The process of catalytic wet peroxide oxidation (CWPO) of phenol has been investigated in a batch reactor employing (Al2O3/NiMnO3) made from nickel and manganese salts. The sol-gel method was utilized to create the nanocatalyst locally using Al(NO3)3 hydrate as the active ingredient and glycerol as the solvent. In addition to the standard FTIR, XRD, TEM, and SEM characteristics, nanocatalyst's surface area and adsorption capacity were measured. They then used a batch reactor running at various reaction temperatures (40, 50, 60, and 70 °C), concentrations of phenol (200, 300, 400, and 500 ppm), and batch times (60, 80, 100, and 120 min) to check for CWPO. The findings demonstrated that at the best reaction temperature (70°C), batch duration (120 min), and starting concentration (200 ppm), the greatest conversion was (98.37%) for the (8% Al2O3/NiMnO3). An effective ANN model is developed in this study using Python to predict the magnitude of this effect. Phenol removal studies in a wet catalytic peroxide oxidation batch reactor were used to validate the model's output and training data. The dataset is separated into three groups based on temperature, time, and concentration. Phenol was eliminated in order for the ANN model to forecast performance. The data nearly closely matched the projected yield values. 0.99 was the regression coefficient (R2).
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