Denim color fading ozonation is dissimilar from other ozone applications as it is employed with distinctive parameters and on special products. In this study, yarns of cotton, lyocell and PET treated by denim color fading ozonation were investigated in terms of the effects of time, pH and water content on their physical properties, which included chemical and crystalline structures, surface microstructure, yarns strength and elongation. It is found that, the cellulose in cotton and lyocell yarns has a loss of strength and elongation, while only slight impacts on their crystalline structures are observed. An aggregation and compact crystalline structure of PET prevents it from the decomposition of ozone, whose prevention may also benefit from its poor ability of moisture regain. As a result, synthetic materials, such as PET is recommended more than cellulose fibers to be used in ozone fading process. Meanwhile, such process should neither be employed on cotton, lyocell and other cellulose yarns at pH < 7 nor without paying attention to select a proper water content.

Textile products with a faded effect achieved via ozonation are increasingly popular nowadays. In order to better understand and apply this process, the complex factors and effects of color fading ozonation are investigated via process modeling in terms of pH, temperature, water pick-up, time (of process) and original color (of textile) affecting the color performance (K/S, L*, a*, b* values) of reactive-dyed cotton using the Extreme Learning Machine (ELM), Support Vector Regression (SVR) and Random Forest (RF), respectively. It is found that the RF and SVR perform better than the ELM as the latter were very unstable in the case of predicting a certain single output. Both the RF and SVR are potentially applicable, but SVR would be more recommended to be used in the real application due to its balancer predicting performance and lower training time cost.