The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Magnetic-induced graphene quantum dots for imaging-guided photothermal therapy in the second near-infrared window
Abstract
Graphene quantum dots (GQDs) are considered emerging nanomaterials for photothermal therapy (PTT) of cancer due to their good biocompatibility and rapid excretion. However, the optical absorbance of GQDs in shorter wavelengths (<1000 nm) limits their overall therapeutic efficacies as photothermal agent in the second near infrared window (1000-1700 nm, NIR-II). Herein, we report a type of GQDs with strong absorption (1070 nm) in NIR-II region that was synthesized via a one-step solvothermal treatment using phenol as single precursor by tuning the decomposition of hydrogen peroxide under a high magnetic field with an intensity of 9T. The obtained 9T-GQDs demonstrate uniform size distribution (3.6 nm), and tunable fluorescence (quantum yield, 16.67%) and high photothermal conversion efficacy (33.45%). In vitro and in vivo results indicate that 9T-GQDs could efficiently ablate tumor cells and inhibit the tumor growth under NIR-II irradiation. Moreover, the 9T-GQDs exhibited enhanced NIR imaging of tumor in living mice, suggesting the great probability of using 9T-GQDs for in vivo NIR imaging-guided PTT in the NIR-II window.
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
Glowing Graphene Quantum Dots and Carbon Dots: Properties, Syntheses, and Biological Applications
Zheng, X. T., Ananthanarayanan, A., Luo, K. Q., & Chen, P. (2015) · Small · doi:10.1002/smll.201402648 · Cited by 2,190
Optical nano-agents in the second near-infrared window for biomedical applications
Cai, Y., Wei, Z., Song, C., Tang, C., Han, W., & Dong, X. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00494c · Cited by 603
Li, J., Jiang, R., Wang, Q., Li, X., Hu, X., Yuan, Y., Lu, X., Wang, W., Huang, W., & Fan, Q. (2019) · Biomaterials · doi:10.1016/j.biomaterials.2019.119304 · Cited by 163
Cited by
Second near-infrared photothermal materials for combinational nanotheranostics
Xu, C., & Pu, K. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00664e · Cited by 941
Inorganic nanomaterials with rapid clearance for biomedical applications
Wang, X., Zhong, X., Li, J., Liu, Z., & Cheng, L. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00461h · Cited by 509
Smart Nanomaterials in Cancer Theranostics: Challenges and Opportunities
Kashyap, B. K., Singh, V. V., Solanki, M. K., Kumar, A., Ruokolainen, J., & Kesari, K. K. (2023) · ACS Omega · doi:10.1021/acsomega.2c07840 · Cited by 348
Li, Y., Zhang, J., Liu, S., Zhang, C., Chuah, C., Tang, Y., Kwok, R. T. K., Lam, J. W. Y., Ou, H., Ding, D., et al. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202102213 · Cited by 88
Activatable Molecular Probes With Clinical Promise for NIR‐II Fluorescent Imaging
Chen, Z., Zhou, Y., Li, L., Ma, W., Li, Y., & Yang, Z. (2025) · Small · doi:10.1002/smll.202411787 · Cited by 26
Metadata
- Authors
- Liu, H., Li, C., Qian, Y., Hu, L., Fang, J., Tong, W., Nie, R., Chen, Q., & Wang, H.
- Venue
- Biomaterials
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 232
- Pages
- 119700
- ISSN
- 0142-9612 (ISSN-L)
- OpenAlex
- W2996464793
- Cited by
- 195
- References
- 3
- FWCI
- 8.38
- 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: Magnetic-induced graphene quantum dots for imaging-guided photothermal therapy in the second near-infrared window. https://app.cochat.ai/papers/10.1016/j.biomaterials.2019.119700
- The paper
- Liu, H., Li, C., Qian, Y., Hu, L., Fang, J., Tong, W., Nie, R., Chen, Q., & Wang, H. (2020). Magnetic-induced graphene quantum dots for imaging-guided photothermal therapy in the second near-infrared window. Biomaterials. https://doi.org/10.1016/j.biomaterials.2019.119700
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.
