Azadirachta indica Seed Oil Epoxidation Using Sulfuric Acid as a Catalyst; Response Surface Methodology and Particle Swarm-Based Evaluation and Optimization

Response surface methodology (RSM) was employed in this study to optimize the epoxidation of Azadirachta indica seed oil (AISO) in the presence of sulfuric acid as a catalyst. The independent variables were (catalyst concentration, time, and temperature) while iodine and oxirane values were the dependent variables. The (analysis of variance) ANOVA showed a second-order polynomial model with a predicted R² value of 0.8530 for iodine value and 0.8114 for oxirane value indicating the model's acceptability. The experimental results [one factor at a time (OFAT), 3D, and contour plots] showed that the process parameters (catalyst concentration, time, and temperature) had a significant impact on the iodine and oxirane value. The model established from ANOVA was optimized using a metaheuristic algorithm—Particle Swarm Optimization (PSO) and validated with RSM-predicted optimal values. The optimal (RSM) iodine value (12.7 g I₂/100g) and oxirane value of 4.910% were obtained at a catalyst concentration of 1.2 mol/L, a reaction time of 14,400 s, and a reaction temperature of 50 °C with a desirability of 1.000. PSO optimal iodine value (7.9 g I₂/100g) and oxirane value of 5.172% were obtained at the same optimal conditions. The results demonstrated that PSO was slightly better than RSM.Nevertheless, both results optimized AISO efficiently and agreed with the experimental data (iodine value—8.25 g I₂/100g; oxirane value—5.134%). The characterizations result via FT-IR (Fourier transform infrared spectroscopy) and GCMS (gas chromatography mass spectrometer) indicated the successful formation of epoxides on AISO for its utilization as intermediates for lubricants and polyols. These results showed that the proposed models enhanced the stability of the AISO epoxidation and reduced the cost and processing time.