Machine learning guided full-color V<sub>4</sub>C<sub>3</sub> MXene quantum dots for building WLEDs-Reference-Cited by-同舟云学术

Machine learning guided full-color V₄C₃ MXene quantum dots for building WLEDs

Published:2022 Issue:38 Volume:10 Page:14282-14287
ISSN:2050-7526
Container-title:Journal of Materials Chemistry C
language:en
Short-container-title:J. Mater. Chem. C

Author:

Li Shouzhen¹,Zheng Huayu²,Ding Lan¹,Xiao Xie¹,Niu Yingchun¹,Tang Yaoyao¹,Liu Zeyang¹,Zhang Weiye¹,Zhou Yang¹^ORCID,Xu Quan¹^ORCID

Affiliation:

1. State Key Laboratory of Heavy Oil Processing, College of New Energy and Materials Science, China University of Petroleum-Beijing, Beijing, 102249, China

2. State Key Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, Nanjing, China

Abstract

In this paper, we report for the first time the preparation of full-color MXene quantum dots (MQDs) using V4C3. Importantly, the ML-driven XGB model guided our success in obtaining the optimal WLED with CIE color coordinates of (0.333, 0.397).

Funder

Science Foundation of China University of Petroleum, Beijing

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/TC/D2TC02969C

Reference35 articles.

1. Machine learning-guided synthesis of advanced inorganic materials

2. Machine-learning-guided directed evolution for protein engineering