High-Accuracy Crude Oil Purity Detection Using a Non-Invasive Microwave Sensor with Proximity-Coupled Patch Antennas

High-Accuracy Crude Oil Purity Detection Using a Non-Invasive Microwave Sensor with Proximity-Coupled Patch Antennas | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article High-Accuracy Crude Oil Purity Detection Using a Non-Invasive Microwave Sensor with Proximity-Coupled Patch Antennas Sepehr Zarghami, Ali Roshani, Parsa Askarian Chayjan, Peshawa Jamal Muhammad Ali, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8713886/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract This paper presents a non-invasive microwave-based sensor for high-precision purity detection of crude oil based on the proximity-coupled rectangular microstrip patch antennas. The sensor employs mutual electromagnetic coupling between two closely placed slotted rectangular-shaped antennas in order to extract dielectric metrics from oil-water mixtures. This design contrasts with more traditional single-antenna sensors, which rely entirely on S 11 or return loss, as our design utilizes additional scattering parameters (S 21 , S 22 ) for improved sensitivity and selectivity when characterizing oil purity. This antenna system operates in two primary frequency bands, specifically 6.9–7.6 GHz for detecting dielectric-based bandwidth variation and 1.6 GHz for characterizing signal transmission. The sensor is fabricated on the FR4 substrate and experimentally validates its capabilities with a wide range of water-oil mixtures. The results showed good agreement with simulated and measured data, and validated the high accuracy of the proposed sensor. To improve sensing precision and decrease nonlinearity due to operation at higher frequencies, artificial neural networks (ANN) models are used in the data processing step. Altogether, the ANN model increased prediction accuracy and model reliability for oil clarity classifications. Measured results indicate an S11 < − 10 dB in the 6.9–7.6 GHz with peak gain of 7.6 dBi, and the ANN regression yielded R²=0.995 with low prediction error, confirming enhanced detection accuracy. Physical sciences/Engineering Physical sciences/Physics Dielectric constant Microstrip Neural network Proximity-coupled Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Feb, 2026 Reviews received at journal 21 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 05 Feb, 2026 Reviewers invited by journal 04 Feb, 2026 Editor invited by journal 04 Feb, 2026 Editor assigned by journal 02 Feb, 2026 Submission checks completed at journal 02 Feb, 2026 First submitted to journal 27 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8713886","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":586515294,"identity":"f726c8ac-b038-42d3-ab57-5e3085672297","order_by":0,"name":"Sepehr Zarghami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYJACZijNBsQScgwMPCRqMSZZC0NiAyEt8u29Bx8X7mGw5599/NqDnzkW6RuOnz344AODnZxuA3YtBmfOJRvPeMbALHEup9ywd5tE7oYzecmGMxiSjc0O4NAikWMmzXMA6KgzPGkSvCAtB0AiDAcSt+HQIj//jflvoBYeeaAWyb/bJNINzr/Br4XhBo8ZM1CLhMEZ9mPSQFsSDG4QsMUA6HKgwyQMDM/wsEnLbpMwnHnjjbHhDAPcfpFvP3vwM88BG3u5M+zPJN9uq5PnO59j+OBDhZ0cLi3QiJMAMQzAfAWwSgNcyuFaQID9AcTeBnyqR8EoGAWjYCQCAO4UV0ZnOHBmAAAAAElFTkSuQmCC","orcid":"","institution":"Razi University","correspondingAuthor":true,"prefix":"","firstName":"Sepehr","middleName":"","lastName":"Zarghami","suffix":""},{"id":586515295,"identity":"41a0770e-9e5b-41f7-a06d-221856377232","order_by":1,"name":"Ali Roshani","email":"","orcid":"","institution":"Sharif University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Roshani","suffix":""},{"id":586515296,"identity":"160ae8fb-7737-4853-91d5-5fed78054dbf","order_by":2,"name":"Parsa Askarian Chayjan","email":"","orcid":"","institution":"Kermanshah University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Parsa","middleName":"Askarian","lastName":"Chayjan","suffix":""},{"id":586515297,"identity":"6269779b-7121-4cf5-87b4-78b710f08200","order_by":3,"name":"Peshawa Jamal Muhammad Ali","email":"","orcid":"","institution":"Koya University","correspondingAuthor":false,"prefix":"","firstName":"Peshawa","middleName":"Jamal Muhammad","lastName":"Ali","suffix":""},{"id":586515298,"identity":"25bcbbd1-6c02-4dc6-9291-920bc95d5c40","order_by":4,"name":"Gholam Hossein Roshani","email":"","orcid":"","institution":"Kermanshah University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Gholam","middleName":"Hossein","lastName":"Roshani","suffix":""}],"badges":[],"createdAt":"2026-01-27 19:38:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8713886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8713886/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102296036,"identity":"172c6ba8-af9f-4c35-a473-1760cacf145e","added_by":"auto","created_at":"2026-02-10 10:16:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2425470,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8713886/v1_covered_8084b074-cb28-4a5f-9a3c-f249a8bbee6e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High-Accuracy Crude Oil Purity Detection Using a Non-Invasive Microwave Sensor with Proximity-Coupled Patch Antennas","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dielectric constant, Microstrip, Neural network, Proximity-coupled","lastPublishedDoi":"10.21203/rs.3.rs-8713886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8713886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents a non-invasive microwave-based sensor for high-precision purity detection of crude oil based on the proximity-coupled rectangular microstrip patch antennas. The sensor employs mutual electromagnetic coupling between two closely placed slotted rectangular-shaped antennas in order to extract dielectric metrics from oil-water mixtures. This design contrasts with more traditional single-antenna sensors, which rely entirely on S\u003csub\u003e11\u003c/sub\u003e or return loss, as our design utilizes additional scattering parameters (S\u003csub\u003e21\u003c/sub\u003e, S\u003csub\u003e22\u003c/sub\u003e) for improved sensitivity and selectivity when characterizing oil purity. This antenna system operates in two primary frequency bands, specifically 6.9\u0026ndash;7.6 GHz for detecting dielectric-based bandwidth variation and 1.6 GHz for characterizing signal transmission. The sensor is fabricated on the FR4 substrate and experimentally validates its capabilities with a wide range of water-oil mixtures. The results showed good agreement with simulated and measured data, and validated the high accuracy of the proposed sensor. 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