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Hierarchical hollow microspheres assembled from carbon nanosheets integrated with molybdenum carbide nanoparticles for boosting microwave absorption properties

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Nano Research 2025年第1期18卷 10-20页

作者： Zongsheng Chen Yahui Wang Yi Liu Zhigang Li Xiangyin Lv Liping Liu Yajing Chang Jiaming Shi Xiao Zhang State Key Laboratory of Pulsed Power Laser Technology School of Electronic EngineeringNational University of Defense TechnologyHefei 230037China Anhui Provincial Laboratory of Advanced Laser Technology School of Electronic EngineeringNational University of Defense TechnologyHefei 230037China Centre for Environmental and Energy Nanomaterials Anhui Key Laboratory of Nanomaterials and NanotechnologyCAS Centre for Excellence in NanoscienceInstitute of Solid State PhysicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China

Hierarchical hollow structure has demonstrated potential for enhancing electromagnetic(EM)attenuation and improving impedance matching,garnering significant attention for ***,we have successfully implemented compositional and structural engineering to fabricate hollow Mo2C/C microspheres with controllable composition by coupling interaction between dopamine hydrochloride and ammonium *** the synergistic effect of composition and hollow structure,the strongest reflection loss intensity and broadest effective absorption of the optimized sample reach-70.2 dB and 6.2 GHz,*** formation of hollow heterogeneous structures not only favors impedance matching feature,but also generates considerable contribution to EM attenuation ***,radar cross-section simulation data indicate that hollow Mo2C/C microspheres with compositional optimization and heterogeneous structures have broad prospects for practical applications.

关键词： electromagnetic absorption Mo2C/C microwave absorption hollow structure

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High-precision numerical modeling of the pro jectile launch and failure mechanism analysis of pro jectile-borne components

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Applied Mathematics and Mechanics(English Edition) 2025年第5期46卷 885-906页

作者： Xindan GUO Qiming LIU Xu HAN Tao LI Bin’an JIANG Canwei CAI State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Artillery Ammunition Technology Laboratory PLA Army Academy of Artillery and Air DefenseHefei 230031China

As core components of precision-guided projectiles,projectile-borne components are highly susceptible to failure or even damage in complex high-overload environments,thereby significantly compromising launch reliability and ***,accurately characterizing the mechanical behavior of propellants remains challenging due to the limitations in the current internal ballistic theory and the constraints of large-scale artillery firing *** complicates the high-precision numerical modeling of projectile launch,and obstructs investigations into the failure mechanisms of projectile-borne ***,this paper identifies propellant parameters using the computational inverse method under uncertainty,further establishes high-precision numerical models of projectile launch,and explores the failure mechanisms of projectile-borne components in complex high-overload ***,a projectile launching experiment is meticulously designed and executed to obtain the breech pressure and muzzle ***,a general simulation model is built,and the powder burn model is used to simulate the ignition and ***,the propellant parameters are effectively identified with the computational inverse method by the combination of the experiments and simulations.A high-precision numerical model of projectile launch is modified with the parameters validated by another experiment,and the high-overload characteristics during projectile launch are thoroughly analyzed based on this ***,the high-overload characteristics of projectile-borne components are analyzed to elucidate the stress variation laws and to reveal the failure mechanisms influenced by time and spatial *** research provides an effective method for perfectly identifying propellant parameters and building high-precision numerical models of projectile ***,it provides significant guidance for the anti-high overload design and analysis of projectile-bo

关键词： projectile-borne component high-overload environment propellant parameter identification computational inverse technique failure mechanism

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Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal

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Plasma science and technology 2024年第8期26卷 64-72页

作者：熊俊卢诗宇刘晓明周文俊查晓明裴学凯 State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhan 430072People’s Republic of China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of TechnologyTianjin 300131People’s Republic of China

Discharge plasma parameter measurement is a key focus in low-temperature plasma *** diagnostics often require costly equipment,whereas electro-acoustic signals provide a rich,non-invasive,and less complex source of discharge *** study harnesses machine learning to decode these *** establishes links between electro-acoustic signals and gas discharge parameters,such as power and distance,thus streamlining the prediction *** building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques,the Mel-Frequency Cepstral Coefficients(MFCCs)of the acoustic signals are extracted to construct the *** machine learning models(Linear Regression,k-Nearest Neighbors,and Random Forest)are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge *** models display impressive performance in prediction precision and fitting *** them,the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error(MSE=0.00571)and the highest R-squared value(R^(2)=0.93877).The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm,which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.

关键词： discharge plasma plasma real-time diagnosis electro-acoustic signal machine learning acoustic signature

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Fault Diagnosis of Unmanned Aerial Vehicle Based on the Slime Mold Algorithm under Imbalanced Data Conditions 14

Fault Diagnosis of Unmanned Aerial Vehicle Based on the Slim...

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14th International Conference on reliability, Maintainability and Safety, ICRMS 2023

作者： Wu, Xinman Zhang, Wenjin Li, Yu Suo, Mingliang Institute of Reliability Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350329988

With the rapid progress of technology, the application of unmanned aerial vehicles (UAVs) has become widespread in various civilian and military activities. The research on fault diagnosis during a flight is a critical step towards enhancing the safety of UAV systems. Swarm-inspired heuristic algorithms have attracted significant attention owing to their fast iteration speed and strong optimization capabilities. This paper proposes a UAV fault diagnosis method based on the slime mold algorithm (SMA) under the condition of imbalanced data, thus addressing the issue of low diagnostic accuracy caused by a significantly longer normal flight time compared to the fault flight time in UAV operations. Using a real-world dataset of UAV flight faults with multiple fault patterns, the proposed approach optimizes the parameters of the support vector machine through SMA, thereby improving the fault diagnosis performance during actual UAV flights. © 2023 IEEE.

关键词： Micro air vehicle (MAV)

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Photo-enhanced uranium recovery from spent fuel reprocessing wastewater via S-scheme 2D/0D C_(3)N_(5)/Fe_(2)O_(3) heterojunctions

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SusMat 2024年第2期4卷 41-50页

作者： Qi Meng Linzhen Wu Xiaoyong Yang Ying Xiong Fanpeng Kong Tao Duan State Key Laboratory of Environment-friendly Energy Materials NuclearWaste and Environmental Safety Key Laboratory of DefenseSouthwest University of Science and TechnologyMianyangSichuanChina MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage Harbin Institute of TechnologyHarbinHeilongjiangChina Department of Materials Science and Engineering KTH Royal Institute of TechnologyStockholmSweden

Re-extracting environmentally transportable hexavalent uranium from wastew-ater produced by spent fuel reprocessing using the photocatalytic technology is a crucial strategy to avoid uranium pollution and recover nuclear fuel strategic ***,we have designed S-scheme 2D/0D C_(3)N_(5)/Fe_(2)O_(3)heterojunction photocatalysts based on the built-in electric field and the energy band bend-ing theory,and have further revealed the immobilization process of hexavalent uranium conversion into relatively insoluble tetravalent uranium in terms of thermodynamics and *** to the results,the hexavalent uranium removal and recovery ratios in wastewater are as high as 93.38%and 83.58%,***,C_(3)N_(5)/Fe_(2)O_(3)heterojunctions also exhibit satisfactory cat-alytic activity and selectivity even in the presence of excessive impurity cations(including Na^(+),K^(+),Ca^(^(2+)),Mg^(2+),Sr^(2+),and Eu^(3+))or various organics(such as xylene,tributylphosphate,pyridine,tannic acid,citric acid,and oxalic acid).It is believed that this work can provide a potential opportunity for S-scheme heterojunction photocatalysts to re-enrich uranium from spent fuel wastewater.

关键词： nuclear wastewater S-scheme heterostructure uranium recovery

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Giant negative electrocaloric effect measured by indirect method in X-ray irradiated P(VDF-TrFE)films

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Journal of Materiomics 2024年第3期10卷 624-631页

作者： Bo Li Bin Yang Hong Zhang Jiajia Zhang Qianjin Wang Weishu Liu Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhenGuangdong 518055China Guangdong Provincial Key Laboratory of Functional Oxide Materials and Devices Southern University of Science and TechnologyShenzhenChina College of Physics and Electronic Information Yunnan Normal UniversityYunnan Kunming 650500China The Science and Technology on Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research InstituteGuangzhou 510610China

Flexible solid-state cooling devices with high efficiency are attracted to ferroelectric polymers with excellent negative electrocaloric(EC)*** is challenging to obtain a large negative EC effect in ferroelectric polymers due to the lack of tunable techniques.A giant negative EC response was obtained in the poly(vinylidene fluoride-trifluoroethylene)copolymers(P(VDF-TrFE),70/30,in mole ratio)irra-diated with high-energy *** irradiated P(VDF-TrFE)films showed an adiabatic temperature change of-13.5 K at 40 MV/m under a dose of 5 Mrad(1 Mrad=10^(4) J/kg)obtained by the indirect *** significant negative EC effect is attributed to the enhancement of crystalline due to the entry of polymer molecules into the amorphous to crystalline structure and the reduction of heat ca-pacity due to the increase of *** addition,X-ray irradiation improves the dielectric coefficient from 15 to *** research indicates that irradiation can modify the negative EC properties of ferro-electric polymers for solid-state cooling.

关键词： Negative electrocaloric effects X-rays radiation P(VDF-TrFE)films

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escience 2023年第5期3卷 49-68页

作者： Zhengqing Ye Ying Jiang Li Li Feng Wu Renjie Chen Beijing Key Laboratory of Environmental Science and Engineering School of Material Science&EngineeringBeijing Institute of TechnologyBeijing100081China State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Material Science and EngineeringHebei University of TechnologyTianjin300401China Advanced Technology Research Institute Beijing Institute of TechnologyJinan250300China Collaborative Innovation Center of Electric Vehicles in Beijing Beijing100081China

The electrocatalytic sulfur reduction reaction(SRR)and sulfur evolution reaction(SER),two fundamental multistep conversion processes in lithium–sulfur batteries(LSBs),are root-cause solutions to overcome sluggish redox kinetics and the polysulfide shuttling ***–organic framework(MOF)electrocatalysts have emerged as good platforms for catalyzing SRR and SER,but their catalytic performance is challenged by poor electrical conductivity and limited chemical *** MOFs and their hybrids may be beneficial for stabilizing and improving the desired catalytic properties to achieve high-performance *** review provides a detailed overview of engineering principles for improving the activity,selectivity,and stability of MOFrelated electrocatalysts via composition modulation and nanostructure design as well as hybrid *** presents and discusses the various advances achieved by using in situ characterization techniques,simulations,and theoretical calculations to reveal the dynamic evolution of MOF-related electrocatalysts,enabling an in-depth understanding of the catalysis mechanism at the molecular/atomic ***,prospects and possible research directions for MOF-related sulfur electrocatalysts are proposed.

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Effect of Integration Time on the Performance Parameters of InGaAs Detectors

Effect of Integration Time on the Performance Parameters of ...

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2024 Conference on Spectral technology and Applications, CSTA 2024

作者： Luo, Xi Liu, Yuebo Zhang, Yichi Lu, Jianting Wei, Zhipeng Yang, Shaohua State Key Laboratory of High Power Semiconductor Lasers Changchun University of Science and Technology Changchun130022 China Reliability Physics and Application Technology of Electronic Component Key Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China

ISBN: (纸本)9781510683082

Shortwave infrared imaging has the characteristics of high recognition and all-weather adaptation. Consequently, InGaAs short-wave infrared (SWIR) detectors find extensive applications in military and civilian fields, which imposes higher performance demands on InGaAs SWIR detectors. To optimize the performance and effectiveness of InGaAs SWIR detectors, this study delves into the fluctuation patterns of detectivity, responsivity, and dynamic range concerning integration time. Furthermore, it examines the outcomes of these parameters at various integration times. It is observed that the performance of InGaAs SWIR detectors changes at different integration times, and each parameter exhibits specific variation patterns with integration time. © 2024 SPIE.

关键词： Infrared detectors

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Fault Diagnosis Model for UAV with Small Sample Size and Imbalanced Data 15

Fault Diagnosis Model for UAV with Small Sample Size and Imb...

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15th IEEE Global reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Song, Guoqing Ma, Ke Yang, Yang Dong, Yanchen Han, Danyang Suo, Mingliang School of Reliability and Systems Engineering Beihang University Beijing100191 China No.31850 People's Liberation Army of China Beijing102200 China Institute of Reliability Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering School of Reliability and Systems Engineering Beihang University Beijing100191 China

ISBN: (纸本)9798350354010

With the development of Unmanned Aerial Vehicles (UAV), their application scenarios and task requirements have become more complex, demanding higher standards for subsequent fault diagnosis and equipment maintenance. The actual flight data of UAV usually exhibits small sample sizes and imbalanced characteristics. To achieve more efficient fault prediction for UAV, this paper establishes a SMOTE-IWOA-RF fault diagnosis model. This model optimizes the Whale Optimization Algorithm (WOA) using chaotic initialization, nonlinear convergence factors, and Lévy flight strategies, resulting in better convergence accuracy and global search capability, as well as faster convergence speed. The model is compared with other classification models on data with different imbalance ratios, demonstrating that it is more efficient and accurate in UAV fault diagnosis, with the F1 score improving by about 10% compared to the pre-optimization state. Furthermore, the IWOA-RF model is combined with other data preprocessing methods, showing that SMOTE-IWOA-RF performs better on UAV operational data, indicating its practical value. © 2024 IEEE.

关键词： Fault detection

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Software fault localization based on eigenvector centrality in complex network theory 24

Software fault localization based on eigenvector centrality ...

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24th IEEE International Conference on Software Quality, reliability and Security Companion, QRS-C 2024

作者： Wu, Wentao Wang, Shihai Shao, Yuanxun Xie, Wandong School of Reliability and Systems Engineering Beihang University Beijing100191 China Science and Technology on Reliability and Environmental Engineering Laboratory China State Key Laboratory of Software Development Environment China Aerospace Science and Engineering Network Information Development CO. Ltd Beijing China Information Center of China North Industries Group Corporation Beijing China

ISBN: (纸本)9798350365658

Software debugging plays a crucial role in fault localization tasks, and spectrum-based fault localization (SBFL) is a hot topic in software automation debugging research. However, existing SBFL technologies are generally limited by tie within ranks, where a large number of elements share the same suspiciousness, which in turn severely limits the performance of SBFL. To this end, we propose an SBFL model based on eigenvector centrality (FLEC). This algorithm first utilizes the statement coverage information in the program spectrum to construct a statement network, and adopts the correlation between statements as edge weights. Then, FLEC takes statement suspiciousness as node weight. On this basis, the algorithm utilizes the eigenvector centrality to calculate the weighted suspiciousness of each statement while considering both node importance and correlation between nodes. Finally, FLEC conducted experimental validation on 3 datasets of Defects4J, and the results showed an average improvement of 10.7% in ACC@N compared to the optimal baseline. © 2024 IEEE.

关键词： Program debugging

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