Artificial Intelligence Techniques and Response Surface Methodology for the Optimization of Methyl Ester Sulfonate Synthesis from Used Cooking Oil by Sulfonation

Adeyinka Sikiru Yusuff; Niyi Babatunde Ishola; Afeez Olayinka Gbadamosi

doi:10.1021/acsomega.2c08117

Artificial Intelligence Techniques and Response Surface Methodology for the Optimization of Methyl Ester Sulfonate Synthesis from Used Cooking Oil by Sulfonation

ACS Omega. 2023 May 24;8(22):19287-19301. doi: 10.1021/acsomega.2c08117. eCollection 2023 Jun 6.

Authors

Adeyinka Sikiru Yusuff¹, Niyi Babatunde Ishola², Afeez Olayinka Gbadamosi³

Affiliations

¹ Department of Chemical and Petroleum Engineering, College of Engineering, Afe Babalola University, Ado-Ekiti 23438, Nigeria.
² Department of Chemical Engineering, Faculty of Technology, Obafemi Awolowo University, Ile-Ife 23438, Nigeria.
³ Department of Petroleum Engineering, College of Petroleum and Geosciences, King Fahd University of Petroleum and Minerals, 31261 Dhahran, Saudi Arabia.

Abstract

Herein, the impacts of sulfonation temperature (100-120 °C), sulfonation time (3-5 h), and NaHSO₃/methyl ester (ME) molar ratio (1:1-1.5:1 mol/mol) on methyl ester sulfonate (MES) yield were studied. For the first time, MES synthesis via the sulfonation process was modeled using the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and response surface methodology (RSM). Moreover, particle swarm optimization (PSO) and RSM methods were used to improve the independent process variables that affect the sulfonation process. The RSM model (coefficient of determination (R²) = 0.9695, mean square error (MSE) = 2.7094, and average absolute deviation (AAD) = 2.9508%) was the least efficient in accurately predicting MES yield, whereas the ANFIS model (R² = 0.9886, MSE = 1.0138, and AAD = 0.9058%) was superior to the ANN model (R² = 0.9750, MSE = 2.6282, and AAD = 1.7184%). The results of process optimization using the developed models revealed that PSO outperformed RSM. The ANFIS model coupled with PSO (ANFIS-PSO) achieved the best combination of sulfonation process factors (96.84 °C temperature, 2.68 h time, and 0.92:1 mol/mol NaHSO₃/ME molar ratio) that resulted in the maximum MES yield of 74.82%. Analysis of MES synthesized under optimum conditions using FTIR, ¹H NMR, and surface tension determination showed that MES could be prepared from used cooking oil.