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SSRN 2024年

作者： Wang, Feng Guo, Ziwang Liu, Lulu Gong, Rui Jia, Guangri Xu, Yanchao Wei, Shuting Zhang, Dantong Ding, Baofu Cui, Xiaoqiang State Key Laboratory of Automotive Simulation and Control School of Materials Science and Engineering Key Laboratory of Automobile Materials of MOE Jilin University 2699 Qianjin Street Changchun130012 China Institute of Technology for Carbon Neutrality Shenzhen Institute of Advanced Technology CAS Shenzhen518055 China Key Laboratory of Materials Design and Quantum Simulation School of Science Changchun University No.6543 Satellite Road Changchun130022 China Faculty of Materials Science and Energy Engineering Shenzhen University of Advanced Technology Guangdong Shenzhen518055 China

Carrier recombination is one of the main factors in lowering charge separation efficiency, and thus severely restricts photocatalytic performance. In this work, we demonstrate a composite system of FAPbI3/MXene/Pt, featuring an internal energy cycling from the non-radiative fluorescence resonance energy transfer (FRET) between perovskite and MXene. That is, the energy of the emitted fluorescent photons is reabsorbed by each other. Recycling process exploits the energy released by carrier recombination and increases efficiency of charge separation. As a result, the composite of FAPbI3/MXene/Pt possesses a rapid H2 evolution rate of 2394 µmol g-1 h-1 under 1.5 AM simulated sunlight, which is more than one order of magnitude higher than that of FAPbI3/Pt (64 µmol g-1 h-1). The proposed insight not only provides an efficient strategy to promote photocatalytic H2 evolution based on perovskite-based composite, but also opens up opportunities to design other novel heterogeneous catalytic materials and promote their application potential in various catalytic fields. © 2024, The Authors. All rights reserved.

关键词： Perovskite

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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

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2021 CIE International Conference on Radar, Radar 2021

作者： Li, Hao Fang, Xueli Zhang, Lei Kang, Hui Zhang, Wei School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665498142

With the emergence of various kinds of complex radar jamming, radar jamming intelligent recognition technology has increasingly become the key to electronic counter-counter measures. To achieve radar jamming open-set recognition with a small number of tagged samples, Generative adversarial network-based pseudolabeled convolutional neural network (GAN-PL-CNN) model is proposed in this paper. Firstly, radar jamming is modelled, and the radar jamming datasets with known and unknown types are established after time-frequency transformation and image processing. Then, the adaptive pseudolabeling method is used to achieve semi-supervised recognition of radar jamming by combining the learning capability of convolutional neural networks and the characteristics of pseudolabeling to increase labeled samples intelligently. Finally, generative adversarial networks are introduced to enhance the recognition ability of the model and the discrimination ability of the unknown type through the game between the generator and the discriminator in the iterative process. Experimental results show that the GAN-PL-CNN model achieves 89.7%-95.1% for known types and 30.7%-86.8% for unknown types at 3%-6% labeling rate. As the number of labeled samples increases, the recognition effect becomes better and has a greater ability to exclude unknown type. © 2021 IEEE.

关键词： convolutional neural network open-set recognition pseudo-label Radar active jamming

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Radar Signal Modulation Recognition Based on Bispectrum Features and Deep learning 2

Radar Signal Modulation Recognition Based on Bispectrum Feat...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Dong, Zeyu Lv, Fengrong Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

Signal bispectral transformation can not only suppress the influence of Gaussian white noise on signal modulation recognition, but also retain the signal amplitude and phase information. It is also used to extract the non-linear characteristics. Compared with other high-order spectra, bispectrum has a simple processing flow. However, the direct use of all bispectrum as signal features will lead to two-dimensional template matching, causing lots of calculations. Converting two-dimensional bispectrum into one-dimensional sequence, for example, extracting slice information of bispectrum, or using integral bispectrum apparently reduce the amount of data to be processed while retaining part of the bispectrum information. We input the extracted bispectral transformation of radar signals into the neural network to realize modulation recognition. The simulations validate our conclusions that our proposed methods still have a high recognition probability while SNR is low. © 2021 IEEE.

关键词： Template matching

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Enhancing Corrosion Resistance of Metallic Surfaces with Hydrophobic H-BN Nanosheets

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SSRN 2024年

作者： Cheng, Ming Li, Wen Dun, Yuchao Chang, Wei Liu, Zeyu Wei, Qi Li, Shaojie Zhang, Xiaochen Nan, Yang Jin, Lei Aviation Key Laboratory of Science and Technology on Advanced Surface Engineering AVIC Manufacturing Technology Institute Beijing100024 China Science and Technology on Power Beam Processes Laboratory AVIC Manufacturing Technology Institute Beijing100024 China Technology Research Center Liyang Aero Power Co. LTD. AECC Guiyang550014 China

The relentless attack of corrosion on metallic surfaces is a pervasive issue that compromises the structural integrity and operational efficiency of materials in numerous industrial applications. This research aims to enhance the corrosion resistance of metallic surfaces through the application of hydrophobic hexagonal boron nitride (h-BN) nanosheets. The primary objectives of this research are to synthesize hydrophobic h-BN nanosheets (BNNS) and to evaluate the efficacy in providing corrosion protection to a variety of metallic substrates. By utilizing a mechanical exfoliation technique, the BNNS were derived from bulk h-BN, followed by a surface modification process to confer hydrophobicity. The synthesized BNNS underwent comprehensive characterization using an array of analytical tools to comprehensively assess the attributes of hydrophobic BNNS in enhancing the corrosion resistance of metallic surfaces. The corrosion resistance of metallic substrates was assessed by applying the BNNS-based coatings and subjecting them to a series of electrochemical tests and salt spray testing. The key findings of this research demonstrate a marked improvement in the corrosion resistance of metallic surfaces post-coating with hydrophobic BNNS. The hydrophobic nature of the BNNS exhibited a significant increase in hydrophobicity post-coating. Electrochemical tests revealed a positive shift in the corrosion potential and a reduction in the corrosion current density, signifying a diminished corrosion rate. By reducing the interaction between water and metal, the BNNS coatings act as a physical barrier, thereby hindering the electrochemical processes that precipitate corrosion. This study offers valuable insights into the development of advanced nanomaterial-based coatings for corrosion protection, with potential applications across various sectors, including aerospace, automotive, and civil infrastructure. © 2024, The Authors. All rights reserved.

关键词： Corrosion resistance

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Radar Signal Detection Based on Ambiguity Function and Deep Learning 2

Radar Signal Detection Based on Ambiguity Function and Deep ...

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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Lv, Fengrong Dong, Zeyu Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

The ambiguity function describes the joint characteristics of the signal in the time domain and the frequency domain, and is usually used for signal recognition. The time domain and frequency domain distribution of noise is more spurious than the signal. Its ambiguity function can also reflect its characteristics. However, the direct use of the ambiguity function as the signal feature will increase the amount of calculation of the detection system, so slice it, which reduces the burden on the system for detecting signal information while preserving the information. At the same time, the radar signal detection based on neural network can avoid the influence of artificially setting the threshold on the detection performance of the system. So, we propose an algorithm for inputting the extracted fuzzy function slice sequence into a neural network to realize signal detection. simulation proves that when the signal-To-noise ratio of the received signal is very low, our proposed method still has a high detection probability. © 2021 IEEE.

关键词： Signal detection

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Explainable Machine-Learning Optimization of H-BN Nanosheets with Surface Defects for Enhanced Hydrophobicity

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SSRN 2024年

作者： Cheng, Ming Li, Wen Wei, Qi Dun, Yuchao Chang, Wei Liu, Zeyu Jin, Lei Wei, Guoke Aviation Key Laboratory of Science and Technology on Advanced Surface Engineering AVIC Manufacturing Technology Institute Beijing100024 China Science and Technology on Power Beam Processes Laboratory AVIC Manufacturing Technology Institute Beijing100024 China Technology Research Center Liyang Aero Power Co. LTD. AECC Guiyang550014 China

Metal corrosion incurs substantial economic and safety costs in industry, necessitating effective protective materials. Hexagonal boron nitride (h-BN) nanosheets, with their chemical stability and hydrophobicity, are an ideal choice for metal surface protection. However, optimizing their hydrophobic properties remains challenging. This study introduces an explainable AI-driven machine learning model to explore the impact of synthesis variables like temperature, heating time, and additive ratio on h-BN nanosheets' hydrophobicity. The model, with 82% accuracy, identified key variables and their nonlinear relationships, optimizing the nanosheets' hydrophobicity. By evaluating 687,500 conditions, AI-selected strategies significantly enhanced hydrophobicity, verified experimentally. This research underscores AI's potential in materials science, offering a new approach to developing advanced metal protective materials with theoretical and practical implications. © 2024, The Authors. All rights reserved.

关键词： Boron nitride

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Explainable Machine-Learning Optimization of H-Bn Nanosheets with Surface Defects for Enhanced Hydrophobicity

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SSRN 2024年

关键词： Hydrophobicity

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Cooperative jamming resource allocation based on integer-encoded directed mutation artificial bee colony algorithm 4

Cooperative jamming resource allocation based on integer-enc...

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4th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2021

作者： Xia, Jiechen Ma, Jing Li, Yibing Song, Mingzhao Harbin Engineering University Harbin150001 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Science and Technology on Special System Simulation Laboratory Beijing100854 China

ISBN: (纸本)9781665432030

Electromagnetic countermeasure (ECM) is of extreme importance in modern warfare. In order to confront the threat of radar-net, cooperative jamming platform with multiple jammers is the main approach. A proper allocation of jamming resource is required before and during the process of interference. This paper proposes an artificial bee colony (ABC) based jamming resource allocation (JRA) algorithm with few parameter adjustments. The allocation strategy is encoded in integer to better handle the constraints of JRA problem. Furthermore, a genetic algorithm (GA) inspired solution update method is introduced in stages of algorithm to accelerate the convergence rate. simulation result shows that the proposed algorithm has a better performance in both rate and precision of convergence compared with tabu search artificial bee colony algorithm (TSABC) and ant colony optimization algorithm (ACO), which were adopted in previous related studies. ©2021 IEEE

关键词： Tabu search

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Compensation method of GPS signal delay based on factor graph 4

Compensation method of GPS signal delay based on factor grap...

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4th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2021

作者： Chen, Hangyu Ma, Jing Ye, Fang Harbin Engineering University Harbin150001 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Science and Technology on Special System Simulation Laboratory Beijing100854 China

ISBN: (纸本)9781665432030

In recent years, unmanned ground vehicles (UGVs) have been widely used in urban environments. The satellite positioning system plays an irreplaceable role in UGVs. However, the tall buildings in cities may cause interference to the transmission of satellite signals, which results in positioning delays, thus reducing the positioning accuracy of UGVs. To address this issue, a compensation method for information delay based on factor graph model is proposed in this paper. In the factor graph model utilized, the corresponding GPS factor node will not be generated when the GPS signal delay occurs at the current fusion time. The subsequent factor graph model is directly generated by the combined navigation system of visual odometry (VO) and inertial measurement unit (IMU). When the delayed GPS signal arrives, the measurement data of VO and IMU are used to compensate the delayed GPS positioning information. The compensated GPS positioning information is used to generate an additional factor node at the moment when the GPS signal actually arrives. This additional factor node is connected into the factor graph model for data fusion so that the delayed GPS positioning information can still be used to correct the positioning error. The method proposed in this paper effectively reduces the positioning error while taking into account the real-time performance. Experimental simulations show that the proposed method can reduce the positioning error while GPS signal delay occurs. ©2021 IEEE

关键词： Global positioning system

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Effect of stress loading direction on microstructure evolution and age-hardening behavior of a stress-aged Mg-7Sn alloy

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Journal of Alloys and Compounds 2025年 1032卷

作者： Jiang, Jing Ran, Jishang Tong, Lin Bi, Guangli Li, Yuandong Chen, Tijun State Key Laboratory of Advanced Processing and Recycling of Nonferrous Metals Lanzhou University of Technology Lanzhou730050 China School of Material Science and Engineering Lanzhou University of Technology Lanzhou730050 China AVIC Shaanxi Hongyuan Aviation Forging Company Ltd. Xianyang713801 China

The effect of stress loading direction on microstructure evolution and age-hardening behavior of a stress-aged Mg-7Sn alloy with a compressed stress of 40 MPa at 160 °C was investigated in this paper. The compressive stress perpendicular to the c-axis effectively facilitated the formation of a high volume fraction of twins and Mg2Sn phases, thereby promoting a c-axis//ED texture. In contrast, the stress parallel to the c-axis resulted in the formation of small amounts of twins and Mg2Sn phases, which further reinforced the basal plane texture. The stress aging with compressive stress applied perpendicular to the c-axis significantly increased the peak hardness of the alloy and reduced the time reached the peak hardness, compared to compressive stress applied parallel to the c-axis. The compressive testing results indicated that the stress peak-aged alloy perpendicular to the c-axis exhibited excellent mechanical properties, whose compressive yield strength, ultimate compressive strength and compressive elongation were 191.3 MPa, 449.9 MPa and 12.6 %, respectively. The high compressive strengths of the peak-aged alloy at a compressive stress perpendicular to the c-axis was mainly attributed to the grain refinement and precipitation strengthening of Mg2Sn phase. © 2025 Elsevier B.V.

关键词： Microhardness

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