Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 484

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

Selective conversion of CO2 and H2 into aromatics

Open access
Ni, Youming, Chen, Zhiyang, Fu, Yi, Liu, Yong, Zhu, Wenliang, Liu, Zhongmin·2018·Nature Communications

Abstract

Transformation of greenhouse gas CO 2 and renewable H 2 into fuels and commodity chemicals is recognized as a promising route to store fluctuating renewable energy. Although several C 1 chemicals, olefins, and gasoline have been successfully synthesized by CO 2 hydrogenation, selective conversion of CO 2 and H 2 into aromatics is still challenging due to the high unsaturation degree and complex structures of aromatics. Here we report a composite catalyst of ZnAlOx and H-ZSM-5 which yields high aromatics selectivity (73.9%) with extremely low CH 4 selectivity (0.4%) among the carbon products without CO. Methanol and dimethyl ether, which are synthesized by hydrogenation of formate species formed on ZnAlOx surface, are transmitted to H-ZSM-5 and subsequently converted into olefins and finally aromatics. Furthermore, 58.1% p-xylene in xylenes is achieved over the composite catalyst containing Si-H-ZSM-5. ZnAlOx&H-ZSM-5 suggests a promising application in manufacturing aromatics from CO 2 and H 2.

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 · 10.1038/s41467-018-05880-4

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

Show all 1 references

Cited by

See all 484

Metadata

Authors
Ni, Y., Chen, Z., Fu, Y., Liu, Y., Zhu, W., & Liu, Z.
Venue
Nature Communications
Published
2018-08-27
Volume
9
Issue
1
Pages
3457-3457
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2888756095
Cited by
484
References
1
FWCI
8.47
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: Selective conversion of CO2 and H2 into aromatics. https://app.cochat.ai/papers/10.1038/s41467-018-05880-4
The paper
Ni, Y., Chen, Z., Fu, Y., Liu, Y., Zhu, W., & Liu, Z. (2018). Selective conversion of CO2 and H2 into aromatics. Nature Communications. https://doi.org/10.1038/s41467-018-05880-4

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.