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Arabian journal for science and engineering (2011), 2019-01, Vol.44 (1), p.1-32
2019

Details

Autor(en) / Beteiligte
Titel
Atomistic Simulation: A Unique and Powerful Computational Tool for Corrosion Inhibition Research
Ist Teil von
  • Arabian journal for science and engineering (2011), 2019-01, Vol.44 (1), p.1-32
Ort / Verlag
Berlin/Heidelberg: Springer Berlin Heidelberg
Erscheinungsjahr
2019
Link zum Volltext
Quelle
SpringerLink (Online service)
Beschreibungen/Notizen
  • It is difficult to understand the atomistic information on the interaction at the metal/corrosion inhibitor interface experimentally which is a key to understanding the mechanism by which inhibitors prevent the corrosion of metals. Atomistic simulations (molecular dynamics and Monte Carlo) are mostly performed in corrosion inhibition research to give deeper insights into the mechanism of inhibition of corrosion inhibitors on metal surfaces at the atomic and molecular time scales. A lot of works on the use of molecular dynamics and Monte Carlo simulation to investigate corrosion inhibition phenomenon have appeared in the literature in recent times. However, there is still a lack of comprehensive review on the understanding of corrosion inhibition mechanism using these atomistic simulation methodologies. In this review paper, we first of all introduce briefly some important molecular modeling simulations methods. Thereafter, the basic theories of molecular dynamics and Monte Carlo simulations are highlighted. Several studies on the use of atomistic simulations as a modern tool in corrosion inhibition research are presented. Some mechanistic and energetic information on how organic corrosion inhibitors interact with iron and copper metals are provided. This atomic and molecular level information could aid in the design, synthesis and development of new and novel corrosion inhibitors for industrial applications.
Sprache
Englisch
Identifikatoren
ISSN: 2193-567X, 1319-8025
eISSN: 2191-4281
DOI: 10.1007/s13369-018-3605-4
Titel-ID: cdi_proquest_journals_2169320516

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