The photocatalytic degradation of Crystal Violet (CV) using ZnO-based nanomaterials presents a promising solution for addressing water pollution caused by synthetic dyes. This review highlights the exceptional efficiency of ZnO and its modified forms—such as doped, composite, and heterostructured variants—in degrading CV under both ultraviolet (UV) and solar irradiation. Key advancements include strategic bandgap engineering through doping (e.g., Cd, Mn, Co), innovative heterojunction designs (e.g., n-ZnO/p-Cu₂O, g-C₃N₄/ZnO), and composite formations with graphene oxide, which collectively enhance visible-light absorption and minimize charge recombination. The degradation mechanism, primarily driven by hydroxyl and superoxide radicals, leads to the complete mineralization of CV into non-toxic byproducts. Furthermore, this review emphasizes the emerging role of Artificial Neural Networks (ANNs) as superior tools for optimizing degradation parameters, demonstrating higher predictive accuracy and scalability compared to traditional methods like Response Surface Methodology (RSM). Potential operational challenges and future directions—including machine learning-driven optimization, real-effluent testing potential, and the development of solar-active catalysts—are further discussed. This work not only consolidates recent breakthroughs in ZnO-based photocatalysis but also provides a forward-looking perspective on sustainable wastewater treatment strategies.

This study explores the enhanced photocatalytic performance of boron-doped zinc oxide (ZnO) nanoparticles synthesized via a scalable mechanochemical route. Utilizing X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), the structural and morphological properties of these nanoparticles were assessed. Specifically, nanoparticles with 1 wt%, 2.5 wt%, and 5 wt% boron doping were analyzed after calcination at temperatures of 500 °C, 600 °C, and 700 °C. The obtained results indicate that 1 wt% B-ZnO nanoparticles calcined at 700 °C show superior photocatalytic efficiency of 99.94% methyl orange degradation under UVA light—a significant improvement over undoped ZnO. Furthermore, the study introduces a predictive model using the artificial neural network (ANN) technique, developed in Python, which effectively forecasts photocatalytic performance based on experimental conditions with R² = 0.9810. This could further enhance wastewater treatment processes, such as heterogeneous photocatalysis, through ANN-guided optimization.

In this study, ZnO–GO nanocomposites were synthesized from waste Zn–C batteries and used for the photocatalytic degradation of malachite green (MG) under UV light. ZnO–GO nanocomposites with different GO contents (1, 2.5, and 5 wt%) were prepared at room temperature and characterized by XRD, SEM, EDS, and UV–Vis spectroscopy. The GO content significantly affects the morphology, optical properties, and photocatalytic activity of the nanocomposites. In the presence of ZnO NPs, a malachite green degradation efficiency of 96.25% was achieved in 90 min, while ZnO–1%GO, ZnO–2.5%GO, and ZnO–5%GO achieved 95.35%, 97.27%, and 99.6% MG degradation, respectively, in just 30 min. The photocatalytic degradation process of MG was optimized using Response Surface Methodology (RSM). The effects of GO content, catalyst dosage, initial MG concentration, and irradiation time on the efficiency of photocatalytic degradation were investigated, and optimal conditions were determined. Under optimal conditions, a photocatalytic degradation efficiency of 98.51% was achieved. These results indicate that ZnO–GO nanocomposites synthesized from waste Zn–C batteries are efficient and environmentally friendly photocatalysts for the treatment of dye-contaminated wastewater.

The persistence and hazardous potential of polycyclic aromatic hydrocarbons (PAHs), with compounds such as anthracene and phenanthrene, raise significant concerns about human health and environmental safety. PAHs are ubiquitous environmental pollutants originating from natural processes and anthropogenic activities, notably fossil fuel combustion. Due to their stability, they tend to accumulate in ecosystems, posing risks to wildlife and human health through bioaccumulation and potential carcinogenicity. Conventional remediation techniques, such as physical adsorption and biological treatment, often fall short in their efficiency and long-term sustainability. Thus, there is an urgent need for innovative methods that can effectively degrade these persistent organic pollutants. Here, we reviewed recent advancements in the photocatalytic degradation of anthracene and phenanthrene, with a focus on metal oxide-based nanocomposites. The major points were: (1) Metal oxides such as TiO₂, ZnO, and CuO, recognized for their photocatalytic properties (they show significantly enhanced efficiency when utilized as a part of nanocomposites, primarily due to the improved charge separation, increased surface area, and numerous active sites); (2) The review of the photocatalytic mechanisms involved in PAH degradation, particularly through the generation of reactive oxygen species that can break down anthracene and phenanthrene into less harmful compounds; and (3) The insights into the formed intermediates and reaction pathways, which can help to deepen the understanding of PAH breakdown and support the design of more efficient catalytic systems for future environmental remediation applications.

The recycling of spent lithium-ion batteries (LIBs) requires efficient and sustainable methods for recovering critical metals. In this study, the leaching behavior of LiCoO₂ cathode material obtained from spent LIBs was investigated in phosphoric acid, using copper powder recovered from waste LIBs as a reducing agent. Leaching experiments were conducted under various conditions (temperature, solid-to-liquid ratio, agitation rate) and compared with systems without copper. In the absence of copper, lithium and cobalt, recoveries after 30 min were approximately 77% and 23%, respectively. The addition of copper significantly enhanced leaching, achieving >96% recovery for both metals at 80 °C, with most extraction occurring within the first 30 min. Kinetic analysis using the shrinking core model indicated a mixed-control mechanism involving both surface chemical reaction and product layer diffusion. The calculated activation energies were 20.2 kJ·mol⁻¹ for lithium and 16.1 kJ·mol⁻¹ for cobalt. Solid residues were characterized by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS). XRD results revealed that the composition of the residues varied with leaching temperature: Co₃O₄ was consistently detected, whereas Cu₈(PO₃OH)₂(PO₄)₄·7H₂O appeared only when leaching was performed above 50 °C. Thermodynamic calculations supported the reductive role of copper and provided insight into possible reaction pathways. These findings confirm the effectiveness of copper-mediated leaching in phosphoric acid and demonstrate that temperature strongly influences residue phase evolution, thereby offering valuable guidance for the design of sustainable LIB recycling processes.