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Solar-driven photocatalytic removal of cefuroxime from water: process optimization <i>via</i> machine learning and nature-inspired algorithms

Sara Zeghbib, Noureddine Nasrallah, Haroun Hafsa, Mohammed Kebir, Hichem Tahraoui, Sabrina Lekmine, Walid Zeghbib, Abdeltif Amrane, Fekri Abdulraqeb Ahmed Ali, Farid Fadhillah, Aymen Amine Assadi

2025RSC Advances9 citationsDOIOpen Access PDF

Abstract

, 180 min reaction time). The integration of machine learning-based modeling and nature-inspired optimization highlights an effective approach for enhancing photocatalytic processes. The results provide a robust framework for optimizing semiconductor-based water treatment technologies, contributing to sustainable environmental remediation strategies.

Topics & Concepts

PhotodegradationPhotocatalysisMaterials scienceDegradation (telecommunications)CatalysisNanoparticlePhotochemistryRadicalOxideVisible spectrumChemical engineeringCefuroximeComputer scienceDopingAlgorithmMachine learningScavengerLeaching (pedology)KineticsNanotechnologyProcess optimizationAbsorption (acoustics)Nuclear chemistryPartial least squares regressionAdvanced Photocatalysis TechniquesTiO2 Photocatalysis and Solar CellsSolar-Powered Water Purification Methods
Solar-driven photocatalytic removal of cefuroxime from water: process optimization <i>via</i> machine learning and nature-inspired algorithms | Litcius