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The quantum dot (QD) color-conversion efficiency (CCE) in GaN micro-light-emitting diodes ( $\mu $ LEDs) is greatly improved by non-radiative energy transfer (NRET) mechanism. An array of deep nano-holes with a diameter of about $1~\mu \text{m}$ was fabricated in $\mu $ LED mesas ( $40\times 60\,\,\mu \text{m}^{2}$ ) by nanoimprint lithography. The nano-holes were etched straight through the $\mu $ LED active region to ensure that the filled QDs were in extremely close contact with the active region. The absorption efficiency and emission efficiency of QDs are effectively improved by NRET, resulting in a superhigh CCE in QD- $\mu $ LED hybrid devices. Compared to $\mu $ LED devices with conventional spin-coated QDs, the CCE of novel nano-hole $\mu $ LEDs with filled QDs has been enhanced by about 118%.

Using deep reinforcement learning to solve traffic signal control problems is a research hotspot in the intelligent transportation field. Researchers have recently proposed various solutions based on deep reinforcement learning methods for intelligent transportation problems. However, most signal control optimization takes the maximization of traffic capacity as the optimization goal, ignoring the concerns of pedestrians at intersections. To address this issue, we propose a pedestrian-considered deep reinforcement learning traffic signal control method. The method combines a reinforcement learning network and traffic signal control strategy with traffic efficiency and safety aspects. At the same time, the waiting time of pedestrians and vehicles passing through the intersection is considered, and the Discrete Traffic State Encoding (DTSE) method is applied and improved to define the more comprehensive states and rewards. In the training of the neural network, the multi-process operation method is adopted, and multiple environments are run for training simultaneously to improve the model’s training efficiency. Finally, extensive simulation experiments are conducted on actual intersection scenarios using the simulation software Simulation of Urban Mobility (SUMO). The results show that compared to Dueling DQN, the waiting time due to our method decreased by 58.76% and the number of people waiting decreased by 51.54%. The proposed method can reduce both the number of people waiting and the waiting time at intersections.

NH-μLED, namely a micro light-emitting diode structure with nano-holes dug all the way through the active region, is designed to make silver nanoparticles in extremely close contact with the quantum wells for improving the coupling between the localized surface plasmon and the quantum wells (LSP-QWs coupling) and thus enhancing the optical properties of the μLED. The experimental results show that, thanks to this deep nanohole structure, the LSP-QWs coupling can be realized effectively, which ultimately increases the optical performance of the μLED. The internal quantum efficiency of the NH-μLED filled with silver nanoparticles is increased by 12%, and the final optical output power is also enhanced. We have further carried out a comparison study which measures the transient lifetime of two different types of μLEDs, and the results provide convincing evidence for the existence of the ultra close range LSP-QWs coupling effect.