Artificial neural network optimization of multifunctional wool dyeing with Hypericum scabrum using biomordant and metal biomordant binary systems

The growing demand for sustainable textile coloration has increased interest in natural dyes and eco-friendly mordanting strategies capable of imparting multifunctional properties. In this study, wool yarn was dyed with Hypericum scabrum extract under optimized conditions (pH 5, 90 °C, 90 min, and 100% o.w.f. dye concentration) and treated with biomordants [sumac (SU), eucalyptus (EU), white gallnut (GN), ascorbic acid (AA), and gallic acid (GA)] and metal–biomordant hybrid systems based on aluminium (Al), tin (Sn), copper (Cu), and iron (Fe). Color strength, CIELAB parameters, fastness properties, ultraviolet protection (UPF), and antioxidant activity were evaluated. Biomordanting alone improved dye performance, yielding a maximum K/S value of 2.96 for GN and a UPF of 62.98 for GA. Greater enhancements were achieved with hybrid systems, where the highest color strengths were obtained for Fe/GN (K/S = 6.81), Sn/GA (6.46), and Cu/GA (6.41). Correlation analysis revealed a strong inverse relationship between K/S and lightness ( r = − 0.79). Cu- and Fe-based systems exhibited excellent fastness properties, with dry rubbing fastness of 5 and light fastness of 7–8. Outstanding UV protection was achieved for Cu/GA (UPF 245.06), Fe/GA (232.57), and Sn/GA (219.41), accompanied by extremely low UV B transmittance values (0.002–0.003). Antioxidant activity increased from 5.04% in undyed wool to 98.97% (AA/Sn), 98.47% (GA/Sn), and 98.37% (AA/Cu). Overall, performance followed the order Cu ≈ Fe > Sn > Al > biomordants > unmordanted samples. These findings highlight the potential of ANN-guided optimization for developing sustainable textiles with enhanced coloration, UV protection, and antioxidant functionality.