Modeling and optimization of dyeing process of polyamide 6 and woolen fabrics with plum-tree leaves using artificial intelligence.

The dyeing process of textile materials is inherently intricate, influenced by a myriad of factors, including dye concentration, dyeing time, pH level, temperature, type of dye, fiber composition, mechanical agitation, salt concentration, mordants, fixatives, water quality, dyeing method, and pre-treatment processes. The intricacy of achieving optimal settings during dyeing poses a significant challenge. In response, this study introduces a novel algorithmic approach that integrates response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA) techniques for the precise fine-tuning of concentration, time, pH, and temperature.

Suitability of dyes from cinnamon bark on wool fibers using metal and bio-mordants.

Growing concern about the environmental effects of metal mordants and synthetic dyes is encouraging the use of bio-mordants and natural colorants. Cinnamon bark is a rich source of natural colorants such as cinnamaldehyde and tannins. The main purpose of this research was to study and compare the effect of bio-mordants versus metal mordants in terms of colorimetric parameters and color fastness properties of cinnamon bark on wool fibers.