Open Access

Materials Advances, volume 4, issue 23, pages 5974-5997

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

Yaoyao Tang ^{1, 2}

Quan Xu ^{1, 2}

Peide Zhu ²

Rongye Zhu ²

Juncheng Wang ³

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College of Artificial Intelligence, China University of Petroleum-Beijing, Beijing, 102249, China |

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

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

Publication type: Journal Article

Publication date: 2023-11-01

Royal Society of Chemistry (RSC)

Journal: Materials Advances

scimago Q1

SJR: 1.033

CiteScore: 7.6

Impact factor: 5.2

ISSN: 26335409

DOI: 10.1039/d3ma00443k

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Chemistry (miscellaneous)

General Materials Science

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.

Found

	1
Colloids and Surfaces B: Biointerfaces	Colloids and Surfaces B: Biointerfaces, 1, 16.67% Colloids and Surfaces B: Biointerfaces 1 publication, 16.67%
Microchemical Journal	Microchemical Journal, 1, 16.67% Microchemical Journal 1 publication, 16.67%
Small	Small, 1, 16.67% Small 1 publication, 16.67%
Journal of Materials Chemistry C	Journal of Materials Chemistry C, 1, 16.67% Journal of Materials Chemistry C 1 publication, 16.67%
Biosensors and Bioelectronics	Biosensors and Bioelectronics, 1, 16.67% Biosensors and Bioelectronics 1 publication, 16.67%
New Journal of Chemistry	New Journal of Chemistry, 1, 16.67% New Journal of Chemistry 1 publication, 16.67%
	1

	1 2 3
Elsevier	Elsevier, 3, 50% Elsevier 3 publications, 50%
Royal Society of Chemistry (RSC)	Royal Society of Chemistry (RSC), 2, 33.33% Royal Society of Chemistry (RSC) 2 publications, 33.33%
Wiley	Wiley, 1, 16.67% Wiley 1 publication, 16.67%
	1 2 3

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Publisher

Royal Society of Chemistry (RSC)

Journal

Materials Advances

scimago Q1

SJR

1.033

CiteScore

7.6

Impact factor

5.2

ISSN

26335409 (Electronic)

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

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