Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Abstract

Abstract Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide‐enriched domains from oxide‐ and metal‐rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary‐ion fragment, NiO 3 H 3 − ( m / z 108.94), emerged as a marker of hydroxide‐rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni‐based HER, this workflow provides a broadly applicable framework to isolate and rank near‐surface patterns that govern catalytic activity, thereby extending ToF‐SIMS from a qualitative probe to a predictive tool for active site identification.