Genesis of Nanogalvanic Corrosion Revealed in Pearlitic Steel

Deciphering the Interplay between Local and Global Dynamics of Anodic Metal Oxidation

The stark difference between global and local metal oxidation dynamics underscores the need for methodologies capable of performing precise sub-μm-scale and wide-field measurements. In this study, we present reflective microscopy as a tool developed to address this challenge, illustrated by the example of chronoamperometric Fe oxidation in a NaCl solution. Analysis at a local scale of 10 s of μm has revealed three distinct periods of Fe oxidation: the initial covering of the metal interface with a surface film, followed by the electrochemical conversion of the formed surface film, and finally, the in-depth oxidation of Fe. In addition, thermodynamic calculations and the quantitative analysis of changes in optical signal (light intensity), correlated with variations in refractive indexes, suggest the initial formation of maghemite, followed by its subsequent conversion to magnetite. The reactivity maps for all three periods are heterogeneous, which can be attributed to the preferential oxidation of certain crystallographic grains. Notably, at the global scale of 100 s of μm, reactivity initiates at the electrode border and progresses toward its center, demonstrating a unique pattern that is independent of the local metal structure. This finding underscores the significance of simultaneously employing sub-μm-precise, quantitative, and wide-field measurements for a comprehensive description of metal oxidation processes.

Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy

Operando wide-field optical microscopy imaging yields a wealth of information about the reactivity of metal interfaces, yet the data are often unstructured and challenging to process. In this study, the power of unsupervised machine learning (ML) algorithms is harnessed to analyze chemical reactivity images obtained dynamically by reflectivity microscopy in combination with ex situ scanning electron microscopy to identify and cluster the chemical reactivity of particles in Al alloy. The ML analysis uncovers three distinct clusters of reactivity from unlabeled datasets. A detailed examination of representative reactivity patterns confirms the chemical communication of generated OH- fluxes within particles, as supported by statistical analysis of size distribution and finite element modelling (FEM). The ML procedures also reveal statistically significant patterns of reactivity under dynamic conditions, such as pH acidification. The results align well with a numerical model of chemical communication, underscoring the synergy between data-driven ML and physics-driven FEM approaches.

Imaging and Quantifying the Chemical Communication between Single Particles in Metal Alloys

The communication within particle agglomerates in industrial alloys can have a significant impact on the macroscopic reactivity, putting a high demand on the adaptation of wide-field methodologies to clarify this phenomenon. In this work, we report the application of correlated optical microscopies probing operando both local pH and local surface chemical transformation correlated with identical location scanning electron microscopy to quantify in situ the structure reactivity of particle agglomerates of foreign elements in the Al alloy. The optical operando analyses allow us (i) to reveal and quantify the local production of OH^- from proton and oxygen reduction at individual Si- or Fe-rich microparticles and (ii) to quantify (and model) the chemical communication between these active sites, within a few micrometer range, on the local chemical transformation of the material. Wide-field image analysis highlights the statistical importance of chemical communication that may introduce a new conceptual framework for the understanding of the mechanisms in related fields of charge transfer, electrocatalysis, and corrosion.