Publication:
Natural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network

dc.contributor.authorEyüpoğlu, Can
dc.contributor.authorEyüpoğlu, Şeyda
dc.contributor.authorMerdan, Nigar
dc.contributor.buuauthorBaşyiğit, Zeynep Ömeroğulları
dc.contributor.buuauthorÖMEROĞULLARI BAŞYİĞİT, ZEYNEP
dc.contributor.departmentBursa Uludağ Üniversitesi/İnegöl Meslek Yüksekokulu/Tekstil, Giyim, Ayakkabı ve Deri, Tekstil Teknolojisi Bölümü.
dc.contributor.researcheridHJY-8602-2023
dc.date.accessioned2024-11-21T11:44:18Z
dc.date.available2024-11-21T11:44:18Z
dc.date.issued2023-06-09
dc.description.abstractIn this study, the ecological dyeing process of wool fabrics was investigated. Wool fabric samples were treated with atmospheric pressure plasma-jet and corona discharge plasma to modify the surface to make the process sustainable and greener. The samples were dyed with the aqueous extract procured from the powdered roots of Rubia tinctorum L. (madder) using the ultrasonic-assisted method. Scanning electron microscopy and Fourier Transform-infrared analysis were performed to investigate the effect of plasma treatment on the physical and chemical properties of wool fibres. The effects of plasma treatment type, plasma treatment parameters and the duration of dyeing on colorimetric and fastness properties were investigated. The etching of the wool fibre surface and roughness after plasma treatment were proven with scanning electron microscopy images. The Fourier Transform-infrared spectra showed that no significant differences in the functional groups of wool fibre occurred after plasma treatment. The experimental results proved that plasma treatment parameters and dyeing time had an effect on the colorimetric and fastness properties of the samples. Furthermore, an artificial neural network model was proposed for estimating the dyeing properties of wool fabrics, namely, L, a, b, K/S, colour change, rubbing fastness (dry) and rubbing fastness (wet). The experimental results show that the proposed model achieves regression values greater than 0.97 for all dyeing properties. The proposed model is successful and can be efficiently used for estimating the dyeing characteristics of wool fabrics.
dc.identifier.doi10.1111/cote.12700
dc.identifier.endpage102
dc.identifier.issn1472-3581
dc.identifier.issue1
dc.identifier.startpage91
dc.identifier.urihttps://doi.org/10.1111/cote.12700
dc.identifier.urihttps://hdl.handle.net/11452/48290
dc.identifier.volume140
dc.identifier.wos001004630400001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherWiley
dc.relation.journalColoration Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectSurface
dc.subjectTextiles
dc.subjectDyes
dc.subjectScience & technology
dc.subjectPhysical sciences
dc.subjectTechnology
dc.subjectChemistry, applied
dc.subjectEngineering, chemical
dc.subjectMaterials science, textiles
dc.subjectChemistry
dc.subjectEngineering
dc.subjectMaterials science
dc.titleNatural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication175a6032-c980-4c66-8cd6-709d104f5264
relation.isAuthorOfPublication.latestForDiscovery175a6032-c980-4c66-8cd6-709d104f5264

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