Curvilinear Regression Models for Benzenoid Hydrocarbons

Curvilinear Regression Models for Benzenoid Hydrocarbons | 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PDF Research Article Curvilinear Regression Models for Benzenoid Hydrocarbons Kerem Yamaç This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4010792/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chemical graph theory enables the use of several methods with important applications in drug design and development. The Van topological indices have been defined recently, which are based on neighbour vertex degree. This article examines the chemical application of the Van topological indices through regression models employing 22 benzenoid hydrocarbons. The chemical applicability of the Van topological indices is investigated in this study, using curvilinear regression models to analyze its relationship with the physico-chemical properties of benzenoid hydrocarbons. The statistical analysis data indicates that the Van topological indices have the potential to serve as a predictive index for the attribute of boiling point (BO), π-electron energy (π-ele), molecular weight (MW), polarizability (PO), molar volume (MV), and molar refractivity (MF). Topological descriptors Van indices benzenoid hydrocarbons physicochemical properties regression models Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4010792","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276604575,"identity":"602ac640-e4d1-49c1-82d2-9542fbe22cf4","order_by":0,"name":"Kerem Yamaç","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACCQhlA6F4SNCSBtciQayWwyRokZyR/HTDj5rziRtuJDA+eNvGUGfeQECLtESa2c2eY7dBWpgN57YxSMgcIKBFTiLB7AZvA1gLmzQvUAtBl8lJpH+7+bfhHEgL+2+itEhL5Jjd5m04ALaFmSgtkj1vym7LHEs2nnnmYbPknHMSkjMIaZE4nr7t5psaO9m+48kHP7wps+EnHMoCCWDKccEBxgYGYqKFgYH/AJiyl28gQvEoGAWjYBSMTAAA6OZBxZClySsAAAAASUVORK5CYII=","orcid":"","institution":"Yüzüncü Yıl University","correspondingAuthor":true,"prefix":"","firstName":"Kerem","middleName":"","lastName":"Yamaç","suffix":""}],"badges":[],"createdAt":"2024-03-04 06:22:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4010792/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4010792/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53343687,"identity":"e8913319-77a3-40b9-a485-6d4fc9f8518b","added_by":"auto","created_at":"2024-03-24 18:06:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":458207,"visible":true,"origin":"","legend":"","description":"","filename":"keremabiscitekisim2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4010792/v1_covered_d7152bad-bae4-4972-9e57-0b57602411de.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Curvilinear Regression Models for Benzenoid Hydrocarbons","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Topological descriptors, Van indices, benzenoid hydrocarbons, physicochemical properties, regression models","lastPublishedDoi":"10.21203/rs.3.rs-4010792/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4010792/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChemical graph theory enables the use of several methods with important applications in drug design and development. 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