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Cited by 299

The DOI matches its Crossref record; 195 of the 195 references it cites were found in a registry or an index.

Photonic Carbon Dots as an Emerging Nanoagent for Biomedical and Healthcare Applications

Chung, You Jung, Kim, Jinhyun, Park, Chan Beum·2020·ACS Nano

Abstract

As a class of carbon-based nanomaterials, carbon dots (CDs) have attracted enormous attention because of their tunable optical and physicochemical properties, such as absorptivity and photoluminescence from ultraviolet to near-infrared, high photostability, biocompatibility, and aqueous dispersity. These characteristics make CDs a promising alternative photonic nanoagent to conventional fluorophores in disease diagnosis, treatment, and healthcare managements. This review describes the fundamental photophysical properties of CDs and highlights their recent applications to bioimaging, photomedicine ( e . g ., photodynamic/photothermal therapies), biosensors, and healthcare devices. We discuss current challenges and future prospects of photonic CDs to give an insight into developing vibrant fields of CD-based biomedicine and healthcare.

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Crossref · 10.1021/acsnano.0c02114

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Metadata

Authors
Chung, Y. J., Kim, J., & Park, C. B.
Venue
ACS Nano
Published
2020-05-22
Volume
14
Issue
6
Pages
6470-6497
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W3027385773
Cited by
299
References
195
FWCI
16.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Photonic Carbon Dots as an Emerging Nanoagent for Biomedical and Healthcare Applications. https://app.cochat.ai/papers/10.1021/acsnano.0c02114
The paper
Chung, Y. J., Kim, J., & Park, C. B. (2020). Photonic Carbon Dots as an Emerging Nanoagent for Biomedical and Healthcare Applications. ACS Nano. https://doi.org/10.1021/acsnano.0c02114

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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.