Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 308

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Selective Etching Quaternary MAX Phase toward Single Atom Copper Immobilized MXene (Ti3C2Clx) for Efficient CO2 Electroreduction to Methanol

Zhao, Qi, Zhang, Chao, Hu, Riming, Du, Zhiguo, Gu, Jianan, Cui, Yanglansen, Chen, Xiao, Xu, Wenjie, Cheng, Zongju, Li, Songmei, Li, Bin, Liu, Yuefeng, Chen, Weihua, Liu, Chuntai, Shang, Jiaxiang, Song, Li, Yang, Shubin·2021·ACS Nano

Abstract

Single atom catalysts possess attractive electrocatalytic activities for various chemical reactions owing to their favorable geometric and electronic structures compared to the bulk counterparts. Herein, we demonstrate an efficient approach to producing single atom copper immobilized MXene for electrocatalytic CO 2 reduction to methanol via selective etching of hybrid A layers (Al and Cu) in quaternary MAX phases (Ti 3 (Al 1– x Cu x )C 2 ) due to the different saturated vapor pressures of Al- and Cu-containing products. After selective etching of Al in the hybrid A layers, Cu atoms are well-preserved and simultaneously immobilized onto the resultant MXene with dominant surface functional group (Cl x ) on the outmost Ti layers (denoted as Ti 3 C 2 Cl x ) via Cu–O bonds. Consequently, the as-prepared single atom Cu catalyst exhibits a high Faradaic efficiency value of 59.1% to produce CH 3 OH and shows good electrocatalytic stability. On the basis of synchrotron-based X-ray absorption spectroscopy analysis and density functional theory calculations, the single atom Cu with unsaturated electronic structure (Cu δ+, 0 < δ < 2) delivers a low energy barrier for the rate-determining step (conversion of HCOOH* to absorbed CHO* intermediate), which is responsible for the efficient electrocatalytic CO 2 reduction to CH 3 OH.

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/acsnano.0c09755

Cites

53 of 53 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 308

Metadata

Authors
Zhao, Q., Zhang, C., Hu, R., Du, Z., Gu, J., Cui, Y., Chen, X., Xu, W., Cheng, Z., Li, S., Li, B., Liu, Y., Chen, W., Liu, C., Shang, J., Song, L., & Yang, S.
Venue
ACS Nano
Published
2021-02-22
Volume
15
Issue
3
Pages
4927-4936
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W3131407445
Cited by
308
References
53
FWCI
8.56
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.