Evidence map›Paper›PMID 40635878›Full record

ArticleACS electrochemistry2025

Effect of Trace Amounts of Chloride on Roughening of Au(111) Single-Crystal Electrode Surface in Sulfuric Acid Solution during Oxidation-Reduction Cycles.

Saeid Behjati, Marc T M Koper

Abstract read
In one paragraph

Article in ACS electrochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Visualizing Metal Nanoparticle Electrochemical Dissolution Atom by Atom.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  2. Dynamics of Adatom and Vacancy Islands on Au(111) in Alkaline and Acidic Media.The journal of physical chemistry. C, Nanomaterials and interfaces · 2025
    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

2 authors.

Saeid BehjatiLeiden Institute of Chemistry, Leiden University, PO Box 9502, 2300 RA Leiden, The Netherlands.ORCID https://orcid.org/0000-0003-2216-7509
Marc T M KoperLeiden Institute of Chemistry, Leiden University, PO Box 9502, 2300 RA Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-6777-4594

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the impact of varying trace-level chloride ion concentrations on the roughening of a Au(111) electrode during oxidation-reduction cycles (ORCs) in 0.1 M sulfuric acid by in situ scanning tunneling microscopy (STM). At the higher chloride concentration (50 μM), rapid dissolution of Au atoms and step line recession are observed in the recorded in situ STM images. The high surface mobility of Au atoms resulted in a lack of detectable vacancy islands in the images with minimal changes in cyclic voltammograms (CVs) and the complete absence of nano-island formation, which is observed in pure sulfuric acid. At moderate concentration (10 μM), the dissolution rate decreased substantially, so the initial step lines are still distinguishable after the 200 ORCs. The lower surface mobility leads to the formation of vacancy islands in the terraces, and these newly formed step sites give rise to additional peaks in the CVs. At the lowest concentration (1 μM), nano-island formation is observed. However, inhomogeneous chloride adsorption (showing as darker areas in the EC-STM images) on the sample at high enough anodic potential (0.9 V) led to previously unreported behavior, showing very inhomogeneous roughening, with parts on the surface showing reduced Au atom mobility and minimal changes even after 200 ORCs.

Indexed as

Au(111)chlorideEC-STMhydrochloric acidin situ scanning probe microscopyoxidation−reduction cyclesrougheningsulfuric acid

Identifiers

PMID40635878
PMCPMC12235628

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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.