Reduced Solvent Consumption Research Articles

Determination of AY 23 dye using magnetic solid-phase extraction coupled with spectrophotometry: Application of greenness and blueness assessment tools

This study developed an eco-friendly magnetic solid-phase extraction (MSPE) method coupled with spectrophotometry (MSPE-UV–Vis) for the preconcentration and determination of Acid Yellow 23 (AY 23) dye in syrup drink samples. Graphene oxide/cobalt oxide/iron oxide magnetic nanoparticles (GO-MNPs) were synthesized via photo-irradiation and employed as adsorbents. Under optimal conditions, the linear range was 0.2–5 mg/L, the limit of detection (LOD) was 0.0104 mg/L, and the limit of quantification (LOQ) was 0.0314 mg/L, with good sensitive values of preconcentration factor (25) and enhancement factor (6). This highlights the successful extraction and concentration of AY 23 dye into a small volume of 1 mL of 0.01 N NaOH through the MSPE process at 3 min. The kinetic experiment showed that the adsorption follows pseudo-second-order (PSO) kinetics, while the isotherm experiment followed the Langmuir isotherm model. The application of greenness and blueness assessment tools (AES, GAPI, AGREE, and BAGI) confirmed that MSPE can be considered a green chemistry method. The proposed MSPE-UV–Vis method offers advantages such as low cost, simplicity, reduced solvent consumption, and minimal environmental impact, making it a promising alternative to conventional methods for AY 23 dye analysis.

Development of a single-unit SMB process for clean production of 2’-fluoro nucleoside phosphoramidites to be used as the key building blocks of antisense oligonucleotide drugs and mRNA-vaccine capping primers

Due to the recent increase in incurable diseases and the pandemic of COVID-19, there have been global interests in antisense 2’-fluoro modified oligonucleotide drugs and mRNA-vaccine capping primers. To ensure stable and economical production of these oligonucleotides and primers, it is essential to establish a reliable process for securing a large amount of their corresponding monomer (2’-fluoro nucleoside phosphoramidite, abbreviated as “2’F-NP” hereafter) at high purity (> 99%) from the output of the relevant reaction. Currently, this task has been handled using two-stage separation processes (extraction and chromatography in series) based on batch (non-continuous) modes, which, however, had the problems of excessive solvent consumption and low yield. For cleaner production of 2’F-NP, these problems should be resolved. To address such issue, this study aimed to develop a new single-step process that can recover 2’F-NP at once in a continuous mode at high purity. For this purpose, we introduced a simulated-moving-bed (SMB) method into the development phase of the targeted 2’F-NP recovery process, and further established the appropriate SMB configuration and solvent-gradient strategy to continuously remove all the impurities at once. The SMB mode process determined based on such considerations was then optimized using the intrinsic parameters estimated, the regeneration method explored, and the optimization tool prepared. The relevant SMB experiment was carried out, which confirmed that the developed process in this study was quite effective in continuous-mode recovery of 2’F-NP at high purity (99.5%) and high yield (96.5%) without the aid of a further process, thereby enabling a significant reduction in solvent consumption. The results in this paper will thus contribute to the clean and eco-friendly production of 2’F-NP, which will also be of benefit to antisense oligonucleotide drug and mRNA-vaccine capping primer production processes.

Porous Polymer Sorbents in Micro Solid Phase Extraction: Applications, Advantages, and Challenges.

In recent years, porous polymers have gained significant attention for their application as powerful and selective sorbents in micro solid phase extraction (µSPE). In this review we explore the preparation and utilization of various porous polymer sorbents, highlighting their impact on enhancing µSPE techniques. Molecularly imprinted polymers (MIPs), graphene oxide-modified frameworks, and zeolitic imidazole frameworks (ZIFs) are among the innovative materials discussed. These innovative materials have significantly improved µSPE methods, offering enhanced extraction efficiencies, superior selectivity, and reduced solvent consumption, all of which align with the principles of green chemistry. Key findings of this review include the demonstration that MIPs exhibit excellent target specificity, making them ideal for complex matrices, while graphene oxide frameworks and ZIFs provide increased surface area and stability for diverse analytical applications. Despite these advancements, challenges remain, particularly the high cost of certain innovative materials, limited reusability, and the absence of automation in µSPE workflows. Furthermore, controlling the precise synthesis and functionalization of these sorbents continues to be a limiting factor. To address these issues, future research should focus on developing cost-effectiveness methods, the use of biopolymer or sustainable feedstocks, and scalable synthesis methods; integrating automation into µSPE; and exploring new polymeric materials with enhanced properties. Additionally, novel hybrid materials that combine the strengths of multiple sorbents offer a promising direction for future exploration. We critically analyze the advantages and limitations of each sorbent type, providing a comprehensive overview of their applications in µSPE. This paper also examines the synthesis, characterization, and unique properties of these porous polymers, emphasizing their role in advancing analytical chemistry towards more efficient and environmentally friendly practices. The need for continued development of high-performance, low-cost, and sustainable sorbents is underscored to further enhance the effectiveness of µSPE techniques.

Leveraging the potential of 1.0-mm i.d. columns in UHPLC-HRMS-based untargeted metabolomics.

Untargeted metabolomics UHPLC-HRMS workflows typically employ narrowbore 2.1-mm inner diameter (i.d.) columns. However, the wide concentration range of the metabolome and the need to often analyze small sample amounts poses challenges to these approaches. Reducing the column diameter could be a potential solution. Herein, we evaluated the performance of a microbore 1.0-mm i.d. setup compared to the 2.1-mm i.d. benchmark for untargeted metabolomics. The 1.0-mm i.d. setup was implemented on a micro-UHPLC system, while the 2.1-mm i.d. on a standard UHPLC, both coupled to quadrupole-orbitrap HRMS. On polar standard metabolites, a sensitivity gain with an average 3.8-fold increase over the 2.1-mm i.d., along with lower LOD (LODavg 1.48ng/mL vs. 6.18ng/mL) and LOQ (LOQavg 4.94ng/mL vs. 20.60ng/mL), was observed. The microbore method detected and quantified all metabolites at LLOQ with respect to 2.1, also demonstrating good repeatability with lower CV% for retention times (0.29% vs. 0.63%) and peak areas (4.65% vs. 7.27%). The analysis of various samples, in both RP and HILIC modes, including different plasma volumes, dried blood spots (DBS), and colorectal cancer (CRC) patient-derived organoids (PDOs), in full scan-data dependent mode (FS-DDA) reported a significant increase in MS1 and MS2 features, as well as MS/MS spectral matches by 38.95%, 39.26%, and 18.23%, respectively. These findings demonstrate that 1.0-mm i.d. columns in UHPLC-HRMS could be a potential strategy to enhance coverage for low-amount samples while maintaining the same analytical throughput and robustness of 2.1-mm i.d. formats, with reduced solvent consumption.

Simultaneous estimation of prasugrel and aspirin in bulk drugs by chemometric methods

A UV–Vis spectrophotometric method enhanced by chemometric techniques, specifically Principal Component Regression (PCR) and Partial Least Squares (PLS) regression, was developed and validated for the simultaneous quantification of prasugrel (PRA) and aspirin (ASP) in bulk drugs and pharmaceutical formulations. The method demonstrated high accuracy, precision, and robustness, achieving mean recoveries of 100.63% for PRA and 100.08% for ASP with relative standard deviations (RSD) below 3%. Both PCR and PLS models showed excellent predictive capabilities, with RMSEP values of 0.45–0.48 for PRA and 0.78–1.13 for ASP, indicating the models’ reliability. In line with green and white chemistry principles, the method minimizes environmental impact by reducing solvent consumption and waste generation compared to traditional chromatographic methods. The Analytical Eco-Scale score was 84, reflecting excellent compliance with green chemistry standards. The method’s simplicity, low energy consumption, and reduced chemical waste further support its alignment with sustainability goals. However, acetonitrile, a hazardous solvent, was still used in small quantities, and solvent recycling was not implemented, slightly affecting the eco-score. To evaluate the method’s greenness, the RGB12 algorithm was applied, achieving a high score of 94.4%, with the majority of parameters related to reagent consumption, waste production, energy efficiency, and safety scoring optimally. The method’s safety, cost-effectiveness, and minimal environmental footprint make it suitable for routine pharmaceutical analysis, particularly in quality control environments where resource efficiency and sustainability are prioritized. Thus, the developed method offers a sustainable, efficient, and environmentally friendly solution for the simultaneous analysis of prasugrel and aspirin in pharmaceutical formulations, making it a valuable tool for routine analysis in the pharmaceutical industry.

Evaluating the reliability of solid phase extraction techniques for hydrocarbon analysis by GC–MS

Saturate and aromatic compounds are essential in the petroleum industry for assessing the thermal maturity of source rocks and oils, which is critical for basin modeling and sweet-spot mapping. These compounds also play a role in environmental applications, such as oil spill fingerprinting and biogeochemistry. However, the analysis of these compounds by gas chromatography-mass spectrometry (GC–MS) requires meticulous and time-consuming separation processes. Traditional methods like normal-phase liquid column chromatography (LCC) involve large volumes of harmful solvents. This study evaluates the effectiveness of five different sorbents using solid-phase extraction (SPE) techniques—neutral Si, SiOH, Ag-ion, neutral Al, and Ag-ion mixed with activated silica—compared to LCC. The goal was to discern differences in peak resolution, concentration, and isomer ratios of saturate and aromatic compounds for thermal maturity and source rock assessments. The results show that SiOH, neutral Si, and neutral Al do not fully separate aromatic compounds from the saturate fraction, sometimes leaving 40–100% of aromatics within the saturate fraction. Ag-ion mixed with activated silica provided the best separation, resulting in up to 23 times higher aromatic concentration than SiOH. This method is more reliable for quantifying both saturate and aromatic compounds, increases the efficiency of hydrocarbon evaluations, and reduces solvent consumption by 63%, offering a more sustainable approach to hydrocarbon analysis.

RECENT ADVANCES IN GAS, LIQUID AND SUPERCRITICAL FLUID CHROMATOGRAPHY IN THE CONTEXT OF SUSTAINABLE/ GREEN CHEMISTRY

Background: Chromatographic techniques such as gas chromatography (GC), liquid chromatography (LC) and supercritical fluid chromatography (SFC) have long been employed in analytical chemistry. However, using or producing certain organic solvents and non-renewable gases is hazardous to the environment. Green chemistry is essential for addressing the environmental hazards associated with traditional procedures. Objectives: This review focuses on recent updates and profound insights into new, greener techniques introduced in GC, LC and SFC. Methodology: To compile this review, several electronic databases were searched, preferably from January 2019-December 2023. Results: This review highlights advancements in miniaturization, rapid methods, and eco-friendly solvents in chromatographic techniques. Integrating micro-electro-mechanical systems (MEMS) and nano-electro-mechanical systems (NEMS) in GC enhances sensitivity and resolution while reducing solvent consumption. Innovations like monolithic micro-GC chips and the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method further streamline analysis times. In LC, supercritical fluids are utilized as green mobile phases, optimizing techniques like electrochemical flow liquid chromatography (EFLC), high-performance liquid chromatography (HPLC), and ultra-high-performance liquid chromatography UHPLC. In contrast, SFC employs rapid methods, such as ultra-high-performance supercritical fluid chromatography-mass spectrometry (UHPSFC-MS). These developments collectively promote sustainability and efficiency in chromatographic practices. Conclusion: Green chromatography has become an essential tool in pharmaceutical analysis because it safeguards the operator’s health and the environment. It opens new horizons and generates new ideas for further experimentation while focusing on recent cutting-edge green technologies incorporated in GC, LC and SFC. These advancements significantly enhance safety and sustainability in analytical practices.

THE INDUSTRIAL IMPORTANCE OF TECHNOLOGY TRANSFER FOR ANALYTICAL METHOD DEVELOPMENT AND VALIDATION–APPLICATION TO VILAZODONE HYDROCHLORIDE DOSAGE FORM

Objective: The research aims to create a fast, economical, and efficient tech transfer method for analyzing bulk materials and pharmaceutical dosage forms. Methods: The analysis was performed using an Acquity UPLC BEH C18 analytical column (130 Å, 1.7 µm, 3 mm x 100 mm) with detection of the analyte at 238 nm. The mobile phase flow rate was optimized at 0.3 ml/min, and an injection volume of 0.5 µl** was used. The isocratic mobile phase consisted of a blend of buffer (0.1% OPA) and acetonitrile at a ratio of 40:60% v/v. Results: All validation parameters of the analytical method were acceptable. The analyte eluted at 3.08 min with satisfactory theoretical plates and a tailing factor. The recovery of the analyte was 99-100%, and the method's precision was 0.59 and 0.72% RSD. The technique showed no interference, indicating specificity. The linearity was demonstrated over the 20-60 µg/ml range, with a regression coefficient of 0.999. Conclusion: The developed method is cost-effective, specific with minimal interference, and time-saving. It also reduces solvent consumption for quality control analysis of vilazodone hydrochloride samples. The method demonstrates good linearity, robustness, and accuracy.

Developments and Applications of Molecularly Imprinted Polymer-Based In-Tube Solid Phase Microextraction Technique for Efficient Sample Preparation.

Despite advancements in the sensitivity and performance of analytical instruments, sample preparation remains a bottleneck in the analytical process. Currently, solid-phase extraction is more widely used than traditional organic solvent extraction due to its ease of use and lower solvent requirements. Moreover, various microextraction techniques such as micro solid-phase extraction, dispersive micro solid-phase extraction, solid-phase microextraction, stir bar sorptive extraction, liquid-phase microextraction, and magnetic bead extraction have been developed to minimize sample size, reduce solvent usage, and enable automation. Among these, in-tube solid-phase microextraction (IT-SPME) using capillaries as extraction devices has gained attention as an advanced "green extraction technique" that combines miniaturization, on-line automation, and reduced solvent consumption. Capillary tubes in IT-SPME are categorized into configurations: inner-wall-coated, particle-packed, fiber-packed, and rod monolith, operating either in a draw/eject system or a flow-through system. Additionally, the developments of novel adsorbents such as monoliths, ionic liquids, restricted-access materials, molecularly imprinted polymers (MIPs), graphene, carbon nanotubes, inorganic nanoparticles, and organometallic frameworks have improved extraction efficiency and selectivity. MIPs, in particular, are stable, custom-made polymers with molecular recognition capabilities formed during synthesis, making them exceptional "smart adsorbents" for selective sample preparation. The MIP fabrication process involves three main stages: pre-arrangement for recognition capability, polymerization, and template removal. After forming the template-monomer complex, polymerization creates a polymer network where the template molecules are anchored, and the final step involves removing the template to produce an MIP with cavities complementary to the template molecules. This review is the first paper to focus on advanced MIP-based IT-SPME, which integrates the selectivity of MIPs into efficient IT-SPME, and summarizes its recent developments and applications.

Red beet betalains extraction process: A comprehensive review of methods, applications, and physicochemical properties.

Red beet extract is rich in bioactive compounds and possesses health-promoting properties. Moreover, the stability of red beet extract over a broad acidic pH range has given them great potential in developing new functional foods and drinks. The choice of extraction solvent and methodology significantly influences the efficiency of betalain extraction from plant vacuoles. Although the conventional solvent extraction method has been widely employed for betalain extraction, recent innovations have introduced alternative methods that offer advantages, such as reduced solvent consumption, energy efficiency, and minimized exposure to high temperatures. This paper aims to summarize the current knowledge about conventional and novel extraction methods, applications, biological activities, and purification of red beet betalains. Furthermore, the physicochemical properties of betalain-rich extract of red beet and associated safety considerations have been investigated.

Reducing Solvent Consumption in Reductive Catalytic Fractionation through Lignin Oil Recycling.

Reductive catalytic fractionation (RCF) enables the simultaneous valorization of lignin and carbohydrates in lignocellulosic biomass through solvent-based lignin extraction, followed by depolymerization and catalytic stabilization of the extracted lignin. Process modeling has shown that the use of exogenous organic solvent in RCF is a challenge for economic and environmental feasibility, and previous works proposed that lignin oil, a mixture of lignin-derived monomers and oligomers produced by RCF, can be used as a cosolvent in RCF. Here, we further explore the potential of RCF solvent recycling with lignin oil, extending the feasible lignin oil concentration in the solvent to 100 wt %, relative to the previously demonstrated 0-19 wt % range. Solvents containing up to 80 wt % lignin oil exhibited 83-93% delignification, comparable to 83% delignification with a methanol-water mixture, and notably, using lignin oil solely as a solvent achieved 67% delignification in the absence of water. In additional experiments, applying the RCF solvent recycling approach to ten consecutive RCF reactions resulted in a final lignin oil concentration of 11 wt %, without detrimental impacts on lignin extraction, lignin oil molar mass distribution, aromatic monomer selectivity, and cellulose retention. Overall, this work further demonstrates the potential for using lignin oil as an effective cosolvent in RCF, which can reduce the burden on downstream solvent recovery.

Sustainable approaches to analyzing phenolic compounds: a green chemistry perspective.

Innovative and eco-friendly methodologies for the determination of phenolic compounds, showing a paradigm shift in analytical chemistry toward sustainability. Phenolic compounds, valued for their diverse health benefits, have historically been analyzed using methods that often involve hazardous solvents and energy-intensive processes. This review focuses on green analytical chemistry principles, emphasizing sustainability, reduced environmental impact, and analytical efficiency. The use of DES, specifically Ch: Chl-based DES, emerges as a prominent green alternative for extracting phenolic compounds from various sources. The integration of UAE with DES enhances extraction efficiency, contributing to a more sustainable analytical approach. Furthermore, the review highlights the significance of DLLME and SPME in reducing solvent consumption and simplifying extraction procedures. These techniques exemplify the commitment to making phenolic compound analysis environmentally friendly. The incorporation of portable measurement tools, such as smartphones, into analytical methodologies is a notable aspect discussed in the review. Techniques like UA-DLLME leverage portable devices, making phenolic compound determination more accessible and versatile. Anticipating the future, the review foresees ongoing advancements in sustainable analytical approaches, driven by collaborative efforts across diverse disciplines. Novel solvents, extraction techniques, and portable measurement methods are expected to play pivotal roles in the continuous evolution of green analytical methodologies for the analysis of phenolic compounds. The review encapsulates a transformative journey toward environmentally responsible and efficient analytical practices, paving the way for further research and application in diverse analytical settings.

Development and validation of an ultrafast method of quantification of rivaroxaban in human serum using laser diode thermal desorption coupled to triple quadrupole mass spectrometry.

Rivaroxaban is an anticoagulant prescribed to patients who are at risk of medical conditions such as deep-vein thrombosis, pulmonary embolisms, and strokes caused by blood clots. The administration of this drug is monitored to adjust the dosage and evaluate patients' blood concentration. Rapid quantification of this drug in plasma could make it possible to ensure that the dose present in the blood of patients does not represent a danger for the medical intervention to be carried out. Liquid chromatography-tandem mass spectrometry is usually employed to quantify rivaroxaban in blood, plasma, and serum. Here, an alternative method of analysis based on laser diode thermal desorption-triple quadrupole mass spectrometry (LDTD-QqQMS) was developed and comprehensively validated. This new method allows the quantification of rivaroxaban in less than 13 s from sample to sample. The extraction of rivaroxaban in human serum was done by a salting-out liquid-liquid extraction with acetonitrile and a saturated sodium chloride solution. The proposed method allows the quantification of rivaroxaban in less than 13 s from sample to sample. During validation, all criteria were respected. The accuracy was <15% of the nominal value, the precision was <15%CV, and the recovery was ≥89.9%. There were no observed carryover or matrix effects. Analysis of the extracted samples established the stability of dry (24 h) and wet samples (1week) when samples cannot be analyzed immediately, a considerable advantage in a clinical setting. This method improves sample throughput by more than 1200% compared to liquid chromatography-tandem mass spectrometry methods of analysis of rivaroxaban and decreases analysis costs by reducing solvent consumption and instrument time.

Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially saving countless hours of labor while also reducing solvent consumption and waste. Tasks such as physicochemical screening and preliminary method screening systems where large amounts of chromatography data are collected from fast and routine operations are particularly well suited for both leveraging large datasets and benefiting from predictive models. Therefore, the generation of predictive models for retention time is an active area of development. However, for these predictive models to gain acceptance, researchers first must have confidence in model performance and the computational cost of building them should be minimal. In this study, a simple and cost-effective workflow for the development of machine learning models to predict retention time using only Molecular Operating Environment 2D descriptors as input for support vector regression is developed. Furthermore, we investigated the relative performance of models based on molecular descriptor space by utilizing uniform manifold approximation and projection and clustering with Gaussian mixture models to identify chemically distinct clusters. Results outlined herein demonstrate that local models trained on clusters in chemical space perform equivalently when compared to models trained on all data. Through 10-fold cross-validation on a comprehensive set containing 67,950 of our company's proprietary analytes, these models achieved coefficients of determination of 0.84 and 3 % error in terms of retention time. This promising statistical significance is found to translate from cross-validation to prospective prediction on an external test set of pharmaceutically relevant analytes. The observed equivalency of global and local modeling of large datasets is retained with METLIN's SMRT dataset, thereby confirming the wider applicability of the developed machine learning workflows for global models.

Design of PVDF hollow fiber membranes with stable crystalline and porous structure by solvent‐free method

AbstractOne of the critical principles of green chemistry and environmental sustainability is to avoid using harmful solvents in chemical processes. In this study, a novel solvent‐free method was employed to prepare poly (vinylidene fluoride) (PVDF) hollow fiber composite membranes with stable crystalline and porous structures. Utilizing the cold‐hot stretching method, the crystalline structure and orientation of PVDF were effectively redesigned, resulting in improved mechanical and penetration properties of the membrane. Additionally, an investigation into the internal crystalline structure of the PVDF hollow fiber membrane was conducted, focusing on crystalline changes induced by ion‐dipole interactions. Results indicated that the addition of neutral ion‐dipole functional particles (N‐P) promoted the conversion of α crystalline to β crystalline, leading to stable β crystalline and controllable pore sizes in the prepared PVDF hollow fiber membrane. Furthermore, the internal crystalline structure significantly contributed to enhancing the membrane's mechanical properties and penetration performance. Notably, a PVDF hollow fiber with high β crystalline content was achieved through 150% cold‐hot stretching and the addition of 20. wt% N‐P further enhanced the β‐crystalline content in the membrane. This study presents a promising approach for reducing solvent consumption and minimizing environmental impact in the field of environment‐friendly membrane fabrication.

Combining EDTA-intercalated (Zn-Al) layered double hydroxides/graphite and two-phase hollow fiber for liquid phase microextraction of nonsteroidal anti-inflammatory drugs

This study synthesized and characterized layered double hydroxides (LDHs) intercalated with ethylenediaminetetraacetic acid(EDTA) to increase the basal spacing of electrosynthesized Zn-Al-LDHs on pencil graphite (PG). The characteristic verification of the Zn-Al-EDTA-LDH nanostructures was conducted utilizing Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), energy dispersive and X-ray analysis (EDS), and X-ray diffraction (XRD). To improve the extraction efficiency, Zn-Al-EDTA-LDHs as adsorbent in solid phase microextraction (SPME) fiber was combined with hollow fiber liquid–liquid phase microextraction (HF-LLPME) to investigate the extraction efficiency of HF-LLME@PG-SPME technique the chosen non-steroidal anti-inflammatory drugs (NSAIDs) from aqueous solution Several variables, comprising extraction time, desorption time, stirring rate, desorption volume, pH of donor phase, and salt effects were screened and optimized by performing placket-Burman design (PBD). After evaluating the extraction and desorption procedures under optimal conditions, NSAIDs analysis was performed employing high-performance liquid chromatography-ultraviolet detection (HPLC-UV). Compared to the most common clean-up and sample preparation methods, the current study focused on developing a greener analytical chemistry process due to reduced solvent consumption, cost-effectiveness, miniaturization and simplified design. The proposed method for NSAIDs exhibited a good linear dynamic range (LDRs) (1.00–200.00 µg/L) with a coefficient of determination of > 0.9956, low limits of detection (LODs) (0.26–0.29 µg/L) and acceptable limits of quantifications (LOQs) (0.86–0.96 µg/L). Relative standard deviations of 5.31 % could be determined. The absolute recoveries of the urine sample analyses could be obtained in a 89.91–97.61 % range and enrichment factors (EFs) (178.92 to 183.88). Investigations of the developed method were also conducted in various urine samples containing the selected drugs. As a result of the obtained recoveries, the method proved to be valuable and suitable to complicated biological samples.

Micro-solid phase extraction of pharmaceuticals and illicit drugs from wastewaters using monolith-coated syringe filters

In this study, a porous monolith of poly(methacrylic acid-co-ethylene glycol dimethacrylate) has been prepared on the nylon membrane of a commercial syringe filters (13 mm, 0.22 µm) for the micro solid-phase extraction (µSPE) of pharmaceutical and illicit drugs from wastewater samples prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) determination. Polymer synthesis conditions were designed and adjusted to provide robust devices with reduced costs and ease of use. The performance of the developed devices was assessed by investigating the most appropriate µSPE conditions. The features of the proposed device allow for the extraction of sample volumes up to 25 mL of wastewater and the use of minimal amounts of organic solvents (200 µL of 0.1 % formic acid in methanol) in the desorption step, providing a 125 enrichment factor. Sample extracts were measured by LC-MS/MS, providing limits of detection from 2 to 22 ng/L, recoveries from 84 to 120 %, and relative standard deviations lower than 16 %. The proposed approach has demonstrated to be suitable for the easy and simple extraction of forty-two psychoactive substances from wastewater samples with a reduced solvent consumption, low cost, minimal environmental impact, and high enrichment capacity. The method greenness and practicality has been evaluated using AGREEprep, complexGAPI, and BAGI tools, demonstrating an adequate green character and practicality of the proposed methodology.

Optimizing Chromatographic Separation with Redosing: Effects on Separation Efficiency of a Model System in Centrifugal Partition Chromatography

This study investigates and optimizes chromatographic separation in a Centrifugal Partition Chromatograph. Therefore, a model system is separated in a single-disc rotor. The occurring loss of the stationary phase lowers the separation efficiency over time. We introduced a new mode of operation, called the redosing of the stationary phase, to counteract this hydrodynamic phenomenon. Experiments with redosing at an optimized operating point demonstrate almost constant separation performance over 12 h, reducing solvent consumption by 45% and increasing chromatographic resolution by 37%. The improvement in retention by 69% contributes to this enhancement. Accordingly, reference experiments without redosing were conducted as a benchmark, highlighting the automated mode’s benefits, as mentioned.

Development of a rapid screening method utilizing 2D LC for effect-directed analysis in the identification of environmental toxicants

Effect-directed analysis (EDA) is a crucial tool in environmental toxicology, effectively integrating toxicity testing with chemical analysis. The conventional EDA approach, however, presents challenges such as significant solvent consumption, extended analysis time, labor intensity, and potential contamination risks. In response, we introduce an innovative alternative to the conventional EDA. This method utilizes the MTT bioassay and online two-dimensional liquid chromatography (2D LC) coupled with high-resolution mass spectrometry (HR-MS), significantly reducing the fractionation steps and leveraging the enhanced sensitivity of the bioassay and automated chemical analysis. In the chemical analysis phase, a switching valve interface is employed for comprehensive analysis. We tested the performance of both the conventional and our online 2D LC-based methods using a household product. Both methods identified the same number of toxicants in the sample. Our alternative EDA is 22.5 times faster than the conventional method, fully automated, and substantially reduces solvent consumption. This novel approach offers ease, cost-effectiveness, and represents a paradigm shift in EDA methodologies. By integrating a sensitive bioassay with online 2D LC, it not only enhances efficiency but also addresses the challenges associated with traditional methods, marking a significant advancement in environmental toxicology research.

Enhancing the purification of crocin-I from saffron through the combination of multicolumn countercurrent chromatography and green solvents

Crocin-I, a valuable natural compound found in saffron (Crocus sativus L.), is the most abundant among the various crocin structures. Developing a cost-effective and scalable purification process to produce high-purity crocin-I is of great interest for future investigations into its biological properties and its potential applications in the treatment of neurological disorders. However purifying crocin-I through single-column preparative chromatography (batch) poses a yield-purity trade-off due to structural similarities among crocins, meaning that the choice of the collection window sacrifices either yield in benefit of higher purity or vice versa. This study demonstrates how the continuous countercurrent operating mode resolves this dilemma. Herein, a twin-column MCSGP (multicolumn countercurrent solvent gradient purification) process was employed to purify crocin-I. This study involved an environmentally friendly ethanolic extraction of saffron stigma, followed by an investigation into the stability of the crocin-I within the feed under varying storage conditions to ensure a stable feed composition during the purification. Then, the batch purification process was initially designed, optimized, and subsequently followed by the scale-up to the MCSGP process. To ensure a fair comparison, both processes were evaluated under similar conditions (e.g., similar total column volume). The results showed that, at a purity grade of 99.7%, the MCSGP technique demonstrated significant results, namely + 334% increase in recovery + 307% increase in productivity, and − 92% reduction in solvent consumption. To make the purification process even greener, the only organic solvent employed was ethanol, without the addition of any additive. In conclusion, this study presents the MCSGP as a reliable, simple, and economical technique for purifying crocin-I from saffron extract, demonstrating for the first time that it can be effectively applied as a powerful approach for process intensification in the purification of natural products from complex matrices.Graphical