Multi-scale computational evaluation of triazole derivatives as corrosion inhibitors: DFT and Monte Carlo simulations on Fe(110) and Al(111) metal surfaces

In this paper, we combine quantum computational techniques like Monte Carlo (MC) simulation to predict adsorption energy, and Density Functional Theory (DFT) to investigate electronic structures. The objective of the work is to computationally predict the electronic structures and corrosion inhibition efficiency of novel triazole derivatives (represented by N1–N6), as well as investigate adsorption energy on Fe, Al surfaces in aqueous media using DFT and MC simulations, identifying the most promising candidates for experimental validation. This is the first investigation to computationally investigate the potential of novel triazole derivatives using a variety of methods: DFT/B3LYP/6-311[Formula: see text]G (d, p) in aqueous water, while MC simulation on the Fe(110) and Al(111) with a precision of 10[Formula: see text] [Formula: see text]kcal/mol. To sum, both DFT and MC results indicate that the N6 inhibitor molecule is the facilitator of chemical activity compound, which is characterized by a smaller HOMO, LUMO energy difference of 4.061[Formula: see text]eV, and is better able to adsorb energy of [Formula: see text]64.685 on Al, then [Formula: see text]46.350[Formula: see text]kcal[Formula: see text]mol[Formula: see text] on Fe, compared to the N1–N5 inhibitor. Overall, N6 exhibits the highest inhibition efficiency due to its superior adsorption energy ([Formula: see text]64.85 kcal mol[Formula: see text] on Al(111)) and favorable electronic properties, making it the most promising candidate for anticorrosion applications and pharmacological performance.