The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Inverse ZrO2/Cu as a highly efficient methanol synthesis catalyst from CO2 hydrogenation
Open accessAbstract
Enhancing the intrinsic activity and space time yield of Cu based heterogeneous methanol synthesis catalysts through CO 2 hydrogenation is one of the major topics in CO 2 conversion into value-added liquid fuels and chemicals. Here we report inverse ZrO 2/Cu catalysts with a tunable Zr/Cu ratio have been prepared via an oxalate co-precipitation method, showing excellent performance for CO 2 hydrogenation to methanol. Under optimal condition, the catalyst composed by 10% of ZrO 2 supported over 90% of Cu exhibits the highest mass-specific methanol formation rate of 524 g MeOH kg cat−1 h−1 at 220 °C, 3.3 times higher than the activity of traditional Cu/ZrO 2 catalysts (159 g MeOH kg cat−1 h−1). In situ XRD-PDF, XAFS and AP-XPS structural studies reveal that the inverse ZrO 2/Cu catalysts are composed of islands of partially reduced 1–2 nm amorphous ZrO 2 supported over metallic Cu particles. The ZrO 2 islands are highly active for the CO 2 activation. Meanwhile, an intermediate of formate adsorbed on the Cu at 1350 cm−1 is discovered by the in situ DRIFTS. This formate intermediate exhibits fast hydrogenation conversion to methoxy. The activation of CO 2 and hydrogenation of all the surface oxygenate intermediates are significantly accelerated over the inverse ZrO 2/Cu configuration, accounting for the excellent methanol formation activity observed.
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
Generalized Gradient Approximation Made Simple
Perdew, J. P., Burke, K., & Ernzerhof, M. (1996) · Physical Review Letters · doi:10.1103/physrevlett.77.3865 · Cited by 215,824
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
Kresse, G., & Furthmüller, J. (1996) · Physical Review B · doi:10.1103/physrevb.54.11169 · Cited by 123,652
Projector augmented-wave method
Blöchl, P. E. (1994) · Physical Review B · doi:10.1103/physrevb.50.17953 · Cited by 92,732
Grimme, S., Antony, J., Ehrlich, S., & Krieg, H. (2010) · The Journal of Chemical Physics · doi:10.1063/1.3382344 · Cited by 59,686
Effect of the damping function in dispersion corrected density functional theory
Grimme, S., Ehrlich, S., & Goerigk, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21759 · Cited by 28,221
Beyond Oil and Gas: The Methanol Economy
Olah, G. A. (2005) · Angewandte Chemie International Edition · doi:10.1002/anie.200462121 · Cited by 2,431
Hansen, J., Sato, M., Ruedy, R., Lo, K., Lea, D. W., & Medina-Elizade, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606291103 · Cited by 2,134
Methanol to Olefins (MTO): From Fundamentals to Commercialization
Tian, P., Wei, Y., Ye, M., & Liu, Z. (2015) · ACS Catalysis · doi:10.1021/acscatal.5b00007 · Cited by 1,723
Álvarez, A., Bansode, A., Urakawa, A., Bavykina, A. V., Wezendonk, T. A., Makkee, M., Gascon, J., & Kapteijn, F. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00816 · Cited by 1,600
Low-temperature hydrogen production from water and methanol using Pt/α-MoC catalysts
Lin, L., Zhou, W., Gao, R., Yao, S., Zhang, X., Xu, W., Zheng, S., Jiang, Z., Yu, Q., Li, Y.-W., et al. (2017) · Nature · doi:10.1038/nature21672 · Cited by 1,564
Self-citation
Cited by
Li, Y., Zhang, Y., Qian, K., & Huang, W. (2022) · ACS Catalysis · doi:10.1021/acscatal.1c04854 · Cited by 538
Metadata
- Authors
- Wu, C., Lin, L., Liu, J., Zhang, J., Zhang, F., Zhou, T., Rui, N., Yao, S., Deng, Y., Yang, F., Xu, W., Luo, J., Zhao, Y., Yan, B., Wen, X.-D., Rodriguez, J. A., & Ma, D.
- Venue
- Nature Communications
- Published
- 2020-11-13
- Volume
- 11
- Issue
- 1
- Pages
- 5767-5767
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3100529310
- Cited by
- 503
- References
- 44
- FWCI
- 9.39
- 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: Inverse ZrO2/Cu as a highly efficient methanol synthesis catalyst from CO2 hydrogenation. https://app.cochat.ai/papers/10.1038/s41467-020-19634-8
- The paper
- Wu, C., Lin, L., Liu, J., Zhang, J., Zhang, F., Zhou, T., Rui, N., Yao, S., Deng, Y., Yang, F., Xu, W., Luo, J., Zhao, Y., Yan, B., Wen, X.-D., Rodriguez, J. A., & Ma, D. (2020). Inverse ZrO2/Cu as a highly efficient methanol synthesis catalyst from CO2 hydrogenation. Nature Communications. https://doi.org/10.1038/s41467-020-19634-8
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.