This research provides valuable insights into the application of ZnO nanoparticles in photocatalytic wastewater treatment. Process optimization was carried out by determining the ratio of the surface area to the energy band gap (S/E) in the photocatalysis rate under different sources of light (UV light, visible light, sunlight). The nanoparticles were synthesized using the precipitation technique, and the calcination process was carried out within a temperature range of 400 to 700 °C. The structural, morphological, and optical properties of materials were investigated using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), UV-Vis diffuse reflectance (UV-Vis DRS), Raman spectroscopies, and Fourier transform infrared (FTIR) spectroscopies. The study demonstrates that calcination temperature significantly influences the photocatalytic activity of ZnO nanoparticles by altering their size, surface properties, shape, and optical behavior. Optimal decomposition efficiencies of Rhodamine B were achieved at 400 °C, with yields of 24%, 92%, and 91% under visible, UV, and sunlight irradiation, respectively. Additionally, the surface area decreased from 12.556 to 8.445 m²/g, the band gap narrowed slightly from 3.153 to 3.125 eV, and crystal growth increased from 0.223 to 0.506 µm as the calcination temperature rose. The photocatalytic properties of ZnO nanoparticles were assessed to determine their efficiency in decomposing Rhodamine B dye under operational parameters, including pollutant concentration (C0), sample amount, pH level, and reaction time. The sample exhibited the best breakdown rates with C0 = 5 mg/L, solid-to-liquid ratio (S/L) = 50 mg/L, pH = 7, and reaction time = 1 h. Additionally, we combined two oxidation processes, namely H₂O₂ and photocatalytic oxidation processes, which significantly improved the Rhodamine B removal efficiency, where 100% of RhB was degraded after 60 min and 100 µL of H₂O₂.

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance the accuracy, speed, and accessibility of water quality monitoring. Data collected from various water samples in Algeria were analyzed to determine key parameters such as conductivity, turbidity, pH, and total dissolved solids (TDS). These measurements were integrated into deep neural networks (DNNs) to predict indices such as the sodium adsorption ratio (SAR), magnesium hazard (MH), sodium percentage (SP), Kelley’s ratio (KR), potential salinity (PS), exchangeable sodium percentage (ESP), as well as Water Quality Index (WQI) and Irrigation Water Quality Index (IWQI). The DNNs model, optimized through the selection of various activation functions and hidden layers, demonstrated high precision, with a correlation coefficient (R) of 0.9994 and a low root mean square error (RMSE) of 0.0020. This AI-driven methodology significantly reduces the reliance on traditional laboratory analyses, offering real-time water quality assessments that are adaptable to local conditions and environmentally sustainable. This approach provides a practical solution for water resource managers, particularly in resource-limited regions, to efficiently monitor water quality and make informed decisions for public health and agricultural applications.

TiO₂-SiO₂-Fe₂O₃ heterojunction using the ceramic technique was used in this study to investigate its effectiveness as a photocatalyst for Rhodamine B (RhB) dye degradation. Structural, optical, and morphological characterizations of the synthesized materials were carried out by X-ray diffraction (XRD), photoluminescence analysis (PL), scanning electron microscopy (SEM-EDS), and diffuse reflectance spectroscopy (DRS) to calculate the gap energy. In addition, a degradation rate of around 97% was obtained at a pH of 8, an initial RhB concentration of 10 mg·L⁻¹, a TS-1F semiconductor dosage of 1 g·L⁻¹, and a reaction time of 210 min. The ability of photocatalysis to degrade RhB at different ratios, pH, and with/without H₂O₂ in aqueous media was evaluated under UV light, visible light (250 W), and sunlight. When it comes to the degradation of RhB under visible light (250 W) and sunlight, respectively, the influence of the n–p junction showed promising results for the degradation of RhB. In contrast, there was no discernible photocatalytic activity under UV light, which proves that the absorbance switched from UV to visible, demonstrating the decrease in the band gap energy. Additionally, an analysis of the procedure’s cost-effectiveness and reusability through an economic study revealed that the synthesized material was interesting in terms of both cost and sustainability.