Evidence map›Paper›PMID 41972343›Full record

ArticleACS applied materials & interfaces2026

Multiscale Analysis of Electrochemical Dealloying of Bimetallic Nanoparticles to Tune Catalytic Activity.

Johanna Angona, Dimitrios Valavanis, Daniel Houghton, Fengli Yang, Thais Schroeder Rossi, Jan Clausmeyer, Beatriz Roldan Cuenya, Julie V Macpherson, Patrick R Unwin, Kristina Tschulik

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS applied materials & interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

10 authors.

Johanna AngonaAnalytical Chemistry, Ruhr University Bochum, Bochum 44801, Germany.ORCID 0000-0002-2356-4736
Dimitrios ValavanisDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0002-8777-664X
Daniel HoughtonDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0003-1750-462X
Fengli YangDepartment of Interface Science, Fritz-Haber Institute of the Max-Planck Society, Berlin 14195, Germany.
Thais Schroeder RossiAnalytical Chemistry, Ruhr University Bochum, Bochum 44801, Germany.ORCID 0000-0003-1243-2866
Jan ClausmeyerAnalytical Chemistry, Ruhr University Bochum, Bochum 44801, Germany.ORCID 0000-0003-0685-4528
Beatriz Roldan CuenyaDepartment of Interface Science, Fritz-Haber Institute of the Max-Planck Society, Berlin 14195, Germany.ORCID 0000-0002-8025-307X
Julie V MacphersonDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0002-4249-8383
Patrick R UnwinDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0003-3106-2178
Kristina TschulikAnalytical Chemistry, Ruhr University Bochum, Bochum 44801, Germany.ORCID 0000-0001-7637-4082

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical dealloying is a promising technique to tune the activity and material utilization of electrocatalysts. Studying this process in bimetallic nanoparticles remains challenging since their synthesis yields ensembles with varied properties. To understand the dealloying behavior of individual nanoparticles, we present a combined characterization method that provides statistical distributions in composition, morphology, and catalytic activity. Ag

Indexed as

bimetallic nanoparticleselectrochemical dealloyinghydrogen evolution reactionidentical-location analysismultiscale electrochemical analysisreverse micellesscanning electrochemical cell microscopyscanning transmission electron microscopy

Identifiers

PMID41972343
PMCPMC13107377

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Registered trials

None linked

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.