The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Structure−Activity Relationship of Iron Titanate Catalysts in the Selective Catalytic Reduction of NOx with NH3
Open accessAbstract
A series of iron titanate catalysts, Fe a Ti b O x, with different Fe−Ti molar ratios are synthesized via a facile coprecipitation method and tested for the selective catalytic reduction (SCR) of NO x with NH 3 . The structural properties and redox behavior of the serial catalysts are comprehensively characterized. Comparing with pristine TiO 2 and Fe 2 O 3, the coexistence of iron and titanium species is favorable to form crystallites with specific Fe−O−Ti structure, which is highly active for the NH 3 -SCR reaction. Fe 4 Ti 4 O x catalyst with a Fe−Ti molar ratio of 1:1 shows the highest intrinsic activity, due to its smallest particle size, enhanced oxidative ability of Fe 3+, highest mobility of lattice oxygen, and abundant acid sites. The correlation between catalytic performance and reactant adsorption capability/conformation is also studied, indicating that an appropriate method to improve the low temperature SCR activity of iron titanate catalyst is to enhance the adsorption ability of NO x as monodentate nitrate on catalyst surface.
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
Sing, K. S. W. (1985) · Pure and Applied Chemistry · doi:10.1351/pac198557040603 · Cited by 24,485
Cited by
Han, L., Cai, S., Gao, M., Hasegawa, J.-Y., Wang, P., Zhang, J., Shi, L., & Zhang, D. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00202 · Cited by 1,736
Metadata
- Authors
- Liu, F., & He, H.
- Venue
- The Journal of Physical Chemistry C
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-03-16
- Volume
- 114
- Issue
- 40
- Pages
- 16929-16936
- ISSN
- 1932-7447 (ISSN-L)
- 1932-7455
- OpenAlex
- W2168893264
- Cited by
- 350
- References
- 1
- FWCI
- 5.41
- Type
- journal article
- Language
- en
- Open access
- green
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: Structure−Activity Relationship of Iron Titanate Catalysts in the Selective Catalytic Reduction of NOx with NH3. https://app.cochat.ai/papers/10.1021/jp912163k
- The paper
- Liu, F., & He, H. (2010). Structure−Activity Relationship of Iron Titanate Catalysts in the Selective Catalytic Reduction of NOx with NH3. The Journal of Physical Chemistry C. https://doi.org/10.1021/jp912163k
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.
