Electrical properties and structural optimization of GaN/InGaN/GaN tunnel junctions grown by molecular beam epitaxy

The InGaN films and GaN/InGaN/GaN tunnel junctions(TJs)were grown on GaN templates with plasma-assisted molecular beam epitaxy.As the In content increases,the quality of InGaN films grown on GaN templates decreases and the surface roughness of the samples increases.V-pits and trench defects were not found in the AFM images.p++-GaN/InGaN/n++-GaN TJs were investigated for various In content,InGaN thicknesses and doping concentration in the InGaN insert layer.The InGaN insert layer can promote good interband tunneling in GaN/InGaN/GaN TJ and significantly reduce operating voltage when doping is sufficiently high.The current density increases with increasing In content for the 3 nm InGaN insert layer,which is achieved by reducing the depletion zone width and the height of the potential barrier.At a forward current density of 500 A/cm^(2),the measured voltage was 4.31 V and the differential resistance was measured to be 3.75×10^(−3)Ω·cm^(2)for the device with a 3 nm p++-In_(0.35)Ga_(0.65)N insert layer.When the thickness of the In_(0.35)Ga_(0.65)N layer is closer to the“balanced”thickness,the TJ current density is higher.If the thickness is too high or too low,the width of the depletion zone will increase and the current density will decrease.The undoped InGaN layer has a better performance than n-type doping in the TJ.Polarization-engineered tunnel junctions can enhance the functionality and performance of electronic and optoelectronic devices.

Development of Long-Range,Low-Powered and Smart IoT Device for Detecting Illegal Logging in Forests

Forests promote the conservation of biodiversity and also play a crucial role in safeguarding theenvironment against erosion,landslides,and climate change.However,illegal logging remains a significant threatworldwide,necessitating the development of automatic logging detection systems in forests.This paper proposesthe use of long-range,low-powered,and smart Internet of Things(IoT)nodes to enhance forest monitoringcapabilities.The research framework involves developing IoT devices for forest sound classification andtransmitting each node’s status to a gateway at the forest base station,which further sends the obtained datathrough cellular connectivity to a cloud server.The key issues addressed in this work include sensor and boardselection,Machine Learning(ML)model development for audio classification,TinyML implementation on amicrocontroller,choice of communication protocol,gateway selection,and power consumption optimization.Unlike the existing solutions,the developed node prototype uses an array of two microphone sensors forredundancy,and an ensemble network consisting of Long Short-Term Memory(LSTM)and ConvolutionalNeural Network(CNN)models for improved classification accuracy.The model outperforms LSTM and CNNmodels when used independently and also gave 88%accuracy after quantization.Notably,this solutiondemonstrates cost efficiency and high potential for scalability.

Dual-wavelength ultraviolet photodetector based on vertical(Al,Ga)N nanowires and graphene

Due to the wide application of UV-A(320 nm–400 nm)and UV-C(200 nm–280 nm)photodetectors,dual-wavelength(UV-A/UV-C)photodetectors are promising for future markets.A dual-wavelength UV photodetector based on vertical(Al,Ga)N nanowires and graphene has been demonstrated successfully,in which graphene is used as a transparent electrode.Both UV-A and UV-C responses can be clearly detected by the device,and the rejection ratio(R254 nm/R450 nm)exceeds35 times at an applied bias of-2 V.The short response time of the device is less than 20 ms.Furthermore,the underlying mechanism of double ultraviolet responses has also been analyzed systematically.The dual-wavelength detections could mainly result from the appropriate ratio of the thicknesses and the enough energy band difference of(Al,Ga)N and Ga N sections.

Interfacial dynamics of GaP/Si(100) heterostructure grown by molecular beam epitaxy

The atomic structure and surface chemistry of GaP/Si(100)heterostructure with different pre-layers grown by molecu-lar beam epitaxy are studied.It is found that GaP epilayer with Ga-riched pre-layers on Si(100)substrate has regular surface mor-phology and stoichiometric abrupt heterointerfaces from atomic force microscopes(AFMs)and spherical aberration-corrected transmission electron microscopes(ACTEMs).The interfacial dynamics of GaP/Si(100)heterostructure is investigated by X-ray photoelectron spectroscopy(XPS)equipped with an Ar gas cluster ion beam,indicating that Ga pre-layers can lower the inter-face formation energy and the bond that is formed is more stable.These results suggest that Ga-riched pre-layers are more con-ducive to the GaP nucleation as well as the epitaxial growth of GaP material on Si(100)substrate.

Smart Monitoring of Solar Photovoltaic Panels by the Approach of Machine Learning

The exploitation of renewable energy has become a pressing task due to climate change and the recent energy crisis caused by regional conflicts.This has further accelerated the rapid development of the global photovoltaic(PV)market,thereby making the management and maintenance of solar photovoltaic(SPV)panels a new area of business as neglecting it may lead to significant financial losses and failure to combat climate change and the energy crisis.SPV panels face many risks that may degrade their power generation performance,damage their structures,or even cause the complete loss of their power generation capacity during their long service life.It is hoped that these problems can be identified and resolved as soon as possible.However,this is a challenging task as a solar power plant(SPP)may contain hundreds even thousands of SPV panels.To provide a potential solution for this issue,a smart drone-based SPV panel condition monitoring(CM)technique has been studied in this paper.In the study,the U-Net neural network(UNNN),which is ideal for undertaking image segmentation tasks and good at handling small sample size problem,is adopted to automatically create mask images from the collected true color thermal infrared images.The support vector machine(SVM),which performs very well in highdimensional feature spaces and is therefore good at image recognition,is employed to classifying the mask images generated by the UNNN.The research result has shown that with the aid of the UNNN and SVM,the thermal infrared images that are remotely collected by drones from SPPs can be automatically and effectively processed,analyzed,and classified with reasonable accuracy(over 80%).Particularly,the mask images produced by the trained UNNN,which contain less interference items than true color thermal infrared images,significantly benefit the assessing accuracy of the health state of SPV panels.It is anticipated that the technical approach presented in this paper will serve as an inspiration for the exploration of more advanced and dependable smart asset management techniques within the solar power industry.

Flexible bidirectional self-powered photodetector with significantly reduced volume and accelerated response speed based on hydrogel and lift-off GaN-based nanowires

Due to the wide range of potential applications for next-generation multi-functional devices,the flexible selfpowered photodetector(PD)with polarity-switchable behavior is essential but very challenging to be realized.Herein,a wearable bidirectional self-powered PD based on detached(Al,Ga)N and(In,Ga)N nanowires has been proposed and demonstrated successfully.Arising from the photovoltage-competing dynamics across(Al,Ga)N and(In,Ga)N nanowire photoelectrodes,such PD can generate the positive(33.3 mA W−1)and negative(-0.019 mA W−1)photo-responsivity under ultraviolet(UV)and visible illumination,respectively,leading to the bidirectional photocurrent behavior.Thanks to the introduction of quasi solid-state hydrogel,the PD can work without the liquid-electrolyte,thus remarkably reducing the volume from about 482 cm3 to only 0.18 cm3.Furthermore,the use of hydrogel is found to enhance response speed in the UV range by reducing the response time for more than 95%,which is mainly attributed to the increased open circuit potential and reduced ion transport distance.As the GaN connecting segment is pretty thin,the piezoelectric charges generated by stress are proposed to have only a limited effect on the photocurrent density.Therefore,both the stable on-off switching characteristics and photocurrent densities can still be achieved after being bent 400 times.With an excellent flexibility,this work creates opportunities for technological applications of bidirectional photocurrent PDs in flexible optoelectronic devices,e.g.,wearable intelligent sensors.

CypA Regulates AIP4-Mediated M1 Ubiquitination of Influenza A Virus

Cyclophilin A (CypA) is a peptidyl-prolyl cis/trans isomerase that interacts with the matrix protein (M1) of influenza A virus (IAV) and restricts virus replication by regulating the ubiquitin–proteasome-mediated degradation of M1. However,the mechanism by which CypA regulates M1 ubiquitination remains unknown. In this study, we reported that E3 ubiquitin ligase AIP4 promoted K48-linked ubiquitination of M1 at K102 and K104, and accelerated ubiquitin–proteasome-mediated degradation of M1. The recombinant IAV with mutant M1 (K102 R/K104 R) could not be rescued, suggesting that the ubiquitination of M1 at K102/K104 was essential for IAV replication. Furthermore, CypA inhibited AIP4-mediated M1 ubiquitination by impairing the interaction between AIP4 and M1. More importantly, both the mutations of M1 (K102 R/K104 R) and CypA inhibited the nuclear export of M1, indicating that CypA regulates the cellular localization of M1 via inhibition of AIP4-mediated M1 ubiquitination at K102 and K104, which results in the reduced replication of IAV.Collectively, our findings reveal a novel ubiquitination-based mechanism by which CypA regulates the replication of IAV.

Interferon as a Mucosal Adjuvant for an Influenza Vaccine in Pigs

Interferon, a natural protein that is produced by a variety of cells during viral infection, activates the transcription of multiple functional genes in cells, regulates synergy among various signaling pathways, and mediates many biological functions such as antiviral activity, immune regulation, and cell growth. However, clinical research on interferon in livestock is lacking. In this study, recombinant porcine interferon(PoIFNa) was used as an adjuvant, in combination with inactivated influenza virus, to vaccinate 6-week-old pigs via nasal infusion. The transcription of target genes was then monitored and the functions of PoIFNa were determined with respect to the activation of mucosal immunity. We found that a combination of low-dose PoIFNa and inactivated influenza virus could significantly up-regulate the expression of immunoregulatory cytokines such as IL-2, IL-18, IFN-c, IL-6, and IL-10 by real-time PCR, suggesting the induction of a strong mucosal innate immune response after administration. In addition, low-dose PoIFNa can significant enhancing the transcription of genes encoding homing factors including CCR9 and CCR10(P \ 0.001), thereby resulting in the induction of higher levels of HA-specific antibodies(P \ 0.05), which can be determined by ELISA and IFA. Post-immunization challenges with H1 N1 virus demonstrated that PoIFNa, combined with inactivated influenza virus, could alleviate clinical signs in pigs during the early stages of viral infection. These studies reveal low-dose PoIFNa as a potential mucosal adjuvant for influenza virus in pigs.

Power fluctuation and power loss of wind turbines due to wind shear and tower shadow

The magnitude and stability of power output are two key indices of wind turbines. This study investigates the effects of wind shear and tower shadow on power output in terms of power fluctuation and power loss to estimate the capacity and quality of the power generated by a wind turbine. First, wind speed models, particularly the wind shear model and the tower shadow model, are described in detail. The widely accepted tower shadow model is modified in view of the cone-shaped towers of modem large-scale wind turbines. Power fluctuation and power loss due to wind shear and tower shadow are analyzed by performing theoretical calculations and case analysis within the framework of a modified version of blade element momentum theory. Results indicate that power fluctuation is mainly caused by tower shadow, whereas power loss is primarily induced by wind shear. Under steady wind conditions, power loss can be divided into wind farm loss and rotor loss. Wind farm loss is constant at 3a（3a- 1）R^2/（8H^2）. By contrast, rotor loss is strongly influenced by the wind turbine control strategies and wind speed. That is, when the wind speed is measured in a region where a variable-speed controller works, the rotor loss stabilizes around zero, but when the wind speed is measured in a region where the blade pitch controller works, the rotor loss increases as the wind speed intensifies. The results of this study can serve as a reference for accurate power estimation and strategy development to mitigate the fluctuations in aerodynamic loads and power output due to wind shear and tower shadow.

Optical properties of Zn-diffused InP layers for the planar-type InGaAs/InP photodetectors

Zn diffusion into InP was carried out ex-situ using a new Zn diffusion technique with zinc phosphorus particles placed around InP materials as zinc source in a semi-closed chamber formed by a modified diffusion furnace. The optical characteristics of the Zn-diffused InP layer for the planar-type InGaAs/InP PIN photodetectors grown by molecular beam epitaxy （MBE） has been investigated by photoluminescence （PL） measurements. The temperature-dependent PL spectrum of Zn-diffused InP samples at different diffusion temperatures showed that band-to-acceptor transition dominates the PL emission, which indicates that Zn was commendably diffused into InP layer as the acceptor. High quality Zn-diffused InP layer with typically smooth surface was obtained at 580 ℃for 10 min. Furthermore, more interstitial Zn atoms were activated to act as acceptors after a rapid annealing process. Based on the above Zn-diffusion technique, a 50μm planar-type InGaAs/InP PIN photodector device was fabricated and exhibited a low dark current of 7.73 pA under a reverse bias potential of -5 V and a high break- down voltage of larger than 41 V （1 〈 10μA）. In addition, a high responsivity of 0.81 A/W at 1.31/~m and 0.97 A/W at 1.55μm was obtained in the developed PIN photodetector.