{"title":"Recent advances in environmental sample preparation: Nanomaterials, automation, and sustainable strategies","authors":"Federico Belén , Julián Gutiérrez , Valeria Springer","doi":"10.1016/j.sampre.2025.100171","DOIUrl":null,"url":null,"abstract":"<div><div>The increasing occurrence of micropollutants and the need for their monitoring in environmental matrices have driven the demand for more efficient and accurate analytical methods. In particular, sample preparation procedures are essential for addressing the complexity of environmental samples while ensuring high sensitivity. To meet these demands, various nanomaterials (NMs) have been proposed as extractive phases for development of miniaturized sorbent-based extraction approaches. These NMs, ranging from carbon-based nanostructures and metal-based or metal oxide nanoparticles, to metal–organic composites, are at the forefront of innovation due to their exceptional surface areas, tunable properties, ease of functionalization and, in some cases, green production routes. On the other hand, the development of (semi)automated platforms has facilitated high-throughput and reproducible sample processing, significantly reducing the use of reagents, time, and labor. This review highlights the pivotal role of NMs and automation in advancing sample preparation methodologies over the past five years, in alignment with green sample preparation (GSP) guidelines. Additionally, the integration of emerging technologies, such as 3D printing, is discussed in the context of developing modern sample preparation methods. Recent contributions involving miniaturized platforms, green nanosorbents, and the integration of processing steps with automation, are evaluated for their potential to provide highly efficient, cost-effective solutions for monitoring micropollutants in environmental matrices.</div></div>","PeriodicalId":100052,"journal":{"name":"Advances in Sample Preparation","volume":"14 ","pages":"Article 100171"},"PeriodicalIF":5.2000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Sample Preparation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772582025000245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The increasing occurrence of micropollutants and the need for their monitoring in environmental matrices have driven the demand for more efficient and accurate analytical methods. In particular, sample preparation procedures are essential for addressing the complexity of environmental samples while ensuring high sensitivity. To meet these demands, various nanomaterials (NMs) have been proposed as extractive phases for development of miniaturized sorbent-based extraction approaches. These NMs, ranging from carbon-based nanostructures and metal-based or metal oxide nanoparticles, to metal–organic composites, are at the forefront of innovation due to their exceptional surface areas, tunable properties, ease of functionalization and, in some cases, green production routes. On the other hand, the development of (semi)automated platforms has facilitated high-throughput and reproducible sample processing, significantly reducing the use of reagents, time, and labor. This review highlights the pivotal role of NMs and automation in advancing sample preparation methodologies over the past five years, in alignment with green sample preparation (GSP) guidelines. Additionally, the integration of emerging technologies, such as 3D printing, is discussed in the context of developing modern sample preparation methods. Recent contributions involving miniaturized platforms, green nanosorbents, and the integration of processing steps with automation, are evaluated for their potential to provide highly efficient, cost-effective solutions for monitoring micropollutants in environmental matrices.