Utilizing machine learning to expedite the fabrication and biological application of carbon dots-Reference-Cited by-同舟云学术

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

Published:2023 Issue:23 Volume:4 Page:5974-5997
ISSN:2633-5409
Container-title:Materials Advances
language:en
Short-container-title:Mater. Adv.

Author:

Tang Yaoyao¹²,Xu Quan¹²^ORCID,Zhu Peide²,Zhu Rongye²,Wang Juncheng³

Affiliation:

1. College of Artificial Intelligence, China University of Petroleum-Beijing, Beijing, 102249, China

2. State Key Laboraty of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, 102249, China

3. Department of Stomatology, First Medical Center, Chinese PLA General Hospital, Beijing, 100042, China

Abstract

This review introduces machine learning into imaging, sensing, and cancer therapy for CDs, demonstrating the great potential for ML to accelerate developments in materials science and provide new insight into the biological application field.

Funder

National Natural Science Foundation of China - State Grid Corporation Joint Fund for Smart Grid

Natural Science Foundation of Beijing Municipality

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/MA/D3MA00443K

Reference163 articles.

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