Computational Modeling: Theoretical Predictive Tools for Designing of Potential Organic Corrosion Inhibitors

Dakeshwar Kumar Verma, Ruby Aslam, Jeenat Aslam, M. A. Quraishi, Eno E. Ebenso, Chandrabhan Verma*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

93 Scopus citations

Abstract

Computational modelings have immersed as powerful tools for designing of efficient corrosion inhibitors for several metals in many electrolytes. One of the greatest advantages of the modeling techniques is that effectiveness of compounds to be used as inhibitors towards metallic corrosion inhibition can be theoretically derived before their chemical synthesis. Quantum chemical calculations using density functional theory (DFT) gives informations about the molecular sites responsible for interactions with metallic surface. Molecular dynamics (MD) and Monte Carlo (MC) simulations give the information about the orientation of inhibitor molecules on the metallic surface. The MD and MC simulations also provide the information about the nature of metal-inhibitor interactions in the form of energy of adsorption (Eads). Present review describes the basics DFT, MD and MC simulations and detailed description about the correlation of these parameters with the corrosion inhibition ability of organic compounds.

Original languageEnglish
Article number130294
JournalJournal of Molecular Structure
Volume1236
DOIs
StatePublished - 15 Jul 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

  • Computational modelings
  • Corrosion inhibition
  • DFT
  • MD and MC simulations
  • Mixed type
  • Simulations
  • Structural effect

ASJC Scopus subject areas

  • Analytical Chemistry
  • Spectroscopy
  • Organic Chemistry
  • Inorganic Chemistry

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