Editors’ Choice—The Effect of Anchor Group and Alkyl Backbone Chain on Performance of Organic Compounds as Corrosion Inhibitors for Aluminum Investigated Using an Integrative Experimental-Modeling Approach

Abstract

An alkaline etched, superhydrophilic aluminum surface was modified using functionalized alkyl compounds selected to study the effect of their properties on adsorption on the metal surface. The thirteen organic compounds differed in alkyl chain length (eight and eighteen carbon atoms) and anchor group (azide, imidazole, thiocyanate, amino, disulfide, thiol, phosphonic, carboxylic, and benzoic). The methodology of the study integrated a complete chain of steps incorporating synthesis, electrochemical and surface analyses, and computational modeling. The corrosion resistant and superhydrophobic properties depend on the anchor group, which governs adhesion to the surface, and backbone, which is responsible for lateral cohesive interactions. The morphology and chemical composition of modified layers were studied using scanning electron microscopy, X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry. Electrochemical and long-term immersion properties were investigated in 0.5 M NaCl. Calculations based on density functional theory were performed as to model the adsorption of selected anchor groups on the hydroxylated oxidized aluminum surface. Integrated results allowed the identification of the anchor groups that are able to form inhibitive adsorbed layers on Al surface regardless the alkyl chain length, and those that are not able to form adsorbed layers at all and are thus not efficient corrosion inhibitors.

Exploring structure-property relationships in magnesium dissolution modulators

“…Hence, they offer a very efficient way to preselect a short list of promising candidates prior to experimental investigation. Additionally, computational techniques can provide deeper insight into the underlying chemical mechanisms and most important chemical functional moieties [41][42][43][44][45][46] . A combination of experimental and computational methods constitutes a sound foundation for a data-driven discovery of modulators.…”

Corrosion inhibition of AA3003 aluminum alloy by self-assembled layers of myristic acid

“…Self-assembled layers (SALs) of amphiphilic molecules are often used to improve the corrosion resistance of metal substrates by working as barriers to prevent the permeation of moisture and electrolytes (Telegdi et al, 2016;Žerjav et al, 2017;Lee and Choi, 2018;Praveena et al, 2020;Milošev et al, 2020). Molecules commonly used to protect aluminum alloy substrates include: fatty acids, phosphonic acids, alkylsilanes and alkylsiloxanes (Milošev et al, 2020;Maege et al, 1998;Wang et al, 2005;Allara and Nuzzo, 1985;Liakos et al, 2004). All of them consist of surfactant-type molecules, comprising a hydrophilic head (polar) group and a hydrophobic tail (long alkyl chain).…”

Rational Design of Effective Mg Degradation Modulators

“…Furthermore, they greatly contribute to a comprehensive understanding of the underlying mechanisms. [24][25][26] There are two major strategies that can be adopted to identify compounds with suitable degradation modulating properties using computational techniques. The first is a data-driven machine learning (ML) approach 22,[27][28][29][30] that is based on quantitative structureactivity relationships to predict the experimental performance of untested compounds.…”