Investigation of indole-3-carboxylic acid as steel inhibitor in 0.1M H2SO4 solution

Effect of Indole-2-carboxylic Acid on the Self-Corrosion and Discharge Activity of Aluminum Alloy Anode in Alkaline Al-Air Battery

Al-air battery has been regarded as a promising new energy source. However, the self-corrosion of aluminum anode leads to a loss of battery capacity and a decrease in battery longevity, limiting its commercial applications. Herein, indole-2-carboxylic acid (ICA) has been added to 4 M NaOH as a corrosion inhibitor. Its impact on the self-corrosion of aluminum alloy and the enhancement of the functionality of Al-air batteries at various concentrations have been investigated. X-ray photoelectron spectroscopy (XPS), attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), and scanning electron microscopy (SEM) techniques have been used to examine the compositional and morphological alterations of aluminum alloy surfaces. Electrochemical and hydrogen evolution tests showed that indole-2-carboxylic acid is an efficient corrosion inhibitor in alkaline solutions, and its impact grows with concentration. Our findings demonstrated that when the inhibitor concentration is 0.07 M, the inhibition efficiency is 54.0%, the anode utilization rises from 40.2% to 79.9%, the capacity density increases from 1197.6 to 2380.9 mAh g^-1, and the energy density increases from 1469.9 to 2951.8 Wh kg^-1. In addition, theoretical calculations have been performed to support the experimental results.

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.

N-(3-(Dimethyl benzyl ammonio)propyl)alkanamide chloride derivatives as corrosion inhibitors for mild steel in 1 M HCl solution: experimental and theoretical investigation

The effects of the synthesized cationic surfactants corrosion inhibitiors DMBL, DMBM and DMBP on the corrosion of mild carbon steel in acidic medium (1.0 M HCl) were investigated using weight loss and electrochemical measurements.