Green Analytical Chemistry最新文献

{"title":"Composite microbeads of cellulose acetate upcycled from waste for water remediation","authors":"Lorenzo Antonelli ,&nbsp;Susanna Grasso ,&nbsp;Massimo Giuseppe De Cesaris ,&nbsp;Nina Felli ,&nbsp;Chiara Dal Bosco ,&nbsp;Stefano Cinti ,&nbsp;Alessandra Gentili","doi":"10.1016/j.greeac.2025.100283","DOIUrl":"10.1016/j.greeac.2025.100283","url":null,"abstract":"<div><div>The rising level of contaminants in the environment highlights the urgent need for the development of effective sorbents that can be applied to remediate contaminated water. Additionally, if sorbents can be prepared by recycling waste, this is a further added value. This study has aimed to develop a sustainable nanocomposite sorbent of cellulose acetate (CA), a bioplastic that can be recycled from different types of waste, including filters from cigarette butts. After an efficient cleaning protocol, the recovered CA was used to prepare microspheres via an emulsion precipitation technique, in combination with activated carbon as adsorption filler (20 % w/w). The sorption performance of this material was evaluated in flow-through systems, i.e. glass cartridges packed with the microspheres, by simulating a filter for water remediation at the laboratory scale. An experimental 2³ factorial design was performed to define the best operational conditions of the instrumental setup, defining the flow rate, amount and chemical nature of the packed microbeads. The adsorption performance was tested towards 40 common contaminants chosen as model compounds. To investigate the retention behaviour of the individual analytes, the Gompertz mathematical model was chosen, as it is useful for fitting the sigmoidal release pattern of contaminants from the packed cartridge. Competitive removal studies revealed differential retention based on analyte polarity, with retention capacities spanning from 2.2 − 4.2 µg of each contaminant per gram of sorbent, with a total loading capacity on the order of 125 µg/g_sorbent. The adsorption studies demonstrated the composite potential for water remediation operations, coupled with advantages in terms of recyclability and sustainability of the material.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100283"},"PeriodicalIF":0.0,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heptad green metrics and quality by design tool evaluated chromatography method for content determination of Bexagliflozin in formulation product","authors":"Satyajit Raj Nethekar ,&nbsp;Phani Raja Kanuparthy ,&nbsp;Leela Prasad Kowtharapu ,&nbsp;Vishnuvardhana Kishore Polisetti ,&nbsp;Pankaj Kumar Lahoti ,&nbsp;Sreekantha B Jonnalagadda ,&nbsp;Naresh Kumar Katari","doi":"10.1016/j.greeac.2025.100280","DOIUrl":"10.1016/j.greeac.2025.100280","url":null,"abstract":"<div><div>The study created an eco-friendly, rapid, sensitive, cost-efficient, stability-assessing method for analyzing Bexagliflozin in pharmaceuticals using a RP-UPLC approach. The method's specificity was achieved using an XBridge analytical column (100 mm x 2.1 mm, 3.5 µm) with a mobile phase consisting of 10 mM Ammonium acetate and Methanol in a ratio of 55:45 (v/v). The flow rate is 0.2 mL/min, the injection volume is 1 µL, and the UV detection wavelength is 220 nm. The total run time is 2.5 minutes. The technique was meticulously validated, strictly adhering to the ICH criteria, and demonstrated specificity, linearity, ruggedness, robustness, and accuracy. The technique robustness analysis was carried out by using the QbD tool to build DoE's and assess their robustness. The methodology exhibited a linear trend as the concentration level increased from 5µg/mL to 30ug/mL. The recovery process ranged from 50% to 150%, with the average recovery considered adequate. Method stability indicating nature proved by forced degradation study. Analytical Eco-scale value found 81. NEMI showing the three quadrants showing the green, Modified NEMI has only one red quadrant. GAPI have five green, 5 yellow and 5 red parts. Complex GAPI have 12 green, 7 yellow and 6 red parts in the whole pictogram. AGREE shown the quantitative value 0.64 and pictogram shown 7 green parts, three yellow parts and 2 red parts. Green metric tools NEMI, modified NEMI, GAPI, complex GAPI Eco-scale, AGREE, and AGREEprep are used to express the method's greenness.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100280"},"PeriodicalIF":0.0,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating artificial intelligence with miniature mass spectrometry","authors":"Jiayi Wang ,&nbsp;Lingyan Liu ,&nbsp;Ting Jiang","doi":"10.1016/j.greeac.2025.100281","DOIUrl":"10.1016/j.greeac.2025.100281","url":null,"abstract":"<div><div>Miniature mass spectrometers are increasingly being employed in various analytical fields due to their portability and low cost. Unlike lab-scale mass spectrometers, miniature mass spectrometers typically operate in environments that demand more automated analytical processes for on-site, real-time analysis. With the successful application of AI across different industries, researchers have started to integrate AI techniques into miniature mass spectrometry to enhance its capabilities. In this review, we provide an overview of the recent advancements in the intelligence of miniature mass spectrometers, focusing on intelligent sample identification and AI methods that enhance the instruments’ performance. These AI methods have not only improved the accuracy and efficiency of analysis but have also expanded the applications of miniature mass spectrometry to critical areas such as food safety, agricultural disease detection, and environmental monitoring. Moreover, we discuss the current challenges in advancing the intelligence of miniature mass spectrometers and explore the complexities involved in integrating AI with these devices. Finally, we offer our insights into future directions and potential solutions for overcoming these challenges.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100281"},"PeriodicalIF":0.0,"publicationDate":"2025-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainability in motion: Investigation of automated gravimetric sample preparation in industrial liquid chromatography","authors":"Mo Legelli ,&nbsp;Marcel Vranceanu ,&nbsp;Michaela Wirtz ,&nbsp;Stefan Lamotte","doi":"10.1016/j.greeac.2025.100279","DOIUrl":"10.1016/j.greeac.2025.100279","url":null,"abstract":"<div><div>For analysis with liquid chromatography (LC), samples and calibration standards generally require a dilution by a factor of 10³ to 10⁶. To guarantee a high accuracy, sample preparation usually employs high-volume pipettes and volumetric flasks for dilution series. Consequently, sample preparation is a prominent driving factor for consumption of solvents in the LC laboratory. Miniaturisation in sample preparation can thus be a means of reducing the required amount of solvent within the laboratory, saving valuable resources. In the context of dilution series, this can be achieved by the use of low-volume dispensing tools, which usually have a higher relative instrument error, resulting in a less accurate overall method. Another approach is the transition to a gravimetric sample preparation, in which the dilution steps are not measured in volume but weight, only depending on the much lower error of the analytical balance. By implementing weighing robots, one can fully automate the sample preparation workflow. This study deals with the comparison of various dilution methods. Gravimetric, robot-aided dilution allows for the reduction of the solvent down to the amount of sample needed for analyses. Including the initial dissolution of the sample, using gravimetric dilution can reliably and repeatedly reduce the required solvent amount by over 90 %, while still generating the same analytical results. Overall, this application leads to significant economic, ecological, social, and technological benefits for the LC laboratory.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100279"},"PeriodicalIF":0.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating electrochemical sensors in circular economy: biochar-film sensors based on paper industry waste for agri-food by-product valorization","authors":"Selene Fiori ,&nbsp;Annalisa Scroccarello ,&nbsp;Flavio Della Pelle ,&nbsp;Michele Del Carlo ,&nbsp;Enrico Cozzoni ,&nbsp;Dario Compagnone","doi":"10.1016/j.greeac.2025.100277","DOIUrl":"10.1016/j.greeac.2025.100277","url":null,"abstract":"<div><div>Sustainable nanostructured paper sensors (PS) have been developed to detect bioactive compounds in plant-derived agri-food by-products. These sensors comprise 100 % recycled fibers-paper and pulp industry-derived biochar and are produced using accessible, cost-effective technologies.</div><div>In detail, black liquor-derived biochar (BH) was nano-dispersed in water using an ultrasound-assisted liquid phase exfoliation-like approach, avoiding solvents. Self-standing BH-sensing nanofilms were formed directly on cellulosic membranes and integrated into stencil-printed complete electrochemical sensors manufactured on recycled paper. The biochar-based paper sensors (BH-PS) were optimized, characterized, and then employed to analyze bioactive phenols present in agri-food waste and derivatives, including cocoa and coffee husks, exhausted coffee powder, and olive leaves and artichoke production waste-based supplements.</div><div>BH-PS demonstrated robust performance, yielding dose-response curves for representative bio-compounds such as caffeic acid, catechin, chlorogenic acid, and oleuropein. These showed excellent linearities (R² ≥ 0.9946) and detection limits ranging from 0.03 to 0.6 µM. The sensors were successfully used to quantify biomolecules in agri-food wastes and derivatives, with results comparable to conventional photometric assays (r ≥ 0.99; relative error vs. AuNPs assay: -3 % to +14 %). The method produced quantitative and reproducible recoveries for all samples (97–114 %; RSD ≤ 13 %, n = 3). Finally, the superior sustainability of the BH-PS was validated using the White Analytical Chemistry framework, achieving a significantly higher score (94 %) compared to traditional colorimetric and chromatographic methods (60–80 %).</div><div>This work demonstrates a circular economy model, utilizing plant-derived waste exclusively to fabricate integrated paper sensors, that were then applied to determine high-value bioactive compounds in plant-derived agri-food by-products.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100277"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-mode glucose sensing: Colorimetric chemical sensors using silver or gold nanoparticles embedded within polymethacrylate matrix","authors":"Nadezhda V. Saranchina ,&nbsp;Olga A. Bazhenova ,&nbsp;Dmitrii A. Shcherbakov ,&nbsp;Nataliya A. Gavrilenko ,&nbsp;Kirill V. Serebriakov ,&nbsp;Darya E. Kuznetsova ,&nbsp;Mikhail A. Gavrilenko","doi":"10.1016/j.greeac.2025.100278","DOIUrl":"10.1016/j.greeac.2025.100278","url":null,"abstract":"<div><div>We suggest sensor systems based on the gold and silver nanoparticles embedded within the polymethacrylate matrix (PMM) for colorimetric determination of glucose. A feature of such sensors is the exclusion of the use of toxic solvents in their manufacture and application. In addition, silver and gold nanoparticles are stabilized in a solid transparent polymer, which prevents migration into the environment. We studied the conditions of interaction between the gold and silver nanoparticles and matrix components by evaluating the influence of such factors as solution pH, the amount of nanoparticles within the polymer matrix, the contact time, and the analyte concentration upon the analytical signal. Dual-signal spectrophotometric and colorimetric approaches of using PMM-Ag⁰ / PMM-Au° can be used for the determination of glucose in saliva in the range of 0.1–5.6 mM with the limit of detection of 0.04 mM and 0.1–1.0 mM with the limit of detection of 0.03 mM, accordingly.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100278"},"PeriodicalIF":0.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human lachrymal fluid preparation methodology eVol®MEPS – Green analytical approach in clinical and forensic analysis","authors":"Renata Wietecha-Posłuszny ,&nbsp;Agnieszka Moos-Matysik ,&nbsp;Agnieszka Bocheńska","doi":"10.1016/j.greeac.2025.100276","DOIUrl":"10.1016/j.greeac.2025.100276","url":null,"abstract":"<div><div>Eco-friendly and efficient extraction methods are considered as an important area of interest in all analytical procedures. The presented new green approach combines microextraction by packed sorbent (MEPS) with the use of an automated analytical syringe. Ultra-performance liquid chromatography coupled with a sensitive mass spectrometry detector (UHPLC-MS-TOF) was used for simultaneous quantification of benzodiazepines (BZDs) as ‘model’ analytes in human lacrimal fluid (LF). All samples were collected via free spillage on a cheek into disposable test tubes. As the LF samples were only centrifuged prior to the MEPS extraction; the procedure was short, simple and performed with limited sample and solvents consumption.</div><div>The Vol®MEPS/UHPLC-MS-TOF method was validated. The following parameters were determined: limit of detection (0.01–0.03 ng/ml), limit of quantification (0.03–0.09 ng/ml), linearity (R²&gt;0.99), precision (2.5–12.3 %) and accuracy of the assay (3.3–11.6 %). Based on the example of analysis of a real human sample, it was demonstrated that the method could be a useful tool in forensic and clinical laboratories.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100276"},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green trapping intra tube flux extraction device using polymethyl methacrylate for organochlorine pesticide analysis by gas chromatography-mass spectrometry","authors":"Desirée Marianne Sales Silveira,&nbsp;Jhonatan Bispo de Oliveira,&nbsp;Ildefonso Binatti,&nbsp;Emerson Fernandes Pedroso,&nbsp;Patrícia Santiago de Oliveira Patricio,&nbsp;Patterson Patricio de Souza","doi":"10.1016/j.greeac.2025.100275","DOIUrl":"10.1016/j.greeac.2025.100275","url":null,"abstract":"<div><div>In chemical analysis, sample preparation is the most time-consuming and error-prone step. Available routine methods such as SPE and SPME are usually laborious, expensive, and fragile. For instance, the highly sensitive SPME fibers can break with even a tiny error, rendering them unusable. In this paper, the use of Poly(methyl methacrylate) (PMMA) as the extraction phase in Intra Tube Flux extraction (IT-FEx-SPME) is presented as a one-step, environmentally friendly, and solvent-free method of aqueous sample preparation for gas chromatography. After the extraction of the analytes, the device is inserted into the gas chromatograph (GC) injector for thermal desorption and chromatographic separation. Different molar masses of the PMMA extraction phase for coating the device were also investigated, specifically 120,000 g mol⁻¹ and 350,000 g mol⁻¹; the denser one was more thermally stable in the long term. The method was optimized and validated for analyzing five organochlorine pesticides - heptachlor, aldrin, heptachlor epoxide, endosulfan, and dieldrin. LOD from 0.21 to 1.63 ng mL⁻¹ and LOQ from 0.92 to 7.22 ng mL⁻¹ were achieved. Repeatability within one day (<em>n</em> = 5) resulted in RSD values of 6.09 % to 23.28 %. Inter-day reproducibility (<em>n</em> = 10) showed RSD values ranging from 12.94 % to 19.33 %. The recovery values ranged from 93.07 % to 100.32 %. The method offers a feasible, cost-effective, rapid, green, and safe alternative for the routine analysis of organochlorine pesticides in aqueous samples using GC.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100275"},"PeriodicalIF":0.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable spectrophotometric determination of dextromethorphan and bupropion: A fourier self-deconvolution approach","authors":"Fotouh R. Mansour ,&nbsp;Samar H. Elagamy ,&nbsp;Omar M. Elserwi ,&nbsp;Amira H. Kamal","doi":"10.1016/j.greeac.2025.100274","DOIUrl":"10.1016/j.greeac.2025.100274","url":null,"abstract":"<div><div>A novel, simple, cheap, environment-friendly and accurate chemometric method using Fourier self-deconvolution has been developed for the simultaneous determination of dextromethorphan (DXM) and bupropion (BUP) in their newly approved tablet dosage form using distilled water as a solvent. Direct UV/Vis spectrophotometry could not be employed for determination of both drugs in their mixture due to the significant spectral overlap. FSD is a powerful computational technique extensively used in signal processing. It traditionally combines deconvolution and curve fitting, where deconvolution first identifies the number and positions of distinguishable peaks in the mixture spectrum. The deconvoluted spectra of each drug were utilized for determination of DXM and BUP at points where there is no spectral interference from the other drug. Processing of spectral data was conducted using OriginPro 2024b software. The proposed method was validated according to ICH guidelines. The method was applied for determination of each drug in synthetic laboratory mixture prepared as the composition of their formulated tablet. The results of the proposed method were compared to those of the reported HPLC one. The greenness of the method was assessed using analytical Eco-scale, MoGAPI, and AGREE. The scores for the developed method and reported one were (94 and 87), (84 and 70), (0.78 and 0.54) using Eco-scale, MoGAPI, and AGREE, respectively. It was proven that the developed method is ecofriendly. The whiteness profile of the developed method was also assessed in comparison with the reported HPLC method, based on the principles of White Analytical Chemistry (WAC) using the WAC calculator. The developed UV method achieved a whiteness score of 84.1 %, outperforming the reported HPLC method, which had a score of 68.5 %.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100274"},"PeriodicalIF":0.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecotoxicity prediction of chemical compounds using machine learning and different molecular structure representations","authors":"Michał Marek,&nbsp;Rafał Kurczab","doi":"10.1016/j.greeac.2025.100273","DOIUrl":"10.1016/j.greeac.2025.100273","url":null,"abstract":"<div><div>Advancements in computational tools have facilitated interdisciplinary approaches in toxicology, enabling chemists to explore the toxicity and ecotoxicity of chemical compounds while minimizing ethically questionable or hazardous methods. This paper presents the development of models for predicting chemical ecotoxicity (HC₅₀) based on machine learning algorithms and different molecular representations. A comprehensive set of descriptors was employed, including 100 molecular descriptors calculated using RDKit, 15 molecular connectivity (Chi) indices combined with shape (Kappa) indices, as well as MACCS and ECFP4 binary molecular fingerprints. The best model achieved an average RMSE of 0.740, an R² of 0.708, and an MAE of 0.546 through ten-fold cross-validation. The analysis of critical molecular descriptors identified logP, molar mass, heavy atom molar mass, Ipc, and the number of valence electrons as significant contributors to prediction of chemical ecotoxicity. This model not only facilitates ecotoxicity prediction but also provides valuable insights into the physicochemical properties influencing a molecule's ecotoxic profile, highlighting the potential of in silico approaches for ethical and efficient toxicology research.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"13 ","pages":"Article 100273"},"PeriodicalIF":0.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}