Frank Jacobs , Dr. Klaus Kerpen , Dr. Eike Kleine-Benne , PD Dr. Ursula Telgheder
{"title":"Development of an automated sorptive extraction system for trace analysis in water","authors":"Frank Jacobs , Dr. Klaus Kerpen , Dr. Eike Kleine-Benne , PD Dr. Ursula Telgheder","doi":"10.1016/j.sampre.2025.100156","DOIUrl":null,"url":null,"abstract":"<div><div>Stir bar sorptive extraction (SBSE) is an established microextraction technique developed in the early 2000s. It has gained widespread use in laboratories around the world, but always had one drawback in that it was a manual sample preparation technique. The newly developed system presented in this study aims to combine the well-known characteristics of SBSE with fully automated sample preparation. The presented system is based on a novel sample probe design, which uses the same dimensions and materials of sorbent phase as the commercially available Gerstel Twister® SBSE technology. To test the performance of this system, pesticides were extracted from pure water as well as river water. Limits of detection (4.5 ng/L to 53.6 ng/L) and quantification (15.7 ng/L to 327.6 ng/L) as well as standard method deviation (3.2 % to 37.6 %) were determined for 21 pesticides based on DIN EN ISO 27,108, part of the water framework directive (WFR). Standard addition was used to quantify pesticides in river water matrix. To check the performance of the new development, it was compared to established methods like manual SBSE, thin film micro extraction (TFME) and SPME-Arrow. The results are comparable between automated sorptive extraction (ASE) and SBSE (average of 84 % compared to automated system), as expected. Performance compared to TFME (65 %) and SPME-Arrow (3 %) was significantly better, especially to the latter. These results show that the automated sorptive extraction system developed in this paper is competitive with already established techniques.</div></div>","PeriodicalId":100052,"journal":{"name":"Advances in Sample Preparation","volume":"13 ","pages":"Article 100156"},"PeriodicalIF":5.2000,"publicationDate":"2025-02-01","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/S2772582025000099","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
Stir bar sorptive extraction (SBSE) is an established microextraction technique developed in the early 2000s. It has gained widespread use in laboratories around the world, but always had one drawback in that it was a manual sample preparation technique. The newly developed system presented in this study aims to combine the well-known characteristics of SBSE with fully automated sample preparation. The presented system is based on a novel sample probe design, which uses the same dimensions and materials of sorbent phase as the commercially available Gerstel Twister® SBSE technology. To test the performance of this system, pesticides were extracted from pure water as well as river water. Limits of detection (4.5 ng/L to 53.6 ng/L) and quantification (15.7 ng/L to 327.6 ng/L) as well as standard method deviation (3.2 % to 37.6 %) were determined for 21 pesticides based on DIN EN ISO 27,108, part of the water framework directive (WFR). Standard addition was used to quantify pesticides in river water matrix. To check the performance of the new development, it was compared to established methods like manual SBSE, thin film micro extraction (TFME) and SPME-Arrow. The results are comparable between automated sorptive extraction (ASE) and SBSE (average of 84 % compared to automated system), as expected. Performance compared to TFME (65 %) and SPME-Arrow (3 %) was significantly better, especially to the latter. These results show that the automated sorptive extraction system developed in this paper is competitive with already established techniques.