Molecular modelling of compounds used for corrosion inhibition studies: a review
Physical Chemistry Chemical Physics Pub Date: 2021-05-27 DOI: 10.1039/D1CP00244A
Abstract
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.
Recommended Literature
- [1] Establishing the accuracy of position-specific carbon isotope analysis of propane by GC-pyrolysis-GC-IRMS ChangjieLiu,PengLiu,XiaofengWang,XiaoqiangLi,JuskeHorita 10.1002/rcm.9494
- [2] Ester-mediated peptide formation promoted by deep eutectic solvents: a facile pathway to proto-peptides? Chen-Yu Chien,Sheng-Sheng YuChem. Commun., 2020,56, 11949-11952 10.1039/D0CC03319G
- [3] Excimer–monomer switch: a reaction-based approach for selective detection of fluoride? Qiao Song,Angela Bamesberger,Lingyun Yang,Haley Houtwed,Haishi CaoAnalyst, 2014,139, 3588-3592 10.1039/C4AN00522H
- [4] Evidence of rutile-to-anatase photo-induced electron transfer in mixed-phase TiO2 by solid-state NMR spectroscopy? Weili Dai,Guangjun Wu,Michael HungerChem. Commun., 2015,51, 13779-13782 10.1039/C5CC04971G
- [5] Excimer formation effects and trap-assisted charge recombination loss channels in organic solar cells of perylene diimide dimer acceptors? Min Kim,Jae-Joon Lee,Tengling Ye,Panagiotis E. Keivanidis,Kilwon ChoJ. Mater. Chem. C, 2020,8, 1686-1696 10.1039/C9TC04955J
- [6] Fast synthesis of red Li3BaSrLn3(WO4)8:Eu3+ phosphors for white LEDs under near-UV excitation by a microwave-assisted solid state reaction method and photoluminescence studies Bo Wei,Zhenyu Liu,Chen Xie,Shu Yang,Wentao Tang,Aiwei Gu,Wing-Tak Wong,Ka-Leung WongJ. Mater. Chem. C, 2015,3, 12322-12327 10.1039/C5TC03165F
- [7] Excimer emission and magnetoluminescence of radical-based zinc(ii) complexes doped in host crystals? Shojiro Kimura,Tetsuro KusamotoChem. Commun., 2020,56, 11195-11198 10.1039/D0CC04830E
- [8] Emulsion soft templating of carbide-derived carbon nanospheres with controllable porosity for capacitive electrochemical energy storage? M. Zeiger,N. J?ckel,P. Strubel,L. Borchardt,R. Reinhold,W. Nickel,J. Eckert,V. Presser,S. KaskelJ. Mater. Chem. A, 2015,3, 17983-17990 10.1039/C5TA03730A
- [9] Emergence of microfluidic wearable technologies Joo Chuan Yeo,KenryLab Chip, 2016,16, 4082-4090 10.1039/C6LC00926C
- [10] Evolution in surface coverage of CH3NH3PbI3?XClXvia heat assisted solvent vapour treatment and their effects on photovoltaic performance of devices Dhirendra K. Chaudhary,Pramendra Kumar,Lokendra KumarRSC Adv., 2016,6, 94731-94738 10.1039/C6RA18729C
Journal Name:Physical Chemistry Chemical Physics
research_products
-
CAS no.: 89640-58-4