DOI: https://doi.org/10.29363/nanoge.DEPERO.2023.008
Publication date: 14th September 2023
With the rapid improvements in both of the external quantum efficiency and operating lifetimes of QLEDs, it approaches to the gate of industrialization for flat display applications. Since blue QLED is known to be one of the most important remaining difficult, it has been of great interests to develop the materials and device for OLEDs. In the past three years, we have tried to remove the bastion of blue QLEDs. In this talk, I will introduce our recent progress in the colloidal synthesis large sized ZnSe nanocrystals with pure blue emission as well the introduction of machine learning methodology in device analysis. Large-sized ZnSe nanocrystals with an emission peak of 455-475 nm are synthesized with a general strategy of reactivity-controlled epitaxial growth (RCEG) was developed through sequential injection of high-reactivity and low-reactivity Zn and Se precursors. We further fabricated stable, large-sized ZnSe/ZnS core-shell nanocrystals with photoluminescence quantum yields up to ~60%. Very recently, we build up a machine learning assisted methodology to predict the operational stability of blue QLEDs by analyzing the measurements of over 200 devices. By developing a convolutional neural network (CNN) model, the methodology is able to predict the operation lifetime of QLED.
This work was supported by Beijing Natural Science Foundation (Z210018, H. Z.)
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