High photoelectric conversion efficiency and fast relaxation time of FA_(0.4)MA_(0.6)PbI_(3) applied in ultrafast modulation of terahertz waves

Active control of terahertz(THz)waves is attracting tremendous attentions in terahertz communications and active photonic devices.Perovskite,due to its excellent photoelectric conversion performance and simple manufacturing process,has emerged as a promising candidate for optoelectronic applications.However,the exploration of perovskites in optically controlled THz modulators is still limited.In this work,the photoelectric properties and carrier dynamics of FA_(0.4)MA_(0.6)PbI_(3)perovskite films were investigated by optical pumped terahertz probe(OPTP)system.The ultrafast carrier dynamics reveal that FA_(0.4)MA_(0.6)PbI_(3)thin film exhibits rapid switching and relaxation time within picosecond level,suggesting that FA_(0.4)MA_(0.6)PbI_(3)is an ideal candidate for active THz devices with ultrafast response.Furthermore,as a proof of concept,a FA_(0.4)MA_(0.6)PbI_(3)-based metadevice with integrating plasma-induced transparency(PIT)effect was fabricated to achieve ultrafast modulation of THz wave.The experimental results demonstrated that the switching time of FA_(0.4)MA_(0.6)PbI_(3)-based THz modulator is near to 3.5 ps,and the threshold of optical pump is as low as 12.7μJ cm^(-2).The simulation results attribute the mechanism of ultrafast THz modulation to photo-induced free carriers in the FA_(0.4)MA_(0.6)PbI_(3)layer,which progressively shorten the capacitive gap of PIT resonator.This study not only illuminates the potential of FA_(0.4)MA_(0.6)PbI_(3)in THz modulation,but also contributes to the field of ultrafast photonic devices.

A Novel Multiple DBC-staked units Package to Parallel More Chips for SiC Power Module

Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation signals.The proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed model.The proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to LWNet.Furthermore, the model also has a moderate computation complexity compared with several state-of-the-art methods.

A review on the cooling of energy conversion and storage systems using thermoelectric modules

Exploitation of sustainable energy sources requires the use of unique conversion and storage systems,such as solar panels,batteries,fuel cells,and electronic equipment.Thermal load management of these energy conversion and storage systems is one of their challenges and concerns.In this article,the thermal management of these systems using thermoelectric modules is reviewed.The results show that by choosing the right option to remove heat from the hot side of the thermoelectric modules,it will be a suitable local cooling,and the thermoelectric modules increase the power and lifespan of the system by reducing the spot temperature.Thermoelectric modules were effective in reducing panel temperature.They increase the time to reach a temperature above 50℃ in batteries by 3 to 4 times.Also,in their integration with fuel cells,they increase the power density of the fuel cell.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

Engineering vascularized organotypic tissues via module assembly

Adequate vascularization is a critical determinant for the successful construction and clinical implementation of complex organotypic tissue models. Currently, low cell and vessel density and insufficient vascular maturation make vascularized organotypic tissue construction difficult,greatly limiting its use in tissue engineering and regenerative medicine. To address these limitations, recent studies have adopted pre-vascularized microtissue assembly for the rapid generation of functional tissue analogs with dense vascular networks and high cell density. In this article, we summarize the development of module assembly-based vascularized organotypic tissue construction and its application in tissue repair and regeneration, organ-scale tissue biomanufacturing, as well as advanced tissue modeling.

A Hybrid Integrated and Low-Cost Multi-Chip Broadband Doherty Power Amplifier Module for 5G Massive MIMO Application

In this paper,a hybrid integrated broadband Doherty power amplifier(DPA)based on a multi-chip module(MCM),whose active devices are fabricated using the gallium nitride(GaN)process and whose passive circuits are fabricated using the gallium arsenide(GaAs)integrated passive device(IPD)process,is proposed for 5G massive multiple-input multiple-output(MIMO)application.An inverted DPA structure with a low-Q output network is proposed to achieve better bandwidth performance,and a single-driver architecture is adopted for a chip with high gain and small area.The proposed DPA has a bandwidth of 4.4-5.0 GHz that can achieve a saturation of more than 45.0 dBm.The gain compression from 37 dBm to saturation power is less than 4 dB,and the average power-added efficiency(PAE)is 36.3%with an 8.5 dB peak-to-average power ratio(PAPR)in 4.5-5.0 GHz.The measured adjacent channel power ratio(ACPR)is better than50 dBc after digital predistortion(DPD),exhibiting satisfactory linearity.

Research on the LA-UMamba Model for Asymmetric Modules with Added Auxiliary Information

Deep learning techniques are revolutionizing the developmentof medical image segmentation.With the advancement of Transformer models,especially ViT and Swin-Transformer,which enhances the remote-dependent modeling capability of the model through the self-attention mechanism,better segmentation performance can be achieve.Moreover,the high computational cost of Transformer has motivated researchers to explore more efficient models,such as the Mamba model based on state-space modeling(SSM),and for the field of medical segmentation,reducing the number of model parameters is also necessary.In this study,a novel asymmetric model called LA-UMamba was proposed,which integrates visual Mamba module to efficiently capture complex visual features and remote dependencies.The classical design of U-Net was adopted in the upsampling phase to help reduce the number of references and recover more details.To mitigate the information loss problem,an auxiliary U-Net downsampling layer was designed to focus on sizing without extracting features,thus enhancing the protection of input information while maintaining the efficiency of the model.The experiments were conducted on the ACDC MRI cardiac segmentation dataset,and the results showed that the proposed LA-UMamba achieves proved performance compared to the baseline model in several evaluation metrics,such as IoU,Accuracy,Precision,HD and ASD,which improved that the model is successful in optimizing the detail processing and reducing the complexity of the model,providing a new perspective for further optimization of medical image segmentation techniques.

Highly Efficient and Stable FAPbI_(3) Perovskite Solar Cells and Modules Based on Exposure of the(011)Facet

Perovskite crystal facets greatly impact the performance and stability of their corresponding photovoltaic devices.Compared to the(001)facet,the(011)facet yields better photoelectric properties,including higher conductivity and enhanced charge carrier mobility.Thus,achieving(011)facet-exposed films is a promising way to improve device performance.However,the growth of(011)facets is energetically unfavorable in FAPbI_(3) perovskites due to the influence of methylammonium chloride additive.Here,1-butyl-4-methylpyridinium chloride([4MBP]Cl)was used to expose(011)facets.The[4MBP]^(+)cation selectively decreases the surface energy of the(011)facet enabling the growth of the(011)plane.The[4MBP]^(+)cation causes the perovskite nuclei to rotate by 45°such that(011)crystal facets stack along the out-of-plane direction.The(011)facet has excellent charge transport properties and can achieve better-matched energy level alignment.In addition,[4MBP]Cl increases the activation energy barrier for ion migration,suppressing decomposition of the perovskite.As a result,a small-size device(0.06 cm2)and a module(29.0 cm2)based on exposure of the(011)facet achieved power conversion efficiencies of 25.24%and 21.12%,respectively.

Efficient and Stable Inverted Perovskite Solar Modules Enabled by Solid-Liquid Two-Step Film Formation

A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.

Analysis of thermal management and anti-mechanical abuse of multi-functional battery modules based on magneto-sensitive shear thickening fluid

Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications.This paper proposes an innovative active protection and cooling integrated battery module using smart materials,magneto-sensitive shear thickening fluid(MSTF),which is specifically designed to address safety threats posed by lithium-ion batteries(LIBs)exposed to harsh mechanical and environmental conditions.The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics(SPH)methodology that incorporates the intricate interplay of non-Newtonian fluid behavior,capturing the fluid-structure coupling inherent to the MSTF.This approach is further advanced by adopting an enhanced Herschel-Bulkley(H-B)model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect(MRE)and shear thickening(ST)behavior.Numerical simulation results show that in the case of cooling,the MSTF is an effective cooling medium for rapidly reducing the temperature.In terms of mechanical abuse,the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module,resulting in 66%and 61.7%reductions in the maximum stress within the battery jellyroll,and 31.1%and 23%reductions in the reaction force,respectively.This mechanism effectively lowers the risk of short-circuit failure.The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

Light-modulated graphene-based φ_(0) Josephson junction and -φ_(0) to φ_(0) transition

We investigate the chiral edge states-induced Josephson current–phase relation in a graphene-based Josephson junction modulated by the off-resonant circularly polarized light and the staggered sublattice potential.By solving the Bogoliubov–de Gennes equation,a φ_(0) Josephson junction is induced in the coaction of the off-resonant circularly polarized light and the staggered sublattice potential,which arises from the fact that the center of-mass wave vector of Cooper pair becomes finite and the opposite center of-mass wave vector to compensate is lacking in the nonsuperconducting region.Interestingly,when the direction of polarization of light is changed,-φ_(0) to φ_(0) transition generates,which generalizes the concept of traditional 0–πtransition.Our findings provide a purely optical way to manipulate a phase-controllable Josephson device and guidelines for future experiments to confirm the presence of graphene-based φ_(0)Josephson junction.

Heat dissipation enhancement method for finned heat sink for AGV motor driver's IGBT module

With the widespread use of high-power and highly integrated insulated gate bipolar transistor(IGBT),their cooling methods have become challenging.This paper proposes a liquid cooling scheme for heavy-duty automated guided vehicle(AGV)motor driver in port environment,and improves heat dissipation by analyzing and optimizing the core component of finned heat sink.Firstly,the temperature distribution of the initial scheme is studied by using Fluent software,and the heat transfer characteristics of the finned heat sink are obtained through numerical analysis.Secondly,an orthogonal test is designed and combined with the response surface methodology to optimize the structural parameters of the finned heat sink,resulting in a 14.57%increase in the heat dissipation effect.Finally,the effectiveness of heat dissipation enhancement is verified.This work provides valuable insights into improving the heat dissipation of IGBT modules and heat sinks,and provides guidance for their future applications.

Unsupervised multi-modal image translation based on the squeeze-and-excitation mechanism and feature attention module

The unsupervised multi-modal image translation is an emerging domain of computer vision whose goal is to transform an image from the source domain into many diverse styles in the target domain.However,the multi-generator mechanism is employed among the advanced approaches available to model different domain mappings,which results in inefficient training of neural networks and pattern collapse,leading to inefficient generation of image diversity.To address this issue,this paper introduces a multi-modal unsupervised image translation framework that uses a generator to perform multi-modal image translation.Specifically,firstly,the domain code is introduced in this paper to explicitly control the different generation tasks.Secondly,this paper brings in the squeeze-and-excitation(SE)mechanism and feature attention(FA)module.Finally,the model integrates multiple optimization objectives to ensure efficient multi-modal translation.This paper performs qualitative and quantitative experiments on multiple non-paired benchmark image translation datasets while demonstrating the benefits of the proposed method over existing technologies.Overall,experimental results have shown that the proposed method is versatile and scalable.

10Gb/s EML Module Based on Identical Epitaxial Layer Scheme

A 10Gb/s transmitter module containing an electroabsorption modulator monolithically integrated with a distributed feedback (DFB) semiconductor laser is fabricated using the identical epitaxial layer scheme.Gain-coupling mechanism is employed to improve the single mode yield of the DFB laser,while inductively coupled plasma dry etching technique is utilized to reduce the modulator capacitance.The integrated device exhibits a threshold current as low as 12mA and an extinction ratio over 15dB at -2V bias.The small signal modulation bandwidth is measured to be over 10GHz.The transmission experiment at 10Gb/s indicates a power penalty less than 1dB at a bit-error-rate of 10 -12 after transmission through 35km single mode fiber.

Tenda AX12路由器0-Day栈溢出漏洞挖掘方法

随着5G技术对物联网发展的加速,预计到2025年将会有约250亿台物联网设备连接到人们的生活。其中承担物联网设备网络管理角色的路由器使用量非常大,但是路由器存在众多安全问题,通过路由器设备进行攻击,可以非法获取用户信息。为了维护网络安全,提前发现路由器的漏洞具有重要的研究意义。本文以Tenda AX12路由器为研究对象,从固件入手对其进行0-Day栈溢出漏洞挖掘研究,并提出了基于危险函数追踪的逆向分析漏洞挖掘方法。首先从危险函数中分析函数所在前端的对应位置,将前后端对应;然后对固件中的Web服务进行分析,对其中可能发生栈溢出的httpd二进制代码进行危险函数分析,该方法使用反汇编代码对危险函数的普通形式和展开形式进行定位,并对危险函数进行参数分析和动态检测;接着通过搭建仿真模拟机在模拟机上运行该服务的二进制文件,并在Web前端页面对潜在漏洞位置进行数据包捕捉;最后根据前期分析的危险函数参数情况对包进行改写并发送,以此来触发漏洞,验证漏洞的存在性,同时验证该危险函数是否发生栈溢出。为了更真实地确定漏洞存在,我们又在真实设备上验证漏洞的真实存在性和可利用性。实验结果表明了该漏洞的挖掘检测方法的有效性,我们分别在不同型号的路由器上挖掘到4个0-Day漏洞,并且经过与SaTC工具进行对比实验结果表明该检测方法能够更准确的定位到出现漏洞的函数位置。

2018—2020年福建地区猪瘟病毒E0基因遗传变异分析

为了了解2018—2020年福建地区猪瘟病毒流行及遗传变异情况,收集福建省不同地区临床发病猪的血液和肺脏、脾脏、淋巴结等组织样本1464份,采用RT-nPCR的方法对样品进行CSFV检测,对部分CSFV阳性样品E0基因进行克隆测序。结果显示,CSFV总体阳性率为1.9%(29/1464),并获得13株CSFV E0基因序列。同源性分析发现所得13株CSFV E0基因之间的同源性在82.2%-99.7%,其中11株CSFV E0基因与1.1亚型代表毒株HCLV的核苷酸同源性为99.0%~99.9%,与Shimen株的核苷酸同源性94.1%~95.0%;1株与2.1c型参考毒株HNSD-2012核苷酸同源性为98.2%;1株与2.1d亚型毒株CSFV/JPN/2018核苷酸同源性为99.6%。遗传进化分析发现,10株CSFV与HCLV、C-ZJ-2008、Shimen和Brescia处于同一分支,属于1.1亚型;1株CSFV与HNSD-2012等位于同一分支,属于2.1c亚亚型;1株与CSFV/JPN/2018等位于同一分支,属于2.1d亚亚型。氨基酸序列分析发现,13株毒株与HCLV等代表毒株在重要的Rnase活性位点高度保守,其中2株2.1亚型毒株与HCLV毒株相比,其在第35位非关键氨基酸残基上发生由G→E的突变。结果表明福建地区CSFV流行情况趋向多样化,提示仍需加强对CSFV流行及遗传变异的持续监测,为猪瘟的诊断及有效防控奠定基础。