Prediction and Optimization of The Effect of Ethanol Pre-Treatment on The Tensile Strength of Permanganate Treated Bamboo Fibers

Prediction and Optimization of The Effect of Ethanol Pre-Treatment on The Tensile Strength of Permanganate Treated Bamboo Fibers | 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 Prediction and Optimization of The Effect of Ethanol Pre-Treatment on The Tensile Strength of Permanganate Treated Bamboo Fibers Mamookho Elizabeth Makhatha, Patrick Ehi Imoisili, Tien-Chien Jen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4087469/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 In this study, Natural fibres (NF) from bamboo bundles was modified by first pre-treated with Ethanol, followed by potassium permanganate (KMnO 4 ) in Acetone solution at varied concentrations and time durations. To optimize the influence of ethanol pre-treatment and KmnO 4 treatment at varied concentration and duration on the tensile strength (TS) of the modified bamboo fibres (BmF), Response surface methodology (RSM) via Box – Behnken design (BBD), was employed. The treatment parameter greatly effects the TS of the BmF as shown by the surface morphology observed by scanning electron microscope (SEM) and analysis of variance (ANOVA). The ANOVA reveal the statistically significant of the model at a significance level of P < 0.0001. The optimal predicted conditions by the model were validated by experimental analysis, and result obtained indicated a 98.29% agreement between the model predictions and empirical values, thus affirming the optimum point of these variables. This investigation has demonstrated that utilizing RAM model via BBD approach is an effective way to get ideal values for treated NF mechanical characteristics at a lower cost and in less time for variety of applications, hence conserving time and resources. Natural fibre Bamboo Response surface methodology Ethanol KMnO4 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. 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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-4087469","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280058209,"identity":"dc41d983-9e3a-4403-a8ba-8f7b4440357e","order_by":0,"name":"Mamookho Elizabeth Makhatha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYHACZmYgkcDA3sBgQIoWgwQGngMka5FIIFI9v9jhx8YFNX/y+Ge+MShgqLFjkG8/gF+L5Ow04+QZxwyKJW7nGBgwHEtmYOwhYJ3B7QTjwzxsBokNYC1sBxiYGQhosb+d/vkwzz+DxPk3zwC1/DvAwMb/gIAt0jnGybxtBokbbvAYGDC2HWDgIRQOQC8UG/P2GSduPJNWYJDYl8wjIUHAFv7Z6Zuleb7JJc47fnibwYdvdnLy/QRsQQZswNhh4CFePRAwE3DRKBgFo2AUjFQAALH+PgF6yI/zAAAAAElFTkSuQmCC","orcid":"","institution":"University of Johannesburg","correspondingAuthor":true,"prefix":"","firstName":"Mamookho","middleName":"Elizabeth","lastName":"Makhatha","suffix":""},{"id":280058210,"identity":"9656dc8a-fd60-436a-8d7b-150f3f683806","order_by":1,"name":"Patrick Ehi Imoisili","email":"","orcid":"","institution":"University of Johannesburg","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"Ehi","lastName":"Imoisili","suffix":""},{"id":280058211,"identity":"5f48af93-4b84-4174-8190-d0b71a3269be","order_by":2,"name":"Tien-Chien Jen","email":"","orcid":"","institution":"University of Johannesburg","correspondingAuthor":false,"prefix":"","firstName":"Tien-Chien","middleName":"","lastName":"Jen","suffix":""}],"badges":[],"createdAt":"2024-03-12 20:30:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4087469/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4087469/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61425827,"identity":"f14819cd-4e7e-477a-a58e-d2bfc0057193","added_by":"auto","created_at":"2024-07-30 14:45:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":823869,"visible":true,"origin":"","legend":"","description":"","filename":"PolymerBulletinmanuscripts3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4087469/v1_covered_7566ac62-7016-4f49-8940-d8cbcd6e3de1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction and Optimization of The Effect of Ethanol Pre-Treatment on The Tensile Strength of Permanganate Treated Bamboo Fibers","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":"Natural fibre, Bamboo, Response surface methodology, Ethanol, KMnO4","lastPublishedDoi":"10.21203/rs.3.rs-4087469/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4087469/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, Natural fibres (NF) from bamboo bundles was modified by first pre-treated with Ethanol, followed by potassium permanganate (KMnO\u003csub\u003e4\u003c/sub\u003e) in Acetone solution at varied concentrations and time durations. To optimize the influence of ethanol pre-treatment and KmnO\u003csub\u003e4\u003c/sub\u003e treatment at varied concentration and duration on the tensile strength (TS) of the modified bamboo fibres (BmF), Response surface methodology (RSM) via Box \u0026ndash; Behnken design (BBD), was employed. The treatment parameter greatly effects the TS of the BmF as shown by the surface morphology observed by scanning electron microscope (SEM) and analysis of variance (ANOVA). The ANOVA reveal the statistically significant of the model at a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001. The optimal predicted conditions by the model were validated by experimental analysis, and result obtained indicated a 98.29% agreement between the model predictions and empirical values, thus affirming the optimum point of these variables. 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