Comprehensive review on acid dye treatment and sustainability: engineering approaches, AI and ML integration

The extensive use of acid dyes, particularly in the textile industry, raises serious environmental concerns due to their toxicity and persistence in wastewater. This review explores various treatment methods, including chemical, biological, physical, and advanced oxidation processes (AOPs), highlighting their mechanisms, applications, and effectiveness. It also evaluates integrated approaches and real-world case studies in the field. Additionally, the study assessed the performance of feedforward neural networks (FFNN) and recurrent neural networks (RNN) in predicting acid dye removal, finding both models to be equally effective. This review identifies research gaps, emphasizes the integration of experimental and AI-based modeling methods, and outlines future directions for improving dye-remediation strategies.