Investigation of Dyeing Properties of Mohair Fiber Dyed with Natural Dyes Obtained from Candelariella reflexa

ABSTRACT

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.

摘要

目前的研究报告使用抗坏血酸作为一种可能的替代品, 以提高天然染料的牢度. 在媒染过程中, 使用了微波能量, 这是可持续和生态生产方法的一部分. 从黑松树干中提取可再生的天然染料源——地衣属大烛台. 采用传统方法, 用从反射烛台中提取的天然染料对马海毛纤维进行染色. 在染色之前, 马海毛纤维使用微波能量与三氯化铁 (FeCl3) 进行预媒介处理. 为了确定媒染工艺参数对染色性能的影响, 对不同浓度和时间的媒染工艺进行了研究. 在染色过程中, 在染色浴中加入不同浓度的抗坏血酸, 以提高样品的耐光牢度. 染色后, 研究了样品的分光光度特性, 耐光性, 摩擦牢度和耐洗牢度. 预媒染和添加抗坏血酸后, 染色马海毛纤维的色牢度, 耐洗牢度, 耐光牢度和摩擦牢度略有提高. 分光光度测量结果表明, 颜色坐标随媒染时间和抗坏血酸含量的变化而变化. 此外, 在媒染过程中使用微波能可以节省能源和时间。此外, 本研究还开发了一个基于机器学习的人工神经网络模型, 用于预测马海毛纤维在天然染料染色后的染色性能. 通过各种测试获得的实验数据首先被用于输入所提出的神经网络, 然后对训练好的神经网络进行验证和测试, 以达到预测的目的. 研究结果表明, 该模型可以成功地预测马海毛纤维的大部分染色性能. 因此, 该模型可以作为评价马海毛纤维染色性能的有效工具.

KEYWORDS:

• Natural dyes
• mohair fiber
• ascorbic acid
• dyeing properties
• machine learning
• artificial neural network

关键词:

• 天然染料
• 马海毛纤维
• 抗坏血酸
• 染色性能
• 机器学习
• 人工神经网络

Disclosure statement

No potential conflict of interest was reported by the author(s).