Computational methods of corrosion monitoring
- Authors
- Lgaz, Hassane; Chaouiki, Abdelkarim; Al-Hadeethi, Mustafa R.; Salghi, Rachid; Lee, Han-Seung
- Issue Date
- Nov-2021
- Publisher
- wiley
- Keywords
- Artificial neural network; Corrosion inhibitor; DFT; Molecular dynamics; Monte carlo; QSAR
- Citation
- Organic Corrosion Inhibitors: Synthesis, Characterization, Mechanism, and Applications, pp 39 - 57
- Pages
- 19
- Indexed
- SCOPUS
- Journal Title
- Organic Corrosion Inhibitors: Synthesis, Characterization, Mechanism, and Applications
- Start Page
- 39
- End Page
- 57
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/120557
- DOI
- 10.1002/9781119794516.ch3
- Abstract
- In recent decades, considerable progress has been made in the development of computational tools. Computer simulations were used as innovative tools to answer complex questions in a way that experiments cannot do. Like many research fields, computational methods were extensively used in corrosion inhibition research. Density functional theory (DFT), molecular Dynamics (MD) simulations, Monte Carlo (MC) simulations, as well as quantitative structure-activity relationships (QSARs) and artificial neural network (ANN) were applied in many corrosion inhibition studies to discover the underlying inhibition mechanism. In this chapter, efforts were made to discuss the recent progress in using computational methods for corrosion inhibition, the present and future challenges. © 2022 John Wiley & Sons, Inc.
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > MAJOR IN ARCHITECTURAL ENGINEERING > 1. Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.