Corrosion inhibition of mild steel by aminobenzoic acid isomers in hydrochloric acid solution: Efficiency and adsorption mechanisms

Imjjad, Abdallah; Abbiche, Khalid; Mellaoui, Moulay Driss; Jmiai, A.; Baraka, Noureddine El; Taleb, Abdelaziz Ait; Bazzi, Illyass; Issami, S. El; Hilali, Mustapha; Said, Ridha Ben; Hochlaf, M.

doi:10.1016/j.apsusc.2021.151780

Cited by 31 publications

(6 citation statements)

References 76 publications

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“…We took advantage of an improved version of the IGM method based on the Hirshfeld partition of molecular density (IGMH) 16,21 to characterize and visualize the intermolecular interactions. IGMH uses atomic densities determined from the Hirshfeld division of the actual molecule electron densities instead of the free‐state atomic densities used in the IGM 54 approach. Several recent studies have used the non‐covalent interaction (NCI) 68 plot to identify intermolecular interactions in TS and compare the extent of new bond formation in TSs in 32CA reactions 21,23,66 …”

Section: Resultsmentioning

confidence: 99%

“…The Multiwfn Version 3.8 software 39 is used to apply the independent gradient model (IGM) 53,54 method, which is based on electron density topology and utilizes the corresponding monodeterminantal wave functions of the ground state of transition structures as determined at the MPWB1K/6-311G(d) level. The latter approach enables the examination of interactions occurring at the transition states, thereby elucidating the progression of bond formation.…”

Section: Introductionmentioning

confidence: 99%

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Insights into the mechanism of [3+2] cycloaddition reactions between N‐benzyl fluoro nitrone and maleimides, its selectivity and solvent effects

Boutiddar,

Abbiche,

Mellaoui

et al. 2023

J Comput Chem

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We present a theoretical study of the [3+2] cycloaddition (32CA) reactions of N‐benzyl fluoro nitrone with a series of maleimides producing isoxazolidines. We use the Molecular Electron Density Theory at the MPWB1K/6‐311G(d) level. We focus on the reaction mechanism, selectivity, solvent, and temperature effects. In addition, we perform topological analyses at the minimal and transition states to identify the intermolecular interactions. Electron Localization Function approach classifies the N‐benzyl fluoro nitrone as zwitterionic (zw‐) three‐atom components (TACs), associated with a high energy barrier. The low polar character of the reaction is evaluated using the Conceptual Density Functional Theory analysis of the reactants, confirmed by the low global electron density transfer computed at the transition states. Computations show that these 32CA reactions follow a one‐step mechanism under kinetic control, with highly asynchronous bond formation and no new covalent bond is formed at the TS. Besides, the potential energy surfaces along the reaction pathways in gas phase and in solvent are mapped. The corresponding Gibbs free energy profiles reveal that the exo‐cycloadducts are kinetically and thermodynamically more favored than endo‐cycloadducts, in agreement with the exo‐selectivity observed experimentally. In particular, we found that solvent and temperature did not affect this selectivity and mainly influence the activation energies and the exothermic character of these 32CA reactions.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Insights into the mechanism of [3+2] cycloaddition reactions between N‐benzyl fluoro nitrone and maleimides, its selectivity and solvent effects

Boutiddar,

Abbiche,

Mellaoui

et al. 2023

J Comput Chem

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“…All quantum calculations were performed in gas and aqueous phase using the self-consistent field theory (SCF), with the polarised continuum model (PCM) [27]. The ionisation energy and electron affinity were determined by the values of the energies of the HOMO and LUMO orbitals using Equations (3) & (4) [19,28,29]: …”

Section: Theory and Computational Detailsmentioning

confidence: 99%

“…The values of I and A are exploited in order to find the values of the electronegativity, the global hardness and the softness of the inhibitor molecule, Equations (5), (6) & (7) [29,30]: …”

Section: Theory and Computational Detailsmentioning

confidence: 99%

Understanding imidazole derivatives effect as a corrosion inhibitor for brass in nitric acid: a combined experimental and theoretical assessments

Asri

Jmiai

Lin

et al. 2022

Corrosion Engineering, Science and Technology

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This paper presents a new study on imidazole derivatives namely 1H-imidazole (IM), N-methylimidazole (MIM) and 1H-benzimidazole (BIM) as a corrosion inhibitor for brass in nitric acid medium. Electrochemical results demonstrate that the inhibition increases with a high concentration of imidazole derivatives; the inhibitory efficiency reaches a maximum of 94% at 10-2 mol L −1 for BIM. SEM morphology and EDS analysis show that these derivatives are adsorbed onto the brass interface, the brass sample is effectively protected and the surface becomes relatively flat, which is more significant in the presence of 1H-benzimidazole. FTIR results confirm the retention of BIM on the interface of Cu-Zn alloys. In addition, quantum chemistry calculation manifests that the three derivatives can reveal high anticorrosion properties. Molecular dynamics simulation data manifest that the three imidazole derivatives can be adsorbed at the brass surface in a paralleled way, and have large binding energy. Highlights. A new action of imidazole derivatives to mitigate brass corrosion was explored in HNO 3 .. BIM showed inhibitory efficiency more than 94% in HNO 3 solution.. The inhibition mechanism is studied using SEM/EDS surface analysis and FTIR analysis.. The calculated adsorption energies are ranked in the following order: BIM > MIM > IM.. Theoretical and experimental results lead to used imidazole derivatives as potential corrosion inhibition for brass in HNO 3 solution.

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“…These extracts exhibit the capability to establish chemical bonds with metal atoms, thereby forming a protective layer that shields against attacks from aggressive ions. Compounds featuring heteroatom groups (e.g., O, N, S, and P) and aromatic rings are prevalent in extracts of natural ingredients, representing optimal candidates for effective utilization as corrosion inhibitors [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors

Akrom,

Rustad,

Dipojono

2024

Phys. Scr.

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This paper presents a quantitative structure–property relationship (QSPR)-based machine learning (ML) framework designed for predicting corrosion inhibition efficiency (CIE) values in natural organic inhibitor compounds. The modeling dataset comprises 50 natural organic compounds, with 11 quantum chemical properties (QCP) serving as input features, and the target variable being the corrosion inhibition efficiency (CIE) value. To enhance the predictive accuracy of the ML model, the kernel density estimation (KDE) function is employed to generate virtual samples during the training process, with the overarching goal of refining the precision of the ML model. Three distinct models, namely random forest (RF), gradient boosting (GB), and k-nearest neighbor (KNN), are tested in the study. The results demonstrate a noteworthy enhancement in the prediction performance of the models, attributable to the incorporation of virtual samples that effectively improve the correlation between input features and target values. Consequently, the accuracy of the predicted CIE values is significantly augmented, aligning more closely with the actual CIE values. Performance improvements were evident across all models after the incorporation of virtual samples. The GB, RF, and KNN models exhibited increments in R2 values from 0.557 to 0.996, 0.522 to 0.999, and 0.415 to 0.994, respectively, concomitant with the introduction of 500 virtual samples. Additionally, each model demonstrated a notable reduction in RMSE values, transitioning from 1.41 to 0.19, 1.27 to 0.10, and 1.22 to 0.16, respectively. While the GB model initially outperformed others before the addition of virtual samples, the performance of the model exhibited fluctuation as the number of virtual samples varied. This behavior suggests that the KDE function provides a certain level of resilience against model variations. The proposed approach contributes to the effective design and exploration of corrosion inhibitor candidates, offering a reliable and accurate predictive tool that bridges the gap between theoretical studies and experimental synthesis.

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Corrosion inhibition of mild steel by aminobenzoic acid isomers in hydrochloric acid solution: Efficiency and adsorption mechanisms

Cited by 31 publications

References 76 publications

Insights into the mechanism of [3+2] cycloaddition reactions between N‐benzyl fluoro nitrone and maleimides, its selectivity and solvent effects

Insights into the mechanism of [3+2] cycloaddition reactions between N‐benzyl fluoro nitrone and maleimides, its selectivity and solvent effects

Understanding imidazole derivatives effect as a corrosion inhibitor for brass in nitric acid: a combined experimental and theoretical assessments

A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors

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