Newly synthesized 1-butyl-3-methylimidazolium p-toluenesulfonate ionic liquid for acid corrosion of API 5L X70 steel: Experimental, DFT/MD-simulation, statistical and machine learning predictions

In this latest work, newly synthesized 1-butyl-3-methylimidazolium p-toluenesulfonate ionic liquid ([C 4 MIM][TOs] (IL)) was utilized as corrosion inhibitor for API 5L X70 steel in 1 M H 2 SO 4 environment. Herein, extensive empirical datasets from mass loss, electrochemical studies, density functional theory (DFT)/molecular dynamics simulation (MD-simulation), were appraised, modeled, and numerically evaluated. Scanning electron microscope (SEM)/laser scanning confocal microscopy (LSCM) was used to study and analyze the inhibited and uninhibited samples of API 5L X70 steel in 1 M H 2 SO 4 solution. Statistical technique (response surface methodology (RSM)), artificial neural network-genetic algorithm (ANN-GA), and adaptive neural fuzzy inference system-genetic algorithm (ANFIS-GA) were deployed as an optimization instrument to forecast the percentage inhibition efficiency (% η ). From the results developed, optimum values of % η of [C 4 MIM][TOs] were documented as 80.36 %, 84 %, and 85.93 % at 0.8 g/L [C 4 MIM][OTs] concentration and temperatures of 313 K for mass loss, potentiodynamic polarization (PDP) measurement and electrochemical impedance spectroscopy (EIS) approach, respectively. PDP outcome revealed [C 4 MIM][OTs] worked prone to a mixed command mechanism of a cathodic prevalence. Kinetic investigations better suited the Langmuir adsorption isotherm and the parameters of activation energy were computed and considered. The SEM/LSCM morphological investigation showed that the value of the surface roughness for the API 5L X70 steel surface decreases from 7.68 μm to 1.09 μm for the uninhibited and inhibited metal, respectively. This confirmed that [C 4 MIM][TOs] molecules evolved a preventive film onto the API 5L X70 steel surface. The DFT results displayed the potential of [C 4 MIM][OTs] molecules to bond firmly onto the metal surface. MD-simulation approach manifested that the adsorption energy value of the [C 4 MIM][OTs] molecules is higher in the solvated phase compared to the gas phase. RSM, ANN-GA, and ANFIS-GA were engaged for optimization, modeling, and computation of error functions therein, coefficient of correlation (R 2 ), root-mean-squared-error (RMSE), average relative error ARE (%), mean square deviation (MSD) and Chi square ( λ ), were utilized to determine the model's susceptibility. The outcomes revealed that the three (3) optimization designs exhibited outstanding forecasting power with R 2 values of 0.99971, 0.99840, and 0.98991 for the ANFIS, RSM and ANN, respectively. The calculated error indices of ARE (%) (ANFIS = 1.5224, RSM = 1.6428, and ANN = 3.6322), RMSE (ANFIS = 0.01861, RSM = 0.01781, and ANN = 0.22280), MSD (ANFIS = 0.01614, RSM = 0.04212 and ANN = 0.06224) and Chi square (ANFIS = 0.02652, RSM = 0.13630 and ANN = 3.34611) proposed excellent relationship linking the actual and forecasted values. Thus, models proffer reasonable forecasts that were in better accord with the empirical data sets, though the ANFIS and the RSM models offer excellent forecast compared to the ANN model. • [C 4 MIM][OTs] molecules produced notable percentage inhibition efficiency as proved by the empirical, statistical and machine learning predictions. • [C 4 MIM][OTs] adsorption is physisorption and spontaneous and obeyed Langmuir adsorption isotherm. • RSM, ANN, and ANFIS models were acceptable for prediction of percentage inhibition efficiency of [C 4 MIM][OTs]. • DFT and MD-simulation were used to explore the molecular indices and correlate with the empirical outcomes. • SEM and LSCM images evidently confirm the presence of a preservative surface coat.