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

Journal Article · · Angewandte Chemie (International Edition)
 [1];  [1];  [2];  [3];  [4];  [5]
  1. Univ. of Maribor (Slovenia)
  2. Univ. of Maribor (Slovenia); National Institute of Chemistry (NIC), Ljubljana (Slovenia); Argonne National Laboratory (ANL), Argonne, IL (United States)
  3. National Institute of Chemistry (NIC), Ljubljana (Slovenia); Association for Technical Culture of Slovenia (ZOTKS), Ljubljana (Slovenia)
  4. Univ. of Maribor (Slovenia); National Institute of Chemistry (NIC), Ljubljana (Slovenia)
  5. National Institute of Chemistry (NIC), Ljubljana (Slovenia)
+ Show Author Affiliations
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, NiO3H3− (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.
Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC02-06CH11357
OSTI ID:
3018529
Journal Information:
Angewandte Chemie (International Edition), Journal Name: Angewandte Chemie (International Edition) Journal Issue: 8 Vol. 65; ISSN 1521-3773; ISSN 1433-7851
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

HER active sites
Multivariate statistical analysis
Nickel catalysts
ToF-SIMS