Evaluation of the Activity of Ni-Based Composite Coatings for Water-Splitting in Alkaline Media by Scanning Electrochemical Cell Microscopy and Correlative Microscopy

Alkaline water electrolysis is considered a promising clean process for energy storage in the form of hydrogen. However, non-noble metal-based electrodes still lack the efficiency and durability required for large-scale H 2 production. Composite materials have gained increasing attention due to their synergistic effects, which enhance water-splitting catalysis while remaining cost-effective. Scanning Electrochemical Cell Microscopy (SECCM) is an efficient tool for screening the water-splitting activity of these electrode candidates. Local heterogeneities of a tested material can be exploited to predict optimal electrode properties. This technique enables the local mapping of electrochemical activity of the material across different surface regions of interest (RoIs). The cartography of electrochemical activity can further be correlated with different surface properties, such as composition or morphology. For this, complementary tools such as Energy Dispersive X-Ray Spectroscopy (EDX), Scanning Electron Microscopy (SEM), or XPS (X-Ray Photoelectron Spectroscopy) allow for the identical location study necessary to correlate differences in electrochemical behaviour with surface features. However, SECCM has rarely been applied to alkaline water electrolysis due to the instability of the electrolyte droplets deposited by the scanning probe. The high wetting properties of alkaline solutions lead to unpredictable droplet spreading, causing variations in surface coverage across different probed areas. Consequently, a direct data comparison across measurement points becomes unreliable. In this work, we address these challenges associated with the use of SECCM under alkaline conditions, with the objective of designing better catalysts for hydrogen generation. We incorporate polyvinylpyrrolidone (PVP) as an additive – a strategy derived from the literature [1] – to improve the reliability of SECCM measurements in alkaline media. In our approach, we electrodeposit a coating with embedded particles on a nickel matrix. A polished cross-section of this coated plate is used as a model surface to evaluate the intrinsic electrochemical activity of the material. Since it is of great importance to distinguish whether the local activity changes stem from the electrochemical surface area (ECSA) or the intrinsic catalytic performance of the material, the electrochemical data are normalized to account for electrolyte droplet size discrepancies. Therefore, in a single experiment, we are able to compare the activity of the coating with respect to a reference material (nickel), as well as the activity variations within the coating. Given that SECCM is a high-throughput technique, a large amount of data is generated from a single experiment. Therefore, automated data processing is strongly desired. In line with this objective, we apply (un)supervised machine learning in an attempt to extract meaningful trends from the collection of data. Altogether, this work establishes SECCM as a viable tool for catalyst optimization in alkaline media for water-splitting applications, showing its potential for accelerating the development of efficient electrodes. [1] Arruda De Oliveira, G., Kim, M., Santos, C. S., Limani, N., Chung, T. D., Tetteh, E. B., & Schuhmann, W. (2024). Controlling surface wetting in high-alkaline electrolytes for single facet Pt oxygen evolution electrocatalytic activity mapping by scanning electrochemical cell microscopy. Chemical Science , 15 (39), 1633116337. Figure 1