<p>This study explores the eco-friendly use of ground coffee pomace, an abundant biomass, as a natural dye source for wool and polyamide fabrics. Dyeing performance was evaluated under varying pH, time, and temperature conditions. The results show that acidic conditions (particularly pH 3), elevated temperatures (up to 100 °C), and extended dyeing times (up to 60&#xa0;min) significantly enhance color yield (<i>K/S</i> values) and deepen fabric shades. The results underscore that ground coffee pomace, a byproduct rich in polyphenolic compounds, represents a viable and environmentally sustainable alternative to conventional synthetic dyes. Its natural dyeing properties offer significant potential for integration into eco-conscious textile manufacturing processes, aligning with the principles of circular economy and green innovation.</p><p>Using a Box–Behnken design approach, the study achieved a high coefficient of determination (<i>R</i><sup>2</sup> ≈ 0.98) for the <i>K/S</i> models developed for wool and polyamide substrates. These results demonstrate the models' strong predictive capability for new dyeing datasets.</p>

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Eco-friendly Dyeing Optimization of Wool and Polyamide Fabrics with Ground Coffee Pomace: a Box-Behnken Design Approach

  • Faouzi Khedher,
  • Boubaker Jaouachi

摘要

This study explores the eco-friendly use of ground coffee pomace, an abundant biomass, as a natural dye source for wool and polyamide fabrics. Dyeing performance was evaluated under varying pH, time, and temperature conditions. The results show that acidic conditions (particularly pH 3), elevated temperatures (up to 100 °C), and extended dyeing times (up to 60 min) significantly enhance color yield (K/S values) and deepen fabric shades. The results underscore that ground coffee pomace, a byproduct rich in polyphenolic compounds, represents a viable and environmentally sustainable alternative to conventional synthetic dyes. Its natural dyeing properties offer significant potential for integration into eco-conscious textile manufacturing processes, aligning with the principles of circular economy and green innovation.

Using a Box–Behnken design approach, the study achieved a high coefficient of determination (R2 ≈ 0.98) for the K/S models developed for wool and polyamide substrates. These results demonstrate the models' strong predictive capability for new dyeing datasets.