The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Directly converting carbon dioxide to linear α-olefins on bio-promoted catalysts
Open accessAbstract
Although considerable efforts have been made in converting carbon dioxide to hydrocarbons via hydrogenation processes, precise control of C–C coupling towards heavy olefins remains a challenge. Here we report a carbon dioxide hydrogenation to olefin process that achieves 72% selectivity for alkenes and 50.3% selectivity for C 4–18 alkenes, of which formation of linear α-olefins accounts for 80%. The process is catalyzed by carbon-supported iron, commonly used in C–C coupling reactions, with multiple alkali promoters extracted from corncob. The design is based on the synergistic catalysis of mineral elements in biomass enzyme on which carbon dioxide can be directly converted into carbohydrate. The mineral elements from corncob may promote the surface enrichment of potassium, suppressing the secondary hydrogenation of alkenes on active sites. Furthermore, carburization of iron species is enhanced to form more Fe 5 C 2 species, promoting both the reverse water–gas shift reaction and subsequent C–C coupling.
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.
Integrity signals
Registry
Cites
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.
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
Recent advances in catalytic hydrogenation of carbon dioxide
Wang, W., Wang, S., Ma, X., & Gong, J. (2011) · Chemical Society Reviews · doi:10.1039/c1cs15008a · Cited by 3,316
Cited by
Significant Advances in C1 Catalysis: Highly Efficient Catalysts and Catalytic Reactions
Bao, J., Yang, G., Yoneyama, Y., & Tsubaki, N. (2019) · ACS Catalysis · doi:10.1021/acscatal.8b03924 · Cited by 367
Metadata
- Authors
- Guo, L., Sun, J., Ji, X., Wei, J., Wen, Z., Yao, R., Xu, H., & Ge, Q.
- Venue
- Communications Chemistry
- Published
- 2018-03-22
- Volume
- 1
- Issue
- 1
- ISSN
- 2399-3669 (ISSN-L)
- OpenAlex
- W2803712767
- Cited by
- 174
- References
- 1
- FWCI
- 4.50
- Type
- journal article
- Language
- en
- Open access
- gold
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: Directly converting carbon dioxide to linear α-olefins on bio-promoted catalysts. https://app.cochat.ai/papers/10.1038/s42004-018-0012-4
- The paper
- Guo, L., Sun, J., Ji, X., Wei, J., Wen, Z., Yao, R., Xu, H., & Ge, Q. (2018). Directly converting carbon dioxide to linear α-olefins on bio-promoted catalysts. Communications Chemistry. https://doi.org/10.1038/s42004-018-0012-4
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.