Visible‐Light‐Induced Enhanced Photodegradation of Organic Dyes Using Zn‐Embedded Silica: Experimental and Machine‐Learning Optimization of Wastewater Treatment

This research entailed the synthesis and functionalization of mesoporous materials with sulfonic acid groups, subsequently embedding a binuclear Zn complex into the porous matrices. The modified was comprehensively analyzed utilizing several techniques like XRD, NMR, BET, UV, TEM, XPS, etc. The outcomes validate the successful integration of the essential functional groups and Zn complex, as well as the preservation of phase purity, crystalline structure, and morphology. The material showed remarkable photodegradation efficiency when exposed to visible light. Methylene blue, crystal violet, and malachite green exhibited 99% degradation within 15, 10, and 5 min, respectively, illustrating their potential to address environmental challenges associated with organic dye pollution. Moreover, a substantial 91% degradation of rhodamine B transpires within a 30‐min period. This modified material performs exceptionally well in challenging settings, including elevated pH and salinity, showcasing their versatility and resilience across diverse environmental contexts. Additionally, a machine learning pipeline was developed to predict the dye deterioration rate under varying input conditions. Through feature engineering, data preprocessing, and hyperparameter tuning, optimized boosting regressors were utilized for prediction. Performance metrics and feature importance scores revealed that adsorption dosage exerts the greatest influence on the predicted dye deterioration rate. The novelty lies in developing a modified material demonstrating ultrarapid photodegradation of diverse organic dyes under visible light, coupled with exceptional resilience in harsh environmental conditions.