Computational Modelling and Simulations for Designing of Corrosion Inhibitors

Fundamentals and Realistic Applications

Dakeshwar Kumar Verma, Chandrabhan Verma, Jeenat Aslam

• Publisher: Elsevier
• Year: 2023
• Print ISBN:
  9780323951616
• eBook ISBN:
  9780323951623
• Topic: Technology & Engineering
• Subtopic: Chemical & Biochemical Engineering
• Index: Technology & Engineering

Computational Modeling and Simulations for Designing of Corrosion Inhibitors: Fundamentals and Realistic Applications offers a collection of major advancements in the field of computational modeling for the design and testing of corrosion inhibition effectiveness of organic corrosion inhibitors. This guide presents the latest developments in molecular modeling of organic compounds using computational software, which has emerged as a powerful approach for theoretical determination of corrosion inhibition potentials of organic compounds. The book covers common techniques involved in theoretical studies of corrosion inhibition potentials, and mechanisms such as density functional theory, molecular dynamics, Monte Carlo simulations, artificial neural networks, and quantitative structure-activity relationship. - Covers basic, fundamental principles, advantages, parameters, and applications of computational and molecular modeling for designing potential corrosion inhibitors for metals and alloys - Describes advancements of computational modeling for the design of organic corrosion inhibitors and applications in electrochemical engineering and materials science - Focuses on the most advanced applications in industry-oriented fields, including current challenges - Includes websites of interest and information about the latest research

Table of contents

• Cover
• Title page
• Table of Contents
• Copyright
• Contents
• List of contributors
• List of Illustrations
• List of Tables
• Chapter 1 : Corrosion inhibition: current trends and challenges
• Chapter 2 : Theory of corrosion and corrosion inhibition
• Chapter 3 : Organic corrosion inhibitors
• Chapter 4 : Deep understanding of corrosion inhibition mechanism based on first-principle calculations
• Chapter 5 : Molecular modeling in corrosion inhibition assessment
• Chapter 6 : Density functional theory-based molecular modeling
• Chapter 7 : Density functional theory (DFT)-based molecular modeling
• Chapter 8 : Molecular dynamics simulation-based computational modeling
• Chapter 9 : Monte Carlo simulation-based molecular modeling
• Chapter 10 : QSAR and ANN-based molecular modeling
• Chapter 11 : MEPTIC and machine learning approaches of corrosion inhibition
• Chapter 12 : Explicit modeling of corrosion inhibition
• Chapter 13 : Electrochemical principles of corrosion inhibition: fundamental and computational aspects of density functional theory (DFT)
• Chapter 14 : Theories and radial distribution function of MD and MC simulations
• Chapter 15 : Important parameters derived from Monte Carlo (MC) and Molecular Dynamics (MD) simulations
• Chapter 16 : Theories methods and the parameters of quantitative structure–activity relationships and artificial neural network
• Chapter 17 : Theoretical calculation-based results of plant extract as green corrosion inhibitors
• Chapter 18 : Aliphatic organic compounds as corrosion inhibitors for ferrous and nonferrous metals
• Chapter 19 : Nitrogen-containing heterocyclic compounds as green corrosion inhibitors
• Chapter 20 : Oxygen-containing heterocyclic compounds as green corrosion inhibitors
• Chapter 21 : Phosphorus containing molecules as green corrosion inhibitors
• Chapter 22 : Carbohydrates and derivatives as green corrosion inhibitors
• Chapter 23 : Pharmaceutical drugs as prominent corrosion inhibitors: fundamental and computational aspects of density functional theory
• Chapter 24 : Ionic liquids as green corrosion inhibitor
• Chapter 25 : Quantitative structure–activity relationship and artificial neural network-based results for designing corrosion inhibitors
• Index
• A