Evidence map›Paper›PMID 41540610›Full record

ArticleAngewandte Chemie (International ed. in English)2026

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

Matjaž Finšgar, Katja Andrina Varda, Dzevad K Kozlica, Matej Huš, Milena Martins, Dušan Strmčnik

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Matjaž FinšgarFaculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, 2000, Slovenia.
Katja Andrina VardaFaculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, 2000, Slovenia.
Dzevad K KozlicaFaculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, 2000, Slovenia.
Matej HušLaboratory for Electrocatalysis, Department of Materials Chemistry, National Institute of Chemistry, Ljubljana, 1000, Slovenia.
Milena MartinsFaculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, 2000, Slovenia.
Dušan StrmčnikLaboratory for Electrocatalysis, Department of Materials Chemistry, National Institute of Chemistry, Ljubljana, 1000, Slovenia.

Funding

The Slovenian Research and Innovation Agency I0-0039The Slovenian Research and Innovation Agency J1-70039The Slovenian Research and Innovation Agency J2-50058The Slovenian Research and Innovation Agency J7-4636The Slovenian Research and Innovation Agency J7-4683The Slovenian Research and Innovation Agency J7-50227The Slovenian Research and Innovation Agency P2-0118The Slovenian Research and Innovation Agency P2-0152
6 · The paper itself

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

Indexed as

HER active sitesMultivariate statistical analysisNickel catalystsToF‐SIMS

Identifiers

PMID41540610
PMCPMC12910139

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.