Molecular modelling of compounds used for corrosion inhibition studies: a review

  • Ebenso, Eno E.; 
  • Verma, Chandrabhan; 
  • Olasunkanmi, Lukman O.; 
  • Akpan, Ekemini D.; 
  • Verma, Dakeshwar Kumar; 
  • ... Lgaz, Hassane; 
  • 외 3명
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198
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228

초록

Molecular modelling of organic compounds using computational software has emerged as a powerful approach for theoretical determination of the corrosion inhibition potential of organic compounds. Some of the common techniques involved in the theoretical studies of corrosion inhibition potential and mechanisms include density functional theory (DFT), molecular dynamics (MD) and Monte Carlo (MC) simulations, and artificial neural network (ANN) and quantitative structure-activity relationship (QSAR) modeling. Using computational modelling, the chemical reactivity and corrosion inhibition activities of organic compounds can be explained. The modelling can be regarded as a time-saving and eco-friendly approach for screening organic compounds for corrosion inhibition potential before their wet laboratory synthesis would be carried out. Another advantage of computational modelling is that molecular sites responsible for interactions with metallic surfaces (active sites or adsorption sites) and the orientation of organic compounds can be easily predicted. Using different theoretical descriptors/parameters, the inhibition effectiveness and nature of the metal-inhibitor interactions can also be predicted. The present review article is a collection of major advancements in the field of computational modelling for the design and testing of the corrosion inhibition effectiveness of organic corrosion inhibitors.

키워드

1 M HCL; DENSITY-FUNCTIONAL THEORY; MILD-STEEL CORROSION; QUANTUM-CHEMICAL CALCULATIONS; ARTIFICIAL NEURAL-NETWORKS; CONSISTENT FORCE-FIELD; SCHIFF-BASE COMPOUNDS; MOLAR NITRIC-ACID; CARBON-STEEL; DYNAMICS SIMULATION
제목
Molecular modelling of compounds used for corrosion inhibition studies: a review
저자
Ebenso, Eno E.; Verma, Chandrabhan; Olasunkanmi, Lukman O.; Akpan, Ekemini D.; Verma, Dakeshwar Kumar; Lgaz, Hassane; Guo, Lei; Kaya, Savas; Quraishi M.A.
DOI
10.1039/d1cp00244a
발행일
2021-09
유형
정기학술지(Article(Perspective Article포함))
저널명
Physical Chemistry Chemical Physics
권
23
호
36
페이지
19987 ~ 20027