基于碳点的白光发光二极管，其相关色温由机器学习引导可调。

Carbon-Dot-Based White-Light-Emitting Diodes with Adjustable Correlated Color Temperature Guided by Machine Learning.

作者信息

Wang Xiao, Wang Bo, Wang Hongshuai, Zhang Tianyang, Qi Huihui, Wu Zhenyu, Ma Yurong, Huang Hui, Shao Mingwang, Liu Yang, Li Youyong, Kang Zhenhui

机构信息

Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-based Functional Materials and Devices, Soochow University, Suzhou, 215123, China.

Macao Institute of Materials Science and Engineering, Macau University of Science and Technology, Taipa, 999078, Macau SAR, China.

出版信息

Angew Chem Int Ed Engl. 2021 May 25;60(22):12585-12590. doi: 10.1002/anie.202103086. Epub 2021 Apr 20.

DOI:10.1002/anie.202103086

PMID:33754433

Abstract

Here, we show the fabrication of the carbon dots (CDs) with green and orange emissions from PTCDA (perylene-3,4,9,10-tetracarboxylic dianhydride). Using these CDs as emitters, the orange (or green) CDs LEDs were fabricated, which show electroluminescence (EL) spectra centered at 560 nm (or 498 nm) with an external quantum efficiency (EQE) of 1.98 % (1.76 %) adhering a luminescence of 626 cd m (or 519 cd m ). The machine learning was successfully used to predict PL CCT value. With the model, the white photoluminescence (PL) emission with adjustable correlated color temperature (CCT) from 3093 to 11018 K via combining blue, green, and orange CDs was achieved. Then, we obtained the warm white CDs LEDs with CCT of 3107, 4071 and 4548 K, and cold white CDs LEDs with CCT of 5632 (CIE coordinates of (0.33, 0.33), EQE: 1.18 %, luminescence: 598 cd m ) and 6034 K accurately.

摘要

在此，我们展示了由苝-3,4,9,10-四羧酸二酐（PTCDA）制备的具有绿色和橙色发射的碳点（CDs）。使用这些碳点作为发光体，制备了橙色（或绿色）碳点发光二极管，其电致发光（EL）光谱中心位于560 nm（或498 nm），外量子效率（EQE）为1.98%（1.76%），发光强度为626 cd m（或519 cd m）。机器学习成功用于预测光致发光相关色温（PL CCT）值。利用该模型，通过组合蓝色、绿色和橙色碳点，实现了相关色温（CCT）在3093至11018 K之间可调的白色光致发光（PL）发射。然后，我们精确获得了色温为3107、4071和4548 K的暖白色碳点发光二极管，以及色温为5632（CIE坐标为(0.33, 0.33)，EQE：1.18%，发光强度：598 cd m）和6034 K的冷白色碳点发光二极管。