Issue 23, 2023

Utilizing machine learning to expedite the fabrication and biological application of carbon dots

Abstract

As a novel type of nanomaterial, carbon dots (CDs) are widely used in biology owing to their optical property, biocompatibility, and intrinsic theranostic properties. Taking advantage of these features, the CDs serve as color agents, fluorescence probes, and anti-cancer drugs. Machine learning (ML) has progressed dramatically, especially for widespread use in the biological field. In this review, we introduce the ML workflow and the leading models in the process and then demonstrate the application of CDs in bioimaging, biosensing, and cancer treatment. Next, we generalize the use in the development of CDs’ combination of ML in complementary aspects. Finally, we briefly summarize the challenges and expectations for the future. This review provides new thoughts and guidance for CDs on the application and integration of machine learning.

Graphical abstract: Utilizing machine learning to expedite the fabrication and biological application of carbon dots

Article information

Article type
Review Article
Submitted
21 7月 2023
Accepted
26 10月 2023
First published
01 11月 2023
This article is Open Access
Creative Commons BY-NC license

Mater. Adv., 2023,4, 5974-5997

Utilizing machine learning to expedite the fabrication and biological application of carbon dots

Y. Tang, Q. Xu, P. Zhu, R. Zhu and J. Wang, Mater. Adv., 2023, 4, 5974 DOI: 10.1039/D3MA00443K

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. You can use material from this article in other publications, without requesting further permission from the RSC, provided that the correct acknowledgement is given and it is not used for commercial purposes.

To request permission to reproduce material from this article in a commercial publication, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party commercial publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements