Utilization of Silicon Carbide Waste in Concrete: Experimental Assessment and AI-Driven Compressive Strength Prediction

Utilization of Silicon Carbide Waste in Concrete: Experimental Assessment and AI-Driven Compressive Strength Prediction | 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 Utilization of Silicon Carbide Waste in Concrete: Experimental Assessment and AI-Driven Compressive Strength Prediction R Prithvi, P Sangeetha, P Kaythry, Ninu PraseethaNS This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7459003/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Dec, 2025 Read the published version in Multiscale and Multidisciplinary Modeling, Experiments and Design → Version 1 posted 18 You are reading this latest preprint version Abstract As global attention increasingly shifts toward sustainability and the well-being of future generations, the use of environmentally friendly materials in construction has gained significant importance. This research investigates the feasibility of utilizing silicon carbide waste (SiCW) as a partial replacement for fine aggregate in concrete mixtures. Renowned for its exceptional thermal resistance, hardness, and durability, SiCW shows potential as an additive to enhance the strength and durability of concrete. Various replacement ratios were tested to evaluate the effects of SiCW on workability, durability, and compressive strength. Experimental results indicate that the inclusion of SiCW improves the mechanical properties of concrete, although it slightly reduces workability due to the angular and coarse nature of its particles. Overall, SiCW proves to be a promising sustainable material, particularly suitable for concrete structures exposed to aggressive environments. Additionally, five machine learning models—Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Regression (SVR), and K-Nearest Neighbors (KNN)—were employed to predict compressive strength. Among these, the Decision Tree model demonstrated superior performance based on both Mean Squared Error (MSE) and Mean Absolute Error (MAE), identifying it as the most effective predictive algorithm for this application. Silicon carbide XRD mechanical strength durability strength machine learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Dec, 2025 Read the published version in Multiscale and Multidisciplinary Modeling, Experiments and Design → Version 1 posted Editorial decision: Revision requested 02 Nov, 2025 Reviews received at journal 02 Nov, 2025 Reviews received at journal 14 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviews received at journal 11 Oct, 2025 Reviewers agreed at journal 13 Sep, 2025 Reviewers agreed at journal 07 Sep, 2025 Reviewers agreed at journal 06 Sep, 2025 Reviewers agreed at journal 06 Sep, 2025 Reviewers invited by journal 27 Aug, 2025 Editor assigned by journal 26 Aug, 2025 Submission checks completed at journal 26 Aug, 2025 First submitted to journal 26 Aug, 2025 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. 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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-7459003","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506453504,"identity":"d1783959-c600-465b-8a21-038076301af9","order_by":0,"name":"R Prithvi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIie3PMUvEMBTA8RcC6RIHt8gd9iukCK2Fw36VhINOt7jITWdCoS7F+eQUv8KNjj26lnMtnEOLq4LgIniDQUEQmtPRIX9ChpAfvAfgcv3LkMIA7ND3V7qV29HXI/08VqIzQ46COa54p9K/EECGgFQNSfc7VX0Ta9Ggung8zY+RXhQhyLv7xF8o1D7nMIwsJL6UOrvKGfaGddjKeiOXDyUObnKgseonvDa70JoRpCYRF2QjOBNksGcIL3cTCuUkNJ/XiT8X3vvvZMoYNGnKZF4i1QiCd5G4MIsbwoOiqriox3LZyOzges2sJKJe+0r57PzW07p7m56Ywcarl6ezUWIdrOcNKXOx/v8W4nK5XK6ffQAcW1wlEV+IpAAAAABJRU5ErkJggg==","orcid":"","institution":"Sri Sivasubramaniya Nadar College of Engineering","correspondingAuthor":true,"prefix":"","firstName":"R","middleName":"","lastName":"Prithvi","suffix":""},{"id":506453505,"identity":"95d4475e-dc60-4086-8a93-9b3518249c89","order_by":1,"name":"P Sangeetha","email":"","orcid":"","institution":"Sri Sivasubramaniya Nadar College of Engineering","correspondingAuthor":false,"prefix":"","firstName":"P","middleName":"","lastName":"Sangeetha","suffix":""},{"id":506453506,"identity":"86f05fbc-5bdd-4e7a-9588-0db0bd930ab5","order_by":2,"name":"P Kaythry","email":"","orcid":"","institution":"Sri Sivasubramaniya Nadar College of Engineering","correspondingAuthor":false,"prefix":"","firstName":"P","middleName":"","lastName":"Kaythry","suffix":""},{"id":506453507,"identity":"2c51c8a8-414c-4dd7-9ded-83f0b3187cb0","order_by":3,"name":"Ninu PraseethaNS","email":"","orcid":"","institution":"Sri Sivasubramaniya Nadar College of Engineering","correspondingAuthor":false,"prefix":"","firstName":"Ninu","middleName":"","lastName":"PraseethaNS","suffix":""}],"badges":[],"createdAt":"2025-08-26 05:38:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7459003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7459003/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s41939-025-01130-5","type":"published","date":"2025-12-27T15:58:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99172866,"identity":"46250b91-bd88-4fcd-a543-847e299fde4e","added_by":"auto","created_at":"2025-12-29 16:11:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1099085,"visible":true,"origin":"","legend":"","description":"","filename":"SicConcretemanuscriptAug162025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7459003/v1_covered_ed5bd4be-e817-4222-925e-6ac1db5efbf6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Utilization of Silicon Carbide Waste in Concrete: Experimental Assessment and AI-Driven Compressive Strength Prediction","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"multiscale-and-multidisciplinary-modeling-experiments-and-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mmed","sideBox":"Learn more about [Multiscale and Multidisciplinary Modeling, Experiments and Design](https://link.springer.com/journal/41939)","snPcode":"41939","submissionUrl":"https://submission.nature.com/new-submission/41939/3","title":"Multiscale and Multidisciplinary Modeling, Experiments and Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Silicon carbide, XRD, mechanical strength, durability strength, machine learning","lastPublishedDoi":"10.21203/rs.3.rs-7459003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7459003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs global attention increasingly shifts toward sustainability and the well-being of future generations, the use of environmentally friendly materials in construction has gained significant importance. 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