Predictive Modeling of Triazole Derivatives: Quantum Insights into Corrosion Inhibition

This study explores the corrosion inhibition efficiency of triazole derivatives on mild steel in hydrochloric acid through quantum chemical calculations, Monte Carlo simulations, and QSAR modeling. Key quantum parameters, such as EHOMO, ELUMO, dipole moment, and adsorption energies, were correlated with experimental inhibition efficiencies (IEexp). The study achieved high correlation coefficients (R² = 0.857 to 0.967), validating the predictive QSAR model. This work highlights the potential of triazole compounds as effective, environmentally friendly inhibitors in industrial corrosion protection.

1. Theoretical, Monte Carlo Simulations and QSAR Studies on Some Triazole Derivatives

2. This presentation explores the relationship between the experimental inhibition efficiencies of triazole derivatives as corrosion inhibitors, quantum chemical parameters, and computational studies including Monte Carlo simulations.

3. Table of contents Background Need for Environmentally Friendly Inhibitors Corrosion Inhibitors and Testing Methods Monte Carlo Simulations Quantitative Structure-Activity Relationship (QSAR) Results and Discussion

4. Background Critical equipment for transporting gases and fluids includes pipelines.
Corrosion occurs during processes like acid washing and pickling.
Corrosion inhibitors are essential to prevent metal degradation.

5. Need for Environmentally Friendly Inhibitors Traditional pickling inhibitors are often toxic.
There is a push for non-toxic and environmentally friendly alternatives.
Triazole derivatives are highlighted as effective inhibitors.

6. Corrosion Inhibitors and Testing Methods Electrochemical techniques (EIS, potentiodynamic polarization) are used.
Quantum chemical analysis helps evaluate inhibition and adsorption capabilities.
Correlation between experimental and calculated efficiencies is explored.

7. Monte Carlo Simulations Monte Carlo methods investigate adsorption behavior on metal surfaces.
The study focuses on the Fe (110) surface for stability during simulations.
Calculated adsorption energies for various triazole derivatives.

8. Quantitative Structure-Activity Relationship (QSAR) Various methods employed: AM1, PM3, PM6, PWC, PBE, BLYP.
Correlations between quantum parameters and inhibitor behavior are analyzed.
Non-linear regression is used to derive predictive models.

9. Results and Discussion A strong correlation (R2 = 0.857 to 0.967) between experimental and calculated values.
The models show predictive stability and effectiveness.
Behavior of inhibitors analyzed in terms of energy levels and molecular structure.

10. The research confirms triazole derivatives as effective non-toxic corrosion inhibitors for mild steel in acidic environments, demonstrating strong correlations between theoretical predictions and experimental results.

11. Thank you! Do you have any questions? [email protected] https://scholar.google.com/citations?user=P6jkjZUAAAAJ&hl

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