber height is utilized as a dispersion zone compared with the previous 45%. The improvements result in elliptical chambers inclined at 35° to the radial direction, with a height of 6 mm and a volume of 1.43 mL. Additionally, baffles are placed inside the chambers opposite to the two inlets, enhancing dispersion of the inflowing phases. Finally, during alternating operation mode, it is demonstrated that ducts with a volume of 0.17 mL lead to an alternating phase ratio between 0.48 and 0.57 inside the chambers, which was repeatable over five simulated switches. This confirms the feasibility of the concept proposed based on hydrodynamics.

This study examined an improved and simplified method for solid-phase extraction that provides rapid and accurate determination and identification of 116 pharmaceutical and personal care products (PPCPs) in an aqueous environment using ultra-high performance liquid chromatography-tandem mass spectrometry. The common active compounds include 22 sulfonamides, 18 quinolones, 8 macrolides, 18 β-agonists, 6 sedative-hypnotics, 3 antipyretic-analgesics, 3 antihypertensives, 2 antidiabetic drugs, 3 antihistamines, 8 sex hormones, 2 antivirals, 6 nitroimidazoles, 8 glucocorticoids, and 3 amphenicols, lincomycin, pimaricin, levothyroxine sodium, bisphenol A, aldosterone, and melamine in water samples. Key parameters of tandem mass spectrometry, ultra-high performance liquid chromatography, and solid-phase extraction were optimized to enhance the analytical performance. The calibration curves were accomplished at seven concentration levels, and a satisfactory linear relationship (R > 0.99) was observed within the range of 5–800 ng/mL. Results showed varying limits of detection (0.0136–13.3 ng/L for different analytes based on signal-to-noise (S/N) = 3) and limits of quantitation (0.0452–44.4 ng/L). Recoveries of the spiked samples ranged from 53.1% to 116.5% with relative standard deviation lower than 9.9%. This approach effectively minimized matrix interference, improved extraction efficiency, and enhanced detection sensitivity, enabling more accurate PPCP residue analysis in water. The validated method was applied to raw water, treated water, and river water samples from Hangzhou, detecting 47 compounds at concentrations ranging from nondetected to 359 ng/L. Our findings provided critical technical support for the preliminary establishment of an environmental monitoring system targeting emerging pollutants. Notably, to the best of our knowledge, this study represented the first reported detection of melamine, loratadine, aldosterone, and levothyroxine sodium in aquatic environments. In particular, melamine was detected in aquatic environment for the first time, thus expanding the understanding of PPCPs’ pollution status.

Wastewater-based epidemiology (WBE) concerns the analysis of human biomarkers in untreated sewage samples as indicators of diseases, exposure to pollutants, and population lifestyle. Smoking, in various forms, and its prevalence in society are essential aspects of such studies. Anatabine, anabasine, cotinine, and hydroxycotinine are the most well-known nicotine biomarkers, and the relation of their concentrations with the smoking prevalence has been used in WBE studies. Analysis of these compounds has been based on LC–MS following classical solid or liquid extractions. Regarding the complexity of the sewage samples, the final chromatograms are still plagued by a large number of contaminants, despite the use of tandem or high-resolution MS detectors. In this work, a novel headspace SPME-Arrow extraction method has been developed, optimized, and validated for determining four nicotine metabolites in raw sewage medium. A Box–Behnken design was used to assess the significance of temperature, pH and ionic strength as three factors influencing the extraction efficiency and also to optimize the experimental conditions. The effect of extraction time and its optimum value were determined individually. The optimized sample preparation method followed by GC–MS (SIM) was shown to be sensitive enough to analyze the analytes at their actual concentration levels (ng–µg L⁻¹), thanks to ng L⁻¹ LOQs and linear calibration up to 40 µg L⁻¹. A raw sewage sample was also used to evaluate the accuracy and validate the method, with relative recoveries ranging from 87% to 103% for the spiked real sample at 400 ng L⁻¹. The entire analytical procedure and the sample preparation step were assessed for their greenness, based on AGREE and AGREEprep models, respectively. Results showed that not only can this method be considered an alternative to SPE-LC–MS methods, but it is also more environmentally friendly due to its automation and solventless nature.

Tetrahydromethyltestosterone (THMT) and 20-hydroxymethyl-18-nortetrahydromethyltestosterone (20OHnorTHMT) are metabolites of the anabolic androgenic steroids methyltestosterone and metandienone. Both molecular structures are used as markers in anti-doping analysis. There are eight reasonable diastereomeric structures of each group relevant for metabolic purposes. Highly sophisticated mass spectrometers fail to confidently differentiate these closely related, yet non-isomeric and non-isobaric groups of molecules. Due to the low abundance of the molecular ion, high-resolution mass spectrometry provides shared fragment ions that challenge identification by extracted ion chromatograms out of full scan mode acquisitions. Further on, tandem mass spectrometry uses partly the same ion transitions for both groups of targeted analytes. Thus, a reliable chromatographic separation is absolutely necessary. Therefore, a gas chromatographic method using a DB-5 ms capillary column (30 m, 0.25 mm, and 0.25 µm) was developed. Hence, discrimination between the two groups was enabled, and a confident structural assignment among the eight diastereomers was achieved. This case study contributes to a higher quality of anti-doping analysis, but even further raises awareness of the importance of chromatographic separation in cases of insufficient mass spectrometric discrimination.

An environmental friendly, fast, easy and inexpensive pH-switchable hydrophobic deep eutectic solvent-based liquid phase microextraction procedure was developed and combined with HPLC-UV detection for the extraction and analysis of morphine and codeine in whole blood samples. In this method, seven deep eutectic solvents were synthesized and then their switchability with pH was investigated. Deep eutectic solvents that could be switched with pH were used as extractant. Under the optimum conditions, relative standard deviation values for intra-day and inter-day of the method based on seven replicate measurements of 50 μg L^-1 of morphine and codeine in blood samples were in the range of 3.7-4.3% and 5.4-6.2%, respectively. The calibration graphs were linear in the range of 1.5-300 μg L^-1 and limit of detection for both analytes was 0.5 μg L^-1. The enrichment factor and the extraction recovery of morphine and codeine were in the ranges of 152-166, and 76-83%, respectively. The results showed that both morphine and codeine were detected in the blood sample of the addicted person. The relative recoveries of real blood samples which have been spiked with different levels of morphine and codeine were 91.8-107.0%. This article is protected by copyright. All rights reserved.

The technical progress of metabolomics—the analysis of metabolite composition of cells, tissues, and biofluids—and its ability to unravel phenotypical responses of organisms to their environment was accompanied by the democratization of their use in a wide range of scientific fields. While the reliability of analytical procedures was thoroughly assessed, the effects of preanalytical processing on sample metabolic profiles (i.e., conditioning, storage, transportation, etc.) remain quite unclear. This uncertainty is especially notable for samples collected in the frame of ecological studies, which often involve field sampling and remote sample production, leading to extended transportation durations and suboptimal storage conditions. In this study, we evaluated the impact of storage duration and temperature, along with the effects of freeze-drying (or lyophilization; the process of stabilization through dehydration by sublimation), on the metabolic profiles of samples relevant to ecological studies. Specifically, we focused on the lesser mealworm (Alphitobius diaperinus), the fruit fly (Drosophila melanogaster), and the perennial ryegrass (Lolium perenne). The levels of 60 different metabolites were quantitatively analyzed using targeted metabolomics through gas chromatography–mass spectrometry (GC–MS). We report significant metabolic shifts associated with freeze-drying, resulting in both increases and decreases in the contents of more than half of the quantified metabolites across all assessed chemical families. Several amino acids exhibited more than a fourfold increase in all investigated matrices. Furthermore, while samples stored at −80°C exhibited profiles most similar to those of samples analyzed right after collection, the metabolic profiles of these samples gradually changed over the 6 months of storage. Interestingly, metabolic shifts related to sample preanalytical processing and storage were relatively consistent across the biological matrices studied, particularly between the two insect species. Based on these observations, we propose several recommendations for reliable preanalytical sample processing in ecological studies, considering logistical and economic constraints.

Obtaining an insight into the composition of fuel and process intermediates samples is important for monitoring of the product quality, production and exploitation process improvement and complying with industry and environmental regulations. A broadband vacuum ultraviolet (VUV) spectroscopy detector has been successfully hyphenated with both GC and comprehensive two-dimensional gas chromatography (GC×GC) for the analysis of various fuel samples. This detector possesses both qualitative and quantitative capabilities. Most compounds absorb in the vacuum ultraviolet spectral range, and they exhibit rich and distinctive spectral features. Main constituents of fuel samples, hydrocarbons, such as paraffins, olefins, naphthenes, aromatics are identified with the VUV with very good selectivity. As data obtained from the GC×GC-VUV analysis of fuels can be challenging to exploit due to the sample complexity, it can be useful to employ chemometric methods for fuel composition exploration in a fast and efficient manner. In this work, 14 gas oil samples were analysed by GC×GC-VUV and after suitable data preprocessing, a pixel-based approach combined with k-means clustering was applied in order to classify compounds’ spectra into major hydrocarbon families in each sample and obtain a semi-quantification result which was then compared with the results of mass spectrometry analysis and quantitative GC×GC-VUV that involved application of detailed identification templates and response factors. It was demonstrated that due to hydrocarbon families exhibiting similar VUV absorbance spectra, the proposed workflow for GC×GC-VUV data preprocessing and analysis can be a fast and efficient way for gas oils global composition exploration.