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  • Statistical optimization and bulk scale validation of the effects of cationic pre-treatment of cotton fabric for digital printing with reactive dyes

Faisal, Saira, Ali, Muhammad, Naqvi, Shehnila and Lin, Long, 2021, Journal Article, Statistical optimization and bulk scale validation of the effects of cationic pre-treatment of cotton fabric for digital printing with reactive dyes Journal of Natural Fibers, 19 (13). pp. 6737-6747. ISSN 1544-046X

Abstract or Description:

Digital printing has the potential of enabling cleaner printing or even dyeing of cotton fabrics. However, whilst effluent-free digital printing and dyeing of synthetic textile fabrics have seen some success, the same remain elusive for cotton fabrics. The study reported in this paper aimed to optimize the process parameters of cationic pre-treatment with a view to creating a cleaner cotton fabric digital printing process that could be sustainably implemented at bulk-scale production. Thus, process variables were screened using the one-factor-at-a-time approach to select optimum experimental regions. A Box–Behnken design was used to investigate the combined effect of selected factors namely amount of thickener (150–200 g/L), urea (75–125 g/L) and alkali (10–20 g/L) on the color strength, dye fixation and ink penetration of cationized and digital-printed cotton fabrics. The significant models showed excellent fitting of the data. The optimum levels of the factors, namely, amount of thickener, urea and alkali were found 200 g/L, 125 g/L and 10 g/L, respectively. The bulk-scale experiments carried out at optimum levels have shown that an average of ca. 52% of reactive ink, 37.5% of urea and 50% of alkali can be saved by digital printing of cationized cotton along with generation of nearly colorless effluent.

Official URL: https://www.tandfonline.com/doi/full/10.1080/15440...
Subjects: Other > Engineering > H900 Others in Engineering
School or Centre: School of Design
Identification Number or DOI: 10.1080/15440478.2021.1932671
Date Deposited: 14 Apr 2025 10:04
Last Modified: 14 Apr 2025 10:04
URI: https://researchonline.rca.ac.uk/id/eprint/6472
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