Advanced Modeling and Optimization of Acrylic Fibers Cationization Using Combined Response Surface Methodology (RSM) and Artificial Neural Networks (ANN)
摘要
In this study, the non-polarity and low affinity of acrylic fibers for indigo carmine were investigated. To achieve satisfactory dyeing quality, a cationic agent was used to treat the acrylic fibers. The effects of key cationization process parameters namely, the percentage of the cationizing agent, cationization temperature, duration, and cationization bath pH on the dyeing performance of acrylic fibers with indigo carmine were evaluated. Dyeing results were assessed by measuring color strength (K/S) and dye bath exhaustion (E%). The acrylic cationization process was modeled and optimized using a combined approach of artificial neural networks (ANN) and response surface methodology (RSM). The ANN model demonstrated a strong correlation between experimental and predicted color strength values. Optimization using RSM revealed that the optimal conditions for cationization were: 90% cationic agent, pH 4, 75 min of cationization time, and a temperature of 90 ℃, resulting in the best dyeing quality. Cationization of acrylic fibers has proven to be an effective method for enhancing their affinity for indigo carmine.