Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,452

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO 2

Graciani, Jesús, Mudiyanselage, Kumudu, Xu, Fang, Baber, Ashleigh E., Evans, Jaime, Senanayake, Sanjaya D., Stacchiola, Darío J., Liu, Ping, Hrbek, Jan, Sanz, Javier Fernández, Rodriguez, José A.·2014·Science

Abstract

Converting CO 2 into methanol by catalysis: By hydrogenating CO 2 , scientists can transform a greenhouse gas into methanol, a desirable fuel. Graciani et al. cast copper in the role of the highly active catalyst for this reaction by putting copper particles on cerium oxide. The interface between the cerium oxide and the copper enables the reverse water-gas shift reaction that converts CO 2 into CO, which reacts more readily with hydrogen to make methanol. This result takes a step forward in innovating catalysts for this environmentally friendly process. Science , this issue p. 546

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 · 10.1126/science.1253057

Cites

1 of 1 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 1,452

Metadata

Authors
Graciani, J., Mudiyanselage, K., Xu, F., Baber, A. E., Evans, J., Senanayake, S. D., Stacchiola, D. J., Liu, P., Hrbek, J., Sanz, J. F., & Rodriguez, J. A.
Venue
Science
Published
2014-08
Volume
345
Issue
6196
Pages
546-550
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1991692033
Cited by
1,452
References
1
FWCI
34.05
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO 2. https://app.cochat.ai/papers/10.1126/science.1253057
The paper
Graciani, J., Mudiyanselage, K., Xu, F., Baber, A. E., Evans, J., Senanayake, S. D., Stacchiola, D. J., Liu, P., Hrbek, J., Sanz, J. F., & Rodriguez, J. A. (2014). Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO 2. Science. https://doi.org/10.1126/science.1253057

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.