DataVXAdvanced Optical MaterialsPaper
journal article·2024-03Open access

Data‐Driven Fine Element Tuning of Halide Double Perovskite for Enhanced Photoluminescence

Lingjun Wu, Zijian Chen, Zhongcheng Yuan, Bobin Wu, Shaohui Liu, Zixuan Wang, Jonathan P. Mailoa, Chenru Duan, Hao Huang, Chang‐Yu Hsieh, Xue‐Feng Yu, Haitao Zhao

Advanced Optical Materials· Volume 12· Issue 8
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Abstract

Abstract Element tuning of targeted materials and obtaining the optimal synthesis recipe are major goals for many material scientists. However, this is often limited by conventional trial‐and‐error procedures, which are time‐consuming and labor‐intensive. In this work, fine element tuning of halide double perovskite Cs2NaxAg1‐xInyBi1‐yCl6 is conducted by performing a data‐driven investigation combining high‐throughput experiments with machine learning (ML). A positive correlation between the more accessible R value in emission RGB values (the intensities of the red/green/blue primary colors) and photoluminescence intensity is revealed, and over a thousand R values of the Cs2NaxAg1‐xInyBi1‐yCl6 crystals synthesized with different additives and element compositions are collected. More importantly, the volume ratios of Na+/Ag+ (VNa: VAg) and Bi3+/In3+ (VBi: VIn) with the corresponding R values are correlated through ML, and the synergistic regulation of the two ion pairs is revealed. A possible correlation between R and XRD is also proposed. Finally, different emission intensities of LED beads coated with Cs2NaxAg1‐xInyBi1‐yCl6 synthesized using parameters obtained from ML are demonstrated, and an emission enhancement of ≈50 times is observed between the brightest and dimmest LEDs. This work illustrates that data‐driven investigation helps guide material synthesis and will significantly reduce the workload for developing novel materials, especially for complex compositions.
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Research context

Electronic materials

OpenAlex topics: Perovskite Materials and Applications · Chalcogenide Semiconductor Thin Films · Quantum Dots Synthesis And Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Materials Interfaces Center Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong 518055 P. R. China

Center for Intelligent and Biomimetic Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong 518055 P. R. China

Department of Chemical and Environmental Engineering The University of Nottingham Ningbo China Ningbo 315100 P. R. China

Clarendon Laboratory Department of Physics University of Oxford Parks Road Oxford OX1 3PU UK

Nano Science and Technology Institute University of Science and Technology of China Suzhou 215000 P. R. China

Quantum Laboratory Tencent Shenzhen Guangdong 518057 P. R. China

Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA

Innovation Institute for Artificial Intelligence in Medicine College of Pharmaceutical Sciences Zhejiang University Hangzhou 310058 P. R. China

Shenzhen Key Laboratory of Micro/Nano Biosensing Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong 518055 P. R. China

Hubei Three Gorges Laboratory Yichang Hubei 443007 P. R. China

Funding

National Natural Science Foundation of China · Natural Science Foundation of Guangdong Province

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