Machine Learning-Assisted Carbon Dot Synthesis: Prediction of Emission Color and Wavelength-Reference-Cited by-同舟云学术

Machine Learning-Assisted Carbon Dot Synthesis: Prediction of Emission Color and Wavelength

Published:2022-11-17 Issue:23 Volume:62 Page:5918-5928
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Senanayake Ravithree D.¹^ORCID,Yao Xiaoxiao²^ORCID,Froehlich Clarice E.²^ORCID,Cahill Meghan S.²^ORCID,Sheldon Trever R.²^ORCID,McIntire Mary²^ORCID,Haynes Christy L.²^ORCID,Hernandez Rigoberto¹³^ORCID

Affiliation:

1. Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States

2. Department of Chemistry, University of Minnesota−Twin Cities, 207 Pleasant Street SE, Minneapolis, Minnesota 55455, United States

3. Departments of Chemical and Biomolecular Engineering and Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States

Funder

Division of Chemistry

Center for Sustainable Nanotechnology

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c01007

Reference50 articles.

1. Synthesis, applications and potential photoluminescence mechanism of spectrally tunable carbon dots

2. Machine Learning-Assisted Array-Based Biomolecular Sensing Using Surface-Functionalized Carbon Dots