QSPR models for pyrimidine-based corrosion inhibitors in acid medium

• S. Hadisaputra¹, A.D. Irham¹, A.A. Purwoko¹ and S. Hamdiani²

¹ Chemistry Education Division, FKIP, University of Mataram. Jalan Majapahit No 62, Mataram, 83125, Indonesia
² Department of Chemistry, FMIPA, University of Mataram, Jalan Majapahit No 62, Mataram, 83125, Indonesia

Abstract: The corrosion inhibition properties of pyrimidine derivative inhibitors against iron were analyzed using the quantitative structure-property relationship (QSPR) method and the Monte Carlo adsorption simulation technique. The modelling approach sought to establish correlations between the pyrimidine derivatives’ corrosion inhibition efficiency (IE%) and various electronic physicochemical properties. A prediction model for the anti-corrosion capabilities of an additional inhibitor in the pyrimidine family was developed using the experimental data. Using the QSPR methodology, the model was constructed by connecting the twelve pyrimidine inhibitors’ unique physicochemical properties to their experimental inhibitory efficacy. These physicochemical properties were computed using density functional theory at B3LYP/6-31G(d,p) level of theory. Statistical analyses were performed using three methods: partial least squares regression (PLS), principal component regression (PCR), and principal component analysis (PCA). The PCR method yielded the best QSPR modelling results, as evidenced by validation outcomes (R²=0.985; R²_adj=0.966) and collinearity analysis of the data. The PCR method produces a slight difference between the predicted and the experimented corrosion inhibition efficiency, confirming the method’s accuracy. Predictions from the PCR modelling for the four pyrimidine-derived compounds exhibited promising results. It was shown from the Monte Carlo simulation predictions that the two inhibitors had excellent corrosion inhibition efficiency.

Keywords: QSPR models, pyrimidine, iron, corrosion inhibition, Monte Carlo simulation

Int. J. Corros. Scale Inhib., 2024, 13, no. 3, 1458-1481
doi: 10.17675/2305-6894-2024-13-3-6

Download PDF (Total downloads: 94)

Back to this issue content: 2024, Vol. 13, Issue 3 (pp. 1355-1890)