Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 300

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Monitoring the Chemical State of Catalysts for CO2 Electroreduction: An In Operando Study

Dutta, Abhijit, Kuzume, Akiyoshi, Rahaman, Motiar, Vesztergom, Soma, Broekmann, Peter·2015·ACS Catalysis

Abstract

A major concern of electrocatalysis research is to assess the structural and chemical changes that a catalyst may itself undergo in the course of the catalyzed process. These changes can influence not only the activity of the studied catalyst but also its selectivity toward the formation of a certain product. An illustrative example is the electroreduction of carbon dioxide on tin oxide nanoparticles, where under the operating conditions of the electrolysis (that is, at cathodic potentials), the catalyst undergoes structural changes which, in an extreme case, involve its reduction to metallic tin. This results in a decreased Faradaic efficiency (FE) for the production of formate (HCOO – ) that is otherwise the main product of CO 2 reduction on SnO x surfaces. In this study, we utilized potential- and time-dependent in operando Raman spectroscopy in order to monitor the oxidation state changes of SnO 2 that accompany CO 2 reduction. Investigations were carried out at different alkaline pH levels, and a strong correlation between the oxidation state of the surface and the FE of HCOO – formation was found. At moderately cathodic potentials, SnO 2 exhibits a high FE for the production of formate, while at very negative potentials the oxide is reduced to metallic Sn, and the efficiency of formate production is significantly decreased. Interestingly, the highest FE of formate production is measured at potentials where SnO 2 is thermodynamically unstable; however, its reduction is kinetically hindered.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acscatal.5b02322

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 300

Metadata

Authors
Dutta, A., Kuzume, A., Rahaman, M., Vesztergom, S., & Broekmann, P.
Venue
ACS Catalysis
Published
2015-11-24
Volume
5
Issue
12
Pages
7498-7502
ISSN
2155-5435 (ISSN-L)
OpenAlex
W2343511514
Cited by
300
References
2
FWCI
5.18
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.