Color and fastness study of wool dyeing in multiple reuse dye baths using acid and reactive dyestuffs in laboratory scale

Moussa, Ali; Ghali, Amel El; Ellouzi, Sabrine; Sakli, Faouzi

doi:10.1080/00405000.2012.718131

Cited by 17 publications

(14 citation statements)

References 10 publications

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“…This minimised the errors in reflectance measurements for this type of woven fabrics; i.e. starting from three measurements, the errors became quasi‐constant …”

Section: Methodsmentioning

confidence: 99%

“…starting from three measurements, the errors became quasi-constant. [24][25][26][27] For evaluating the colour differences between the target colour and the colour reproduced by the proposed recipe, we adopted the Colour Measurement Committee (CMC)(2:1) differences formula in D65/10° (illuminant D65 and 10° standard observer). 28 It is currently the ISO standard for the textiles industry (ISO 105-J03).…”

Section: Colour Measurementmentioning

confidence: 99%

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Colour recipe prediction using ant colony algorithm: principle of resolution and analysis of performances

Chaouch

Moussa

Marzoug

et al. 2019

Coloration Technology

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This paper presents a new method for colour recipe prediction using ant colony optimisation. Three reactive dyes, namely CI Reactive Yellow 145, CI Reactive Red 238 and CI Reactive Blue 235, were used for colour formulation. Samples of 100% cotton fabrics were used for dyeing. The objective was to assure, control and optimise the colour formulation step by determining the dyes to be applied and their respective concentrations to reproduce the desired shades. The criterion of optimisation is to minimise the colour differences [Colour Measurement Committee (2:1)] between the target colour and the colour obtained by the proposed recipe. Errors between the proposed recipe and actual concentrations are also evaluated. The developed algorithm showed good performances with small colour differences between the target and reproduced colours (all lower than 0.7).

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“…This minimised the errors in reflectance measurements for this type of woven fabrics; i.e. starting from three measurements, the errors became quasi‐constant …”

Section: Methodsmentioning

confidence: 99%

Section: Colour Measurementmentioning

confidence: 99%

Colour recipe prediction using ant colony algorithm: principle of resolution and analysis of performances

Chaouch

Moussa

Marzoug

et al. 2019

Coloration Technology

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“…The theoretical color differences [Δ E CMC(2 : 1) ] between the optimal solutions (colors generated by the algorithm) and the target colors (T 1 ) and (

T_{1}^{'}

) are very small equal to 0.275 and 0.886, respectively. These values of color differences are lower than the threshold in the textile industry 32‐34,46‐48 …”

Section: Resultsmentioning

confidence: 79%

Application of genetic algorithm to color recipe formulation using reactive and direct dyestuffs mixtures

Chaouch

Moussa

Marzoug

et al. 2020

Color Research & Application

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Color reproduction is a science in constant development. In this article, a new model to solve the color recipe prediction problem using a genetic algorithm is proposed. The objective is to optimize the color recipe prediction stage by determining the dyes to use in a mixture and their respective proportions to reproduce the target color. Two ranges of dyes were used for dyeing 100% cotton woven fabrics: three reactive dyes (CI Reactive Red 238, CI Reactive Yellow 145, and CI Reactive Blue 235) and four direct dyes (CI Direct Orange 34, CI Direct Red 227, CI Direct Blue 85, and CI Direct Black 22). The criterion of optimization, in reproducing the desired shades, is to minimize the CMC color difference between the desired reference color and the color resulting of the predicted recipe. The proposed algorithm revealed good results with small CMC color differences between target and reproduced colors. The effectiveness of the algorithm was also evaluated and proven by calculating errors between the predicted concentrations in the proposed recipes and the actual concentrations.

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“…To reduce wastewater discharges and environmental impacts, various methods were used to improve the exhaustion and fixation of dyes on wool fiber. These attempts included (a) pretreatment or modification of wool fiber before coloration [10,11,12,13,14,15,16]; (b) synthesis of novel dyestuffs [8,17]; (c) microencapsulation with liposomes [18,19]; (d) reuse of dyebath [20] and seawater [21]; (e) foam dyeing [22]; (g) ultrasound-assisted dyeing [23,24,25]; and (h) solvent-assisted dyeing using mixed solvent [26], supercritical critical fluid, and/or reverse micelle [27,28,29,30,31,32].…”

Section: Introductionmentioning

confidence: 99%

A Computer Color-Matching Study of Reverse Micellar Dyeing of Wool with Reactive Dyes

et al. 2019

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Computer color-matching (CCM) and the levelness of poly(ethylene glycol)-based reverse-micellar dyed wool fabrics in octane and nonane were investigated and compared with a conventional water-based dyeing system. Reflectance curves and calibration curves exhibited no chromatic change and maintained high linearity in both dyeing systems. The linearity of water-dyed calibration curves was slightly higher than that of the reverse-micellar dyed curves. The color yield, in term of K/Ssum values, of solvent-dyed samples was found to be generally higher than that of water-based dyed samples at various calibrated dye concentrations. The concentrations predicted by CCM were close to the theoretical concentrations for both dyeing methods. This indicates that octane- and nonane-assisted reverse-micellar dyeing of wool is able to generate color recipes comparable to the conventional water-based dyeing system. The solvent-dyed samples, measured by the relative unlevelness indices (RUI), exhibit good-to-excellent levelness, which is highly comparable with the water-dyed samples.

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Color and fastness study of wool dyeing in multiple reuse dye baths using acid and reactive dyestuffs in laboratory scale

Cited by 17 publications

References 10 publications

Colour recipe prediction using ant colony algorithm: principle of resolution and analysis of performances

Colour recipe prediction using ant colony algorithm: principle of resolution and analysis of performances

Application of genetic algorithm to color recipe formulation using reactive and direct dyestuffs mixtures

A Computer Color-Matching Study of Reverse Micellar Dyeing of Wool with Reactive Dyes

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