Combined experimental and computational studies on corrosion inhibition of Houttuynia cordata leaf extract for steel in HCl medium

Corrosion Inhibition of Mild Steel in Hydrochloric Acid Environments Containing Sonneratia caseolaris Leaf Extract

Sonneratia caseolaris leaf extract was characterized for its mitigation of the electrochemical corrosion of steel in naturally aerated hydrochloric acid environments by electrochemical methods and surface analysis. The presence of S. caseolaris leaf extract (SCLE) in the hydrochloric acid medium ameliorated the corrosion resistance of steel via the adsorption of SCLE species to form a barrier layer. The improved inhibition effectiveness was demonstrated to be independent of the SCLE concentration and the corrosive environment. The highest inhibition performance of approximately 98% was reached for steel in a 1 M HCl medium containing 2500 ppm SCLE. The performance significantly decreased with a decrease in the HCl concentration from 1.00 to 0.01 M with the same SCLE concentration. In addition, severe corrosion occurred on the uninhibited steel surface but was significantly reduced on the inhibited steel surface. The analyzed results also indicated the existence of electronegative functional groups in SCLE, which could promote the adsorption process for the self-formation of the barrier layer on the steel surface. The work reported herein suggested a powerful strategy to mitigate electrochemical corrosion by adding an effective new inhibitor to achieve a green inhibitor system.

Molecular modelling of compounds used for corrosion inhibition studies: a review

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.

An Overview of Molecular Dynamic Simulation for Corrosion Inhibition of Ferrous Metals

Molecular dynamics (MD) simulation is a powerful tool to study the molecular level working mechanism of corrosion inhibitors in mitigating corrosion. In the past decades, MD simulation has emerged as an instrument to investigate the interactions at the interface between the inhibitor molecule and the metal surface. Combined with experimental measurement, theoretical examination from MD simulation delivers useful information on the adsorption ability and orientation of the molecule on the surface. It relates the microscopic characteristics to the macroscopic properties which enables researchers to develop high performance inhibitors. Although there has been vast growth in the number of studies that use molecular dynamic evaluation, there is still lack of comprehensive review specifically for corrosion inhibition of organic inhibitors on ferrous metal in acidic solution. Much uncertainty still exists on the approaches and steps in performing MD simulation for corrosion system. This paper reviews the basic principle of MD simulation along with methods, selection of parameters, expected result such as adsorption energy, binding energy and inhibitor orientation, and recent publications in corrosion inhibition studies.

Quantum Chemical and Monte Carlo Simulation Studies on Inhibition Performance of Caffeine and Its Derivatives against Corrosion of Copper

Performance tests on caffeine’s corrosion inhibition properties and their derivatives against copper corrosion have been previously reported experimentally using gravimetric and electrochemical analyses. The test was able to measure the efficiency of their corrosion inhibition accurately. However, the caffeine and its derivatives’ structure patterns and coating mechanisms when interacting with metals during copper corrosion inhibition have not been explained in detail by experimental studies. In the present study, the theoretical density functional study (DFT), ab initio MP2, and Monte Carlo simulation approaches explain the problem. The geometrical and quantum chemical parameters of inhibitors were compared under normal and protonated conditions in the gas and aqueous environments. Theoretical studies can accurately determine the molecule’s geometrical parameters and successfully explain the quantum parameters of inhibitors. Molecular dynamics are applied to study the mechanism of interaction between inhibitors and metal surfaces in an explicit water molecule environment. The energy absorption of caffeine and its derivatives on metal surfaces was linear, with quantum parameters calculated from the density functional theory and an ab initio approach. Furthermore, these theoretical study results align with the previously reported experimental studies published by de Souza et al. The inhibition efficiency ranking of studied molecules preventing copper corrosion was caffeine > theobromine > theophylline. This theoretical approach is expected to bridge the gap in designing effective corrosion inhibitors.