Investigation of Dyeing Characteristics of Merino Wool Fiber Dyed with Sustainable Natural Dye Extracted from Aesculus hippocastanum

Seyda Eyupoglu, Can Eyupoglu, Nigar Merdan and Oktay Karakuş ()
Additional contact information
Seyda Eyupoglu: Department of Textile, Clothing, Footwear and Leather, Vocational School of Technical Sciences, İstanbul University—Cerrahpaşa, 34500 Istanbul, Türkiye
Can Eyupoglu: Department of Computer Engineering, Turkish Air Force Academy, National Defence University, 34149 Istanbul, Türkiye
Nigar Merdan: Department of Fashion and Textile Design, Architecture and Design Faculty, İstanbul Ticaret University, 34840 Istanbul, Türkiye
Oktay Karakuş: School of Computer Science and Informatics, Cardiff University, Cardiff CF24 4AG, UK

Sustainability, 2024, vol. 16, issue 22, 1-18

Abstract: Recently there has been growing interest in dyeing biomaterials using natural sustainable plant extracts classified as eco-friendly. The microwave-assisted method provides fast heating and energy efficiency, more homogenous heat distribution in dyeing baths, less use of chemicals, and less heat loss, resulting in this method being greener—more sustainable and ecological. Artificial neural networks (ANNs) are used to predict the dyeing properties of fibers, which are often complex and dependent on multiple variables. This saves time and reduces costs compared to trial-and-error methods. This study presents the green dyeing of merino wool fiber with natural dye extracted from Aesculus hippocastanum (horse chestnut) shells using the microwave-assisted method. Before dyeing, the merino wool fiber underwent a pre-mordanted process with aluminum potassium sulfate with different concentrations using the microwave-assisted method. Spectrophotometric analysis of the light, washing, and rubbing fastness of the dyed merino wool fibers was performed. The color strength, light, washing, and rubbing fastness of the dyed merino wool fiber were developed using the pre-mordanting process. After the pre-mordanting process, the light fastness of the samples improved from 1–2 to 3, the color change increased from 2 to 3–4, and the rubbing fastness developed from 2–3 to 4 according to mordant concentration, mordanting time, and dyeing time quantities. The spectrophotometric analysis results indicate that color coordinates vary based on mordant concentration, mordanting, and dyeing duration. Furthermore, the results proved that microwave energy significantly shortened the mordanting and dyeing duration, resulting in an eco-friendly dyeing process. In this investigation, a feed-forward neural network (FFNN) model with sigmoid hidden neurons and a linear output neuron was used to predict the color strength dyeing property of merino wool fiber. Experimental results showed that the proposed model achieved a regression value of 0.9 for the color strength dyeing property. As demonstrated, the proposed FFNN model is effective and can be utilized to forecast the color strength dyeing properties of merino wool fiber.

Keywords: natural dye; Aesculus hippocastanum; merino wool; spectrophotometric analysis; fastness; feed-forward neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/22/10129/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/22/10129/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:22:p:10129-:d:1525164

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().