This conference presentation was prepared for the Advances in Display Technologies XIII conference at SPIE OPTO, 2023.

This conference presentation was prepared for the Advances in Display Technologies XIII conference at SPIE OPTO, 2023.

This conference presentation was prepared for the Advances in Display Technologies XIII conference at SPIE OPTO, 2023.

Multi-Resonance Emitters (MREs) are a promising candidate for fulfilling the harsh requirements of display applications due to their unique photophysical properties. Recently, MREs have been widely used as a Terminal Emitter (TE) in Hyper Fluorescence Organic Light-Emitting Diodes (HF-OLEDs); however, since MREs are always TADF-active, possessing long triplet lifetimes in milli-second order, they result in severe chemical degradation. The device lifetime of blue OLED is still a challenge. Here, instead of shortening the delayed lifetime of MREs by molecular design, we introduced a low-triplet pyrene unit into an MRE scaffold to achieve narrowband emission and quick removal of triplets in MREs simultaneously. Blue HF-OLED based on the non-TADF MRE demonstrated a high external quantum efficiency (EQE) of 20% and a ten-fold improvement in stability, compared to those of the HF-OLEDs with standard MREs.

This conference presentation was prepared for the Advances in Display Technologies XIII conference at SPIE OPTO, 2023.

This conference presentation was prepared for the Advances in Display Technologies XIII conference at SPIE OPTO, 2023.

The combination of Computer-Generated Holography (CGH) and deep learning has opened the possibility to generate both real-time and high-quality holograms. However, the widely-used data-driven deep learning method faces the problem of the large number of labeled training datasets generated by traditional algorithms, such as Gerchberg–Saxton (GS) iterative algorithm. It always takes a long time and limits the training performance of the network. In this work, we propose a model-driven neural network for high-fidelity Phase-Only Hologram (POH) generation. The Fresnel diffraction process is introduced as the physical model, which makes the network can automatically learn the latent encodings of POHs in an unsupervised way. Furthermore, the sub-pixel convolution upsampling method effectively improves the reconstruction quality. Once the training is completed, the POH of any two-dimensional image can be quickly generated. The calculation time is one to two orders of magnitude faster.

In this study, we developed a femtosecond pulse laser-based micro LED transfer process and optical system technology that precisely transfers micro LED chips with a size of several tens of micrometers. In order to realize the high-speed and precision transfer process of the micro LED chip, the femtosecond pulse laser was applied as a light source for the transfer process. In addition, dynamic release layer was applied to transfer micro LED chips at high speed without direct damages by laser. we analyzed the tendency of chip transfer process by adjusting the parameters for laser irradiation properties and material properties.