Machine Learning‐Assisted Hybrid Package of White Light‐Emitting Diodes Employing Quantum Dots and Phosphor
Source abstract
Abstract
Abstract White light‐emitting diodes (WLEDs), known for their high brightness, high efficiency, and long lifetime, are widely utilized in the backlight of liquid crystal displays. However, it is still difficult to improve the color gamut of WLEDs while maintaining the L50 lifetime. The luminous characteristics of WLEDs employing different combinations of quantum dots and phosphor are investigated in this work. Additionally, investigations on the L50 lifetime for WLEDs are carried out by employing a two‐step accelerated stress method. Finally, an ensemble machine learning model is proposed to predict the L50 lifetime of WLEDs, achieving high predictive accuracy with R2 of 0.986.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Quantum Dots Synthesis And Properties · Molecular Communication and Nanonetworks · Gas Sensing Nanomaterials and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Innovation Platform for the Fusion of Industry and Education in Integrated Circuits Department of Electronic Science School of Electronic Science and Engineering Xiamen University Xiamen 361005 China
Funding
National Natural Science Foundation of China · Fujian Provincial Department of Science and Technology
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