Data driven high quantum yield halide perovskite phosphors design and fabrication

被引：0
|
作者：
Mai, Haoxin [1 ]
Wen, Xiaoming [1 ,2 ]
Li, Xuying [1 ]
Dissanayake, Nethmi S.L. [3 ]
Sun, Xueqian [3 ]
Lu, Yuerui [3 ]
Le, Tu C. [4 ]
Russo, Salvy P. [5 ]
Chen, Dehong [1 ]
Winkler, David A. [6 ,7 ,8 ]
Caruso, Rachel A. [1 ]
机构：
[1] Applied Chemistry and Environmental Science, School of Science, STEM College, RMIT University, Melbourne,VIC,3001, Australia
[2] School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn,VIC,3122, Australia
[3] School of Engineering, College of Engineering, Computing and Cybernetics, The Australian National University, Canberra,ACT,2601, Australia
[4] School of Engineering, STEM College, RMIT University, GPO Box 2476, Melbourne,VIC,3001, Australia
[5] ARC Centre of Excellence in Exciton Science, School of Science, RMIT University, Melbourne,VIC,3000, Australia
[6] Monash Institute of Pharmaceutical Sciences, Monash University, Parkville,VIC,3052, Australia
[7] School of Biochemistry and Chemistry, La Trobe University, Kingsbury Drive, Bundoora,VIC,3042, Australia
[8] School of Pharmacy, University of Nottingham, Nottingham,NG7 2RD, United Kingdom
来源：
Materials Today | / 74卷
关键词：
Compilation and indexing terms; Copyright 2025 Elsevier Inc;
D O I：
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中图分类号：
学科分类号：
摘要：
Aluminum compounds - Fabrication - Light emitting diodes - Machine learning - Perovskite - Phosphors - Quantum yield
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页码：12 / 21
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