| 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 |
in COLORATION TECHNOLOGY > Vol. 140, N° 1 (02/2024) . - p. 91-102
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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 in COLORATION TECHNOLOGY, Vol. 140, N° 1 (02/2024)
