Progress of GaN-Based Optoelectronic Devices Integrated with Optical Resonances

Low-Power Perovskite Neuromorphic Synapse with Enhanced Photon Efficiency for Directional Motion Perception

The advancement of artificial intelligent vision systems heavily relies on the development of fast and accurate optical imaging detection, identification, and tracking. Framed by restricted response speeds and low computational efficiency, traditional optoelectronic information devices are facing challenges in real-time optical imaging tasks and their ability to efficiently process complex visual data. To address the limitations of current optoelectronic information devices, this study introduces a novel photomemristor utilizing halide perovskite thin films. The fabrication process involves adjusting the iodide proportion to enhance the quality of the halide perovskite films and minimize the dark current. The photomemristor exhibits a high external quantum efficiency of over 85%, which leads to a low energy consumption of 0.6 nJ. The spike timing-dependent plasticity characteristics of the device are leveraged to construct a spiking neural network and achieve a 99.1% accuracy rate of directional perception for moving objects. The notable results offer a promising hardware solution for efficient optoneuromorphic and edge computing applications.

Feature-Assisted Machine Learning for Predicting Band Gaps of Binary Semiconductors

The band gap is a key parameter in semiconductor materials that is essential for advancing optoelectronic device development. Accurately predicting band gaps of materials at low cost is a significant challenge in materials science. Although many machine learning (ML) models for band gap prediction already exist, they often suffer from low interpretability and lack theoretical support from a physical perspective. In this study, we address these challenges by using a combination of traditional ML algorithms and the 'white-box' sure independence screening and sparsifying operator (SISSO) approach. Specifically, we enhance the interpretability and accuracy of band gap predictions for binary semiconductors by integrating the importance rankings of support vector regression (SVR), random forests (RF), and gradient boosting decision trees (GBDT) with SISSO models. Our model uses only the intrinsic features of the constituent elements and their band gaps calculated using the Perdew-Burke-Ernzerhof method, significantly reducing computational demands. We have applied our model to predict the band gaps of 1208 theoretically stable binary compounds. Importantly, the model highlights the critical role of electronegativity in determining material band gaps. This insight not only enriches our understanding of the physical principles underlying band gap prediction but also underscores the potential of our approach in guiding the synthesis of new and valuable semiconductor materials.

χ(2) nonlinear photonics in integrated microresonators

Second-order (χ⁽²⁾) optical nonlinearity is one of the most common mechanisms for modulating and generating coherent light in photonic devices. Due to strong photon confinement and long photon lifetime, integrated microresonators have emerged as an ideal platform for investigation of nonlinear optical effects. However, existing silicon-based materials lack a χ⁽²⁾ response due to their centrosymmetric structures. A variety of novel material platforms possessing χ⁽²⁾ nonlinearity have been developed over the past two decades. This review comprehensively summarizes the progress of second-order nonlinear optical effects in integrated microresonators. First, the basic principles of χ⁽²⁾ nonlinear effects are introduced. Afterward, we highlight the commonly used χ⁽²⁾ nonlinear optical materials, including their material properties and respective functional devices. We also discuss the prospects and challenges of utilizing χ⁽²⁾ nonlinearity in the field of integrated microcavity photonics.

The Effect of Periodic Duty Cyclings in Metal-Modulated Epitaxy on GaN:Mg Film

Metal modulation epitaxy (MME) is a technique in which metal beams (Al, Ga, In, and Mg) are switched on and off in short periods in an RF MBE system while a continuous nitrogen plasma beam is kept on. We systematically studied the effect of periodic duty cycling on the morphology, crystalline quality, Mg doping concentration, and electrical properties of GaN:Mg films grown by MME. When the metal shutter duty cycling is 20 s open/10 s close, the sample has smooth surface with clear steps even with Mg doping concentration higher than 1 × 10²⁰ cm^-3. The RMS roughness is about 0.5 nm. The FWHM of (002) XRD rocking curve is 230 arcsec and the FWHM of (102) XRD rocking curve is 260 arcsec. As result, a hole concentration of 5 × 10¹⁸ cm^-3 and a resistivity of 1.5 Ω·cm have been obtained. The hole concentration increases due to the incorporation of surface accumulated Mg dopants into suitable Ga substitutional sites with minimal formation of compensatory defects.

Fabrication of wafer-scale nanoporous AlGaN-based deep ultraviolet distributed Bragg reflectors via one-step selective wet etching

In this paper, we reported on wafer-scale nanoporous (NP) AlGaN-based deep ultraviolet (DUV) distributed Bragg reflectors (DBRs) with 95% reflectivity at 280 nm, using epitaxial periodically stacked n-Al_0.62Ga_0.38N/u-Al_0.62Ga_0.38N structures grown on AlN/sapphire templates via metal-organic chemical vapor deposition (MOCVD). The DBRs were fabricated by a simple one-step selective wet etching in heated KOH aqueous solution. To study the influence of the temperature of KOH electrolyte on the nanopores formation, the amount of charge consumed during etching process was counted, and the surface and cross-sectional morphology of DBRs were characterized by Scanning electron microscopy (SEM) and atomic force microscopy (AFM). As the electrolyte temperature increased, the nanopores became larger while the amount of charge reduced, which revealed that the etching process was a combination of electrochemical and chemical etching. The triangular nanopores and hexagonal pits further confirmed the chemical etching processes. Our work demonstrated a simple wet etching to fabricate high reflective DBRs, which would be useful for AlGaN based DUV devices with microcavity structures.

Photonics with Gallium Nitride Nanowires

The surface plasmon resonance in low-dimensional semiconducting materials is a source of valuable scientific phenomenon which opens widespread prospects for novel applications. A systematic study to shed light on the propagation of plasmons at the interface of GaN nanowire is reported. A comprehensive analysis of the interaction of light with GaN nanowires and the propagation of plasmons is carried out to uncover further potentials of the material. The results obtained on the basis of calculations designate the interaction of light with nanowires, which produced plasmons at the interface that propagate along the designed geometry starting from the center of the nanowire towards its periphery, having more flux density at the center of the nanowire. The wavelength of light does not affect the propagation of plasmons but the flux density of plasmons appeared to increase with the wavelength. Similarly, an increment in the flux density of plasmons occurs even in the case of coupled and uncoupled nanowires with wavelength, but more increment occurs in the case of coupling. Further, it was found that an increase in the number of nanowires increases the flux density of plasmons at all wavelengths irrespective of uniformity in the propagation of plasmons. The findings point to the possibility of tuning the plasmonics by using a suitable number of coupled nanowires in assembly.