From Small‐Area Observations to Insight: Surface‐Feature‐Extrapolation of Anodes for Alkaline Oxygen Evolution Reaction

In this study, we developed a statistical framework, named multistage data quantification (MSDQ), to evaluate representative surface characteristics such as surface roughness, surface area, and homogeneity score of cobalt oxide-based anodes, and contributing to a deeper insight into the quality of the anode surface. Atomic force microscopy (AFM) was employed to capture the surface morphology of two anodes that have a comparable loading of cobalt oxide but exhibit distinct morphological features. Application of MSDQ exposed notable disparities in surface characteristics across these anodes, underlining the critical importance of MSDQ in precise surface characterization. Specifically, surface roughness, surface area and homogeneity score effectively elucidated the disparities in electrocatalytic activity for the oxygen evolution reaction (OER), as quantified through scanning droplet cell (SDC) measurements. By conducting a systematic comparative analysis, the respective contributions of the extrinsic surface characteristics of the anodes to the intrinsic electrocatalytic material property could be differentiated and quantified. Applications of our findings range from benchmarking of anodes to optimization of anode manufacturing processes. Multistage data quantification (MSDQ) is a three-step process that enables full-scale surface extrapolation. MSDQ facilitates optimal region selection and ensures unbiased surface characterization. The extracted extrinsic properties of anode surfaces influence the catalytic activity during the oxygen evolution reaction. Hence, MSDQ provides deeper understanding of the surface morphology, thereby providing insights into processes and their parameters involved during anode fabrication. image