Bushra Kamal , Amirhossein Yazdanicherati , Mabkhot S. BinDahbag , Zahra Abbasi , Hassan Hassanzadeh
{"title":"Highly sensitive real-time microwave sensor for detection of organic liquid solvents in an oleic phase","authors":"Bushra Kamal , Amirhossein Yazdanicherati , Mabkhot S. BinDahbag , Zahra Abbasi , Hassan Hassanzadeh","doi":"10.1016/j.meaene.2024.100028","DOIUrl":null,"url":null,"abstract":"<div><div>Accurately determining the concentration of organic solvents in an oleic phase is essential for various industrial applications, including enhanced oil recovery. Popular detection methods, like chromatographic and distillation-based approaches, suffer from sample processing-induced solvent loss. There is a lack of standard methods for detecting solvents in produced fluid streams during solvent-aided oil recovery. We propose a novel sensing approach for solvent monitoring using planar microwave sensors. The proposed sensor consists of a chipless tag-reader pair communicating wirelessly using electromagnetic coupling. The sensor has a high sensitivity response to variations in permittivity at various solvent concentrations, which is reflected in the resonance-frequency spectrum. To maximize repeatability response of sensor, the sensor is integrated into a plastic container to form a sensing probe that can be used as an on-site in-line instrument. The experiments were conducted using four solvents, including n-pentane, n-hexane, n-heptane, and ethyl acetate. The results demonstrated that when solvent concentration changes from zero to 20 wt%, the frequency shift of resonance peak changes by 2.71, 2.01, 1.66, and 2.10 MHz for the examined solvents, respectively, indicating an exceptional capability of real-time monitoring for measuring solvents in oleic phase. The proposed approach offers the potential for applying planar microwave sensors to detect organic solvents in industrial processes.</div></div>","PeriodicalId":100897,"journal":{"name":"Measurement: Energy","volume":"4 ","pages":"Article 100028"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement: Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950345024000289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurately determining the concentration of organic solvents in an oleic phase is essential for various industrial applications, including enhanced oil recovery. Popular detection methods, like chromatographic and distillation-based approaches, suffer from sample processing-induced solvent loss. There is a lack of standard methods for detecting solvents in produced fluid streams during solvent-aided oil recovery. We propose a novel sensing approach for solvent monitoring using planar microwave sensors. The proposed sensor consists of a chipless tag-reader pair communicating wirelessly using electromagnetic coupling. The sensor has a high sensitivity response to variations in permittivity at various solvent concentrations, which is reflected in the resonance-frequency spectrum. To maximize repeatability response of sensor, the sensor is integrated into a plastic container to form a sensing probe that can be used as an on-site in-line instrument. The experiments were conducted using four solvents, including n-pentane, n-hexane, n-heptane, and ethyl acetate. The results demonstrated that when solvent concentration changes from zero to 20 wt%, the frequency shift of resonance peak changes by 2.71, 2.01, 1.66, and 2.10 MHz for the examined solvents, respectively, indicating an exceptional capability of real-time monitoring for measuring solvents in oleic phase. The proposed approach offers the potential for applying planar microwave sensors to detect organic solvents in industrial processes.