The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Graphitic Carbon Nitride Materials: Sensing, Imaging and Therapy
Abstract
Graphitic carbon nitrides (g‐C 3 N 4) are a class of 2D polymeric materials mainly composed of carbon and nitrogen atoms. g‐C 3 N 4 are attracting dramatically increasing interest in the areas of sensing, imaging, and therapy, due to their unique optical and electronic properties. Here, the luminescent properties (mainly includes photoluminescence and electrochemiluminescence), and catalytic and photoelectronic properties related to sensing and therapy applications of g‐C 3 N 4 materials are reviewed. Furthermore, the fabrication and advantages of sensing, imaging and therapy systems based on g‐C 3 N 4 materials are summarized. Finally, the future perspectives for developing the sensing, imaging and therapy applications of the g‐C 3 N 4 materials are discussed.
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
Barman, S., & Sadhukhan, M. (2012) · Journal of Materials Chemistry · doi:10.1039/c2jm35501a · Cited by 462
Cited by
Yang, B., Chen, Y., & Shi, J. (2019) · Advanced Materials · doi:10.1002/adma.201901778 · Cited by 601
Self-citationAkhundi, A., Habibi-Yangjeh, A., Abitorabi, M., & Rahim Pouran, S. (2019) · Catalysis Reviews · doi:10.1080/01614940.2019.1654224 · Cited by 526
Vázquez-González, M., Liao, W.-C., Cazelles, R., Wang, S., Yu, X., Gutkin, V., & Willner, I. (2017) · ACS Nano · doi:10.1021/acsnano.7b00352 · Cited by 323
Two-dimensional nanomaterials: fascinating materials in biomedical field
Hu, T., Mei, X., Wang, Y., Weng, X., Liang, R., & Wei, M. (2019) · Science Bulletin · doi:10.1016/j.scib.2019.09.021 · Cited by 309
Huang, H., Feng, W., & Chen, Y. (2021) · Chemical Society Reviews · doi:10.1039/d0cs01138j · Cited by 285
Self-citation
Metadata
- Authors
- Dong, Y., Wang, Q., Wu, H., Chen, Y., Lu, C., Chi, Y., & Yang, H.
- Venue
- Small
- Publisher
- Wiley
- Published
- 2016-09-09
- Volume
- 12
- Issue
- 39
- Pages
- 5376-5393
- ISSN
- 1613-6810 (ISSN-L)
- 1613-6829
- OpenAlex
- W2514558928
- Cited by
- 243
- References
- 1
- FWCI
- 11.21
- 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: Graphitic Carbon Nitride Materials: Sensing, Imaging and Therapy. https://app.cochat.ai/papers/10.1002/smll.201602056
- The paper
- Dong, Y., Wang, Q., Wu, H., Chen, Y., Lu, C., Chi, Y., & Yang, H. (2016). Graphitic Carbon Nitride Materials: Sensing, Imaging and Therapy. Small. https://doi.org/10.1002/smll.201602056
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.