Screening the Surface Structure-Dependent Action of a Benzotriazole Derivative on Copper Electrochemistry in a Triple-Phase Nanoscale Environment.
Enrico DaviddiViacheslav ShkirskiyPaul M KirkmanMathew P RobinCameron L BentleyPatrick R UnwinPublished in: The journal of physical chemistry. C, Nanomaterials and interfaces (2022)
Copper (Cu) corrosion is a compelling problem in the automotive sector and in oil refinery and transport, where it is mainly caused by the action of acidic aqueous droplets dispersed in an oil phase. Corrosion inhibitors, such as benzotriazole (BTAH) and its derivatives, are widely used to limit such corrosion processes. The efficacy of corrosion inhibitors is expected to be dependent on the surface crystallography of metals exposed to the corrosion environment. Yet, studies of the effect of additives at the local level of the surface crystallographic structure of polycrystalline metals are challenging, particularly lacking for the triple-phase corrosion problem (metal/aqueous/oil). To address this issue, scanning electrochemical cell microscopy (SECCM), is used in an acidic nanodroplet meniscus|oil layer|polycrystalline Cu configuration to explore the grain-dependent influence of an oil soluble BTAH derivative (BTA-R) on Cu electrochemistry within the confines of a local aqueous nanoprobe. Electrochemical maps, collected in the voltammetric mode at an array of >1000 points across the Cu surface, reveal both cathodic (mainly the oxygen reduction reaction) and anodic (Cu electrooxidation) processes, of relevance to corrosion, as a function of the local crystallographic structure, deduced with co-located electron backscatter diffraction (EBSD). BTA-R is active on the whole spectrum of crystallographic orientations analyzed, but there is a complex grain-dependent action, distinct for oxygen reduction and Cu oxidation. The methodology pinpoints the surface structural motifs that facilitate corrosion-related processes and where BTA-R works most efficiently. Combined SECCM-EBSD provides a detailed screen of a spectrum of surface sites, and the results should inform future modeling studies, ultimately contributing to a better inhibitor design.