Investigation and feed-forward neural network-based estimation of dyeing properties of air plasma treated wool fabric dyed with natural dye obtained from Hibiscus sabdariffa / Zeynep Omerogullari Basyigit in COLORATION TECHNOLOGY, Vol. 139, N° 4 (08/2023)  

[article]  inCOLORATION TECHNOLOGY > Vol. 139, N° 4 (08/2023) . - p. 441-453 Titre : Investigation and feed-forward neural network-based estimation of dyeing properties of air plasma treated wool fabric dyed with natural dye obtained from Hibiscus sabdariffa Type de document : texte imprimé Auteurs : Zeynep Omerogullari Basyigit, Auteur ; Can Eyupoglu, Auteur ; Seyda Eyupoglu, Auteur ; Nigar Merdan, Auteur Année de publication : 2023 Article en page(s) : p. 441-453 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Colorants végétaux Laine Réseaux neuronaux (informatique) Résistance à l'abrasion Résistance au lavage Solidité de la couleur Surfaces -- Analyse Technique des plasmas Teinture -- Fibres textiles Ultrasons Index. décimale : 667.3 Teinture et impression des tissus Résumé : In the colouring processes of textile products, more environmentally friendly chemicals and finishing methods should be used instead of conventional ones that harm the environment every day, so that alternative realistic ways to protect nature, both academically and industrially, could be possible. Due to some inconveniences caused by synthetic dyes that are widely used today, in this study, ultrasonic dyeing of wool fabric with Hibiscus sabdariffa was carried out after environmental-friendly air vacuum plasma application which increased the absorption of the dyes into the textile material. According to the performance results, colour strengths of the wool fabrics were increased significantly. Surface morphology analysis was carried out and etching effects of air vacuum plasma treatment were clearly seen on the micrographs of the treated wool fabrics. An environmental-friendly green process was achieved through this study and it was concluded that vacuum air plasma treatment could be an alternative green-process as a pretreatment to increase the dye up-take of natural dyeing treatment. Moreover, in this study, a feed-forward neural network (FFNN) model was presented and used for predicting the dyeing properties (L, a, b and K/S) of samples. The experimental results showed that the presented model achieves the regression values greater than 0.9 for all dyeing properties. Consequently, it was considered that the proposed FFNN was successfully modelled and could be efficiently utilised for dyeing characteristics of wool fabrics dyed with natural dye extracted from Hibiscus sabdariffa. Note de contenu : - MATERIALS AND METHODS : Materials - Method - RESULTS AND DISCUSSION : Colour results - Fastness results - Scanning electron microscope analysis results - Fourier-transform infrared analysis results - Feed-forward neural network-based results - Table 1 : CIELab L, a, b and ΔE values of samples - Table 2 : The K/S values of all wool fabrics at 540 nm - Table 3 : Washing and rubbing fastness results of samples - Table 4 : Regression results of the proposed feed-forward neural network (FFNN) model for the dyeing properties of samples DOI : https://doi.org/10.1111/cote.12665 En ligne : https://onlinelibrary.wiley.com/doi/epdf/10.1111/cote.12665 Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=39681 [article]

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Natural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network / Can Eyupoglu in COLORATION TECHNOLOGY, Vol. 140, N° 1 (02/2024)  

[article]  inCOLORATION TECHNOLOGY > Vol. 140, N° 1 (02/2024) . - p. 91-102 Titre : Natural dyeing of air plasma-treated wool fabric with Rubia tinctorum L. and prediction of dyeing properties using an artificial neural network Type de document : texte imprimé Auteurs : Can Eyupoglu, Auteur ; Seyda Eyupoglu, Auteur ; Nigar Merdan, Auteur ; Zeynep Omerogullari Basyigit, Auteur Année de publication : 2024 Article en page(s) : p. 91-102 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Analyse morphologique Colorants végétaux Colorimétrie Extraction (chimie) Laine Résistance à l'abrasion Résistance au lavage Technique des plasmas Teinture -- Fibres textiles Traîtements de surface Index. décimale : 667.3 Teinture et impression des tissus Résumé : In 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. Note de contenu : - MATERIALS AND METHODS : Materials - Dye extraction - Plasma application - Dyeing process - Surface morphology analysis - FTIR analysis - Colorimetric analysis - Fastness analysis - Proposed ANN model - RESULTS AND DISCUSSION : Scanning electron microscopy analysis - FTIR analysis - Fastness properties - Analysis of colour parameters - Neural network-based results - Table 1 : The washing and rubbing fastness values of the samples - Table 2 : Colour properties of the samples - Table 3 : Regression results of the proposed model for the dyeing properties of samples DOI : https://doi.org/10.1111/cote.12700 En ligne : https://drive.google.com/file/d/1O7FIts3_5sVxA2vOu7vIfDTuYTejtya6/view?usp=drive [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=40393 [article]

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