Titanium dioxide (TiO₂) based photocatalysts have been widely used as a photocatalyst for the degradation of various persistent organic compounds in water and air. The degradation mechanism involves the generation of highly reactive oxygen species, such as hydroxyl radicals, which react with organic compounds to break down their chemical bonds and ultimately mineralize them into harmless products. In the case of pharmaceutical and pesticide molecules, TiO₂ and modified TiO₂ photocatalysis effectively degrade a wide range of compounds, including antibiotics, pesticides, and herbicides. The main downside is the production of dangerous intermediate products, which are not frequently addressed in the literature that is currently available. The degradation rate of these compounds by TiO₂ photocatalysis depends on factors such as the chemical structure of the compounds, the concentration of the TiO₂ catalyst, the intensity, the light source, and the presence of other organic or inorganic species in the solution. The comprehension of the degradation mechanism is explored to gain insights into the intermediates. Additionally, the utilization of response surface methodology is addressed, offering a potential avenue for enhancing the scalability of the reactors. Overall, TiO₂ photocatalysis is a promising technology for the treatment of pharmaceutical and agrochemical wastewater, but further research is needed to optimize the process conditions and to understand the fate and toxicity of the degradation products.

Harnessing the synergistic potential of graphene oxide-doped titanium dioxide (GO-TiO₂), this study pioneers an advanced photocatalytic approach by incorporating graphene oxide-doped titanium dioxide (GO-TiO₂) as a catalyst to enhance the photocatalytic degradation of levofloxacin (LVX), with optimisation of parameters using response surface methodology (RSM) and artificial neural networks (ANNs). By adjusting key operational parameters such as catalyst dosage, LVX concentration, pH, and percentage dopant in TiO₂, the study aimed to maximise degradation efficiency. The RSM statistical model highlighted optimal conditions, i.e., neutral pH, 0.1 g/g dopant, 1.1 g/L catalyst, and 25 ppm LVX concentration, achieving a degradation efficiency close to 80% (R² = 0.88). An ANN model was also developed, offering a three-layer neural network that accurately predicts LVX degradation under varied conditions, with R² reaching 0.97. Current modelling techniques frequently fail to strike a balance between practical insights for optimising photocatalytic degradation and predictive accuracy. By combining the parametric insights of RSM with the nonlinear predictive power of ANN, this study closes that gap and develops a sustainable, data-driven framework for effectively breaking down pharmaceutical pollutants and developing environmentally friendly wastewater treatment methods.

The extensive consumption of freshwater resources and the continuous discharge of pharmaceutical residues pose serious risks to aquatic ecosystems and public health. In this study, pristine ZnO, TiO₂, Zn@TiO₂, and Ti@ZnO nanocomposites were synthesized via a precipitation-assisted solid–liquid interference method and systematically evaluated for the photocatalytic degradation of the antibiotic levofloxacin under UV and visible light irradiation. The structural, optical, and surface properties of the synthesized materials were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), UV–visible diffuse reflectance spectroscopy (UV–DRS), and X-ray photoelectron spectroscopy (XPS). XRD analysis confirmed the crystalline nature of all samples, while SEM images revealed spherical and agglomerated morphologies. Photocatalytic experiments were conducted using a 50-ppm levofloxacin solution with a catalyst dosage of 1 g L⁻¹. Pristine ZnO exhibited limited visible-light activity (33.81%) but high UV-driven degradation (92.98%), whereas TiO₂ showed comparable degradation efficiencies under UV (78.6%) and visible light (78.9%). Notably, Zn@TiO₂ nanocomposites demonstrated superior photocatalytic performance, achieving over 90% and near 70% degradation under both UV and visible light, respectively, while Ti@ZnO composites exhibited less than 60% degradation. The enhanced activity of Zn@TiO₂ is attributed to improved interfacial charge transfer, suppressed electron–hole recombination, and extended light absorption. These findings highlight Zn@TiO₂ nanocomposites as promising photocatalysts for efficient treatment of pharmaceutical wastewater under dual-light irradiation.

Heterogeneous catalysts are the crucial components for the efficient conversion of reactants; however, their lifespan depends on a range of reactor operating conditions, and catalytic metals constitute the fundamental active components of modern catalytic engineering. The recovery and recycling of precious metals from the spent catalysts is essential to achieve sustainable development goals. Conventional pyrometallurgy and hydrometallurgy have been implemented for the recycling of precious metals. However, these methodologies are facing operational difficulties, including high energy consumption, hazardous effluent generation, and adverse environmental impacts. In contrast, biometallurgical approaches are eco‐friendly but exhibit slow kinetics and limited commercialization potential. Consequently, several advanced techniques, such as microwave‐supported extraction, mineral phase reconstruction, ionic liquid extraction, solvent extraction, electro‐winning technique, and molecular recognition technology, have been explored at an experimental level. Experimental studies are going on to overcome the limitations of traditional methods. In this review, we will summarize current recycling methodologies, identify critical challenges and research gaps, and evaluate the scope of progressive approaches for the selective separation of target metals from unwanted spent catalyst matrices. The efficient recycling of discarded catalysts and facilitating the manufacturing of new catalytic materials support circular economy principles and sustainability by reducing dependence on original primary resources.