Investigation of dyeing properties of mohair fiber dyed with natural dyes obtained from candelariella reflexa
Yükleniyor...
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Ltd.
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
The current study reports on using ascorbic acid as a possible substitute for improving fastness properties of natural dyes. In the mordanting process, microwave energy, which is a part of the sustainable and ecological production approach, was used. Renewable natural dye source Candelariella reflexa, which is a genus of lichen, was obtained from the trunk of Pinus nigra. Mohair fiber was dyed with natural dye extracted from Candelariella reflexa by using a conventional method. Before dyeing, mohair fiber was subjected to the premordanted process with iron (III) chloride (FeCl3) using microwave energy. In order to determine the effect of mordanting process parameters on dyeing properties, the mordanting process was performed with different concentrations and durations. In the dyeing process, ascorbic acid was added at different concentrations in the dyeing bath to improve the light fastness of samples. After the dyeing process, spectrophotometric features, light, and rubbing and washing fastness of samples were investigated. The color strength, washing, light, and rubbing fastness of dyed mohair fiber improve slightly with the premordanting process and by adding ascorbic acid. The spectrophotometric measurement results show that color coordinates vary from the mordanting time and amount of ascorbic acid. Furthermore, the use of microwave energy in the mordanting process leads to saving of energy and time. Besides, in this study, a machine learning-based model exploiting the artificial neural network (ANN) was developed for prediction of dyeing properties of mohair fiber dyed with natural dyes obtained from Candelariella reflexa. Experimental data obtained through various tests were first used to feed the proposed ANN, and then the trained ANN was validated and tested for the aim of prediction. The study results show that the proposed model can successfully predict most of the dyeing properties of mohair fiber. Therefore, this model can be used as an effective tool to estimate dyeing characteristics of mohair fiber.
Açıklama
Anahtar Kelimeler
artificial neural network; ascorbic acid; dyeing properties; machine learning; mohair fiber; Natural dyes
Kaynak
Journal of Natural Fibers
WoS Q Değeri
Q1
Scopus Q Değeri
N/A
Cilt
19
Sayı
16
