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Enhancing the reactivity and combustion efficiency of Al@AP by precise catalysis of MoO3-x quantum dots with oxygen vacancy

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Journal of Analytical and Applied Pyrolysis 2025年 190卷

作者： Li, Xin Xu, Ruixuan Zhang, Hao Deng, Heng Yan, Qi-Long Nie, Hongqi National Key Laboratory of Solid Propulsion Northwestern Polytechnical University Xi'an710072 China National Key Laboratory of Land and Air Based Information Perception and Control Xi'an Modern Control Technology Research Institute Xi'an710065 China

Aluminum (Al) can significantly improve the energy density and specific impulse (Isp) of solid rocket propellants as the primary metal fuel, but its incomplete combustion results in an undesirable energy release performance. The strategy of fuel/oxidizer interfacial control has been proved to effectively enhance the reaction efficiency of Al-based composites and thus improving the combustion properties of solid propellants. Ammonium perchlorate (AP) is commonly used as a high-energy oxidizer in solid propellant, and its thermal decomposition behavior directly affects the combustion characteristics of propellants. The addition of combustion catalysts can decrease thermal decomposition temperature and increase thermal reactivity of AP. As an emerging catalytic material, MoO3-x quantum dots (QDs) with oxygen vacancies possess a high specific surface and strong charge adsorption capacity, which renders it a great potential for catalyzing AP. In this study, MoO3-x QDs were introduced as catalyst and compared with traditional nano-metal oxides (MxOy), the spherical Al@AP/MxOy composites with polydopamine as interfacial layer were prepared by spray drying method. The particle morphology, thermal decomposition kinetics and ignition properties of Al@AP/MxOy were investigated. The phase composition, morphology and particle size distribution for the condensed combustion products of composites were further analyzed. The decreased particle size and less unreacted Al content in CCPs indicated the increase of combustion efficiency between Al and AP. In particular, Al@AP/MoO3-x has the higher heat of reaction, lower thermal decomposition temperature and small CCPs particle size distribution, which collectively suggested that the MoO3-x is capable to improve the thermal reactivity of Al@AP composites with a higher combustion efficiency. © 2025 Elsevier B.V.

关键词： Nanocrystals

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Structure design and analysis of a rigid-soft robotic hand with large load capacity 3

Structure design and analysis of a rigid-soft robotic hand w...

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3rd International Conference on Electrical, Electronics, and Information Engineering, EEIE 2024

作者： Wu, Peichen Lan, Fuming Hong, Wen Chen, Xiaoping Shuai, Wei Cui, Guowei Gao, Yang Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Shanghai Institute of Aerospace System Engineering Shanghai201100 China Intelligent Manufacturing Institute of HFUT HeFei230041 China School of Computer Science and Technology University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9781510688179

In recent years, soft grippers have gained significant attention due to their adaptability and safety. However, when performing horizontal object grasping, their limited structural stiffness prevents them from withstanding the torque generated by friction between the gripper and the object, leading to a loss of contact and limiting their horizontal load capacity. To address this limitation while preserving the adaptability of soft grippers, this paper proposes a gripper structure called the rigid-soft robotic hand, which incorporates lateral rigid connecting rods outside the soft joints. The paper analyzes the bending capacity of the rigid-soft joint using kinematic methods and investigates the influence of link design parameters on maximum bending angle. Subsequently, a finite element analysis is conducted to study the finger structure with the added connecting rods, aiming to optimize the link design parameters. Experimental results demonstrate the grasping capabilities of the rigid-soft gripper in both vertical and horizontal orientations. The findings show that the rigid-soft gripper significantly improves the load-carrying capacity during horizontal object grasping while maintaining the adaptability of the soft gripper. © The Authors.

关键词： Robotic arms

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Load Balancing Routing Algorithm for LEO Satellite Networks Based on Ant Colony Optimization

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Internet technology Letters 2025年第3期8卷

作者： Zhi, Ruxin Wang, Jiahui Xu, Zhan Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

To address the problem of the unbalanced load and optimize the traffic distribution of large-scale low earth orbit (LEO) satellite networks, this paper proposes a load-balancing routing algorithm for LEO satellite networks based on ant colony optimization. The algorithm establishes the global optimal initial path through the improved ant colony algorithm to bypass the network bottleneck, makes local adjustments to cope with burst traffic changes to avoid congestion, and optimizes the "inferior" paths through regular rerouting to improve the overall network performance. The results show that the algorithm performs well in terms of packet loss rate, throughput, and load balancing, which can effectively alleviate the link utilization imbalance problem and provide a more stable and efficient service for the satellite network. Among them, the packet loss rate is reduced by 7.8%, and the load distribution index is improved by 30%. © 2025 The Author(s). Internet technology Letters published by John Wiley & Sons Ltd.

关键词： Ant colony optimization

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Investigation on machining mechanism and surface integrity of Sip/Al composites with ultrasonic vibration-assisted epoxy coating cutting

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Journal of Manufacturing Processes 2025年 146卷 427-444页

作者： Chen, Dachuan Zheng, Zhengding Ding, Jixiang Zhang, Jianguo Chen, Xiao Xiao, Junfeng Xu, Jianfeng State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Key Laboratory of Modern Manufacturing Quality Engineering in Hubei Province Hubei University of Technology Wuhan430068 China

Due to the significant mechanical differences between the plastic Al matrix and the brittle Si particles, the ultra-precision machining of Sip/Al composites is considered a major challenge. To overcome this challenge, this paper proposes a new cutting strategy, namely ultrasonic vibration-assisted epoxy coating cutting (UV-ECC). By analyzing the groove morphology, cutting force, chip morphology, residual stress, and surface roughness, the effect of UV-ECC on the machining mechanism and surface integrity of Sip/Al composites is investigated. Research results indicate that epoxy coating can provide compressive stress to the surface of Sip/Al composites, thereby suppressing the formation and propagation of cracks as well as the pull-out or rotation of particles. After the introduction of ultrasonic vibration, the vibrating tool can compensate for the shortcomings of the epoxy coating in terms of chip removal. Furthermore, the intermittent separation reduces the damage to both the Sip/Al composites and the epoxy coating. Finally, the space gap created by the elliptical trajectory allows the crack suppression effect of the epoxy coating to be seen as a significant improvement. Overall, compared to traditional cutting and epoxy coating cutting, UV-ECC offers significant advantages in enhancing surface integrity, reducing specific cutting force, and achieving a uniform residual stress distribution. Among them, the surface roughness decreased by 75.4 % and 59.0 %, respectively, and the specific cutting force decreased by 75.01 % and 64.89 %, respectively. The current research provides a promising cutting strategy for achieving efficient and low-damage machining of Sip/Al composites. © 2025 The Society of Manufacturing Engineers

关键词： Ultrasonic cutting

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Design and characterization study of dual D-shaped no-core fiber based SPR sensor for refractive index and temperature measurement

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Optoelectronics Letters 2025年

作者： Liu Yinggang Li Rui Li Fei Xu Xinyi Zhou Rui Shaanxi Engineering Research Center of Oil and Gas Resource Optical Fiber Detection & Shaanxi Key Laboratory of Measurement and Control Technology for Oil and Gas wells， Xi'an Shiyou University

To address the issue of temperature cross-sensitivity in refractive index （RI） measurement， a fiber-optic Surface Plasmon Resonance （SPR） sensor based on dual D-shaped no-core fiber （NCF） is proposed and designed. The sensor mainly consists of D-shaped NCF， Ag/Fe2O3composite film， and polydimethylsiloxane （PDMS）， where the silver and Fe2O3are successively coated on both D-shaped surfaces of NCF to generate SPR and enhance the oxidation resistance. The layer of PDMS coated on one D-shaped surface acts as a tunable ambient medium sensing the temperature variation and affecting the transmission spectrum of the sensor. Since the surface plasmon waves are excited in the two D-shaped surfaces with different films， the two RI and temperature-dependent spectral resonance peaks with different wavelengths will be produced. Research results demonstrate that the two peaks’ wavelengths have different responses to the variations of ambient RI and temperature. In the refractive index range of 1.36-1.376 and temperature range of 10-100 °C， the RI and temperature sensitivities reach to 5000 nm/RIU and -0.546 nm/°C， respectively. With the sensitivity coefficient matrix， simultaneous measurement of refractive index and temperature can be realized， and the corresponding accuracy is superior to 0.4×10-5RIU and 0.037°C.

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Density characterization of hydrogen-blended natural gas system by a single-sinker densimeter for future hydrogen economy

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International Journal of Hydrogen Energy 2025年 135卷 507-514页

作者： Lin, Qingjin Zhang, Pu Zhou, Li Zhang, Peiying Sheng, Bowen Gong, Maoqiong Research Institute of Natural Gas Technology PetroChina Southwest Oil & Gasfield Company Sichuan Chengdu610213 China Key Laboratory of Natural Gas Quality Control and Energy Measurement State Administration for Market Regulation Sichuan Chengdu610213 China Key Laboratory of Natural Gas Quality Control and Energy Measurement CNPC Sichuan Chengdu610213 China State Key Laboratory of Cryogenic Science and Technology Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing100190 China

Hydrogen-blended natural gas (HNG) has emerged as a promising energy carrier for hydrogen transportation and carbon emission reduction. Precise determination of thermophysical properties in HNG mixtures is critical for optimizing the design of storage infrastructure, pipeline networks, and end-use applications. This work investigated the density of Chinese natural gas blended with hydrogen (3–20 %) using a single-sinker densimeter across temperatures (253.15 K–350.15 K), with pressures up to 10 MPa. Experimental results have been compared with predictions from three equations of state (EoSs), including GERG-2008, AGA8-DC92, and PR. The GERG-2008 and AGA8-DC92 EoSs remained better than 0.10 % and 0.11 % of average absolute relative deviation (AARD), respectively, and the AARD of PR EoS exceeds 2.13 %. It demonstrated superior accuracy of GERG-2008 and AGA8-DC92 EoSs for the hydrogen-blended natural gas mixture with 3–20 % H2 compared to the PR EoS. However, GERG-2008 EoS exhibited a relative deviation of 0.16 % at 3 MPa. Pressure dependence analysis revealed no similar trend in relative deviations for all mixtures as increasing pressure. Blending hydrogen resulted in a larger discreteness of the relative deviation at different temperatures between the calculated values from the GERG-2008 and AGA8-DC92 EoSs and the experimental ones. Thus, the mixing rule model in the equations of state may be improved while applied to hydrogen-blended natural gas mixtures. © 2025 Hydrogen Energy Publications LLC

关键词： Natural gas transportation

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Microwave Photonics-Based Small Hydrostatic Pressure Sensing Assisted by Convolutional Neural Network

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IEEE Sensors Journal 2025年

作者： Li, Songlin Xue, Ting Wu, Yan Li, Zhuping Wu, Bin Tianjin University Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin300072 China Tianjin University State Key Laboratory of Precision Measuring Technology and Instruments Tianjin300072 China

Hydrostatic pressure measurement is essential in many industries, such as oil and gas production, chemical processing, and environmental monitoring. Due to the minimal impact of small hydrostatic pressure on ordinary silica optical fibers, research on its measurement utilizing optical fiber sensing technology remains limited. In this paper, a novel microwave photonics technique, termed optical carrier-based microwave interferometry (OCMI), is utilized for small hydrostatic pressure sensing with the assistance of a convolutional neural network (CNN). The theory of OCMI-based phase demodulation is established, and numerical simulations are conducted to investigate the factors affecting the axial displacement of the fiber core. In practical experiments, the phase demodulation method is applied to small hydrostatic pressure measurements;however, the results are suboptimal. Therefore, the CNN is developed to assist in the implementation of accurate small hydrostatic pressure sensing. The small hydrostatic pressures predicted by the well-trained CNN model are in good agreement with the actual values, with an error of less than 0.25 kPa. In addition, the prediction results from multiple Fabry-Perot interferometers demonstrate the feasibility and effectiveness of utilizing CNN for OCMI-based small hydrostatic pressure sensing. The introduction of machine learning broadens the application scope of the OCMI technique, allowing it to be employed for distributed sensing of a wider range of physical, chemical, and biological quantities. © 2001-2012 IEEE.

关键词： Interferometry

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MorNet: Asymmetric UNet-like Network with Morphological Opening and Closing for Image Segmentation 17th

MorNet: Asymmetric UNet-like Network with Morphological Open...

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Li, Meng Yun, Juntong Jiang, Du Tao, Bo Li, Gongfa Liu, Rong Liu, Ying Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China School of Medicine Wuhan University of Science and Technology No. 1 Huangjia Lake University Town Wuhan430065 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

Image segmentation plays a crucial role in target recognition as it provides an essential prerequisite for identifying targets. However, UNet cannot acquire comprehensive information about the image, which limits its ability to effectively segment small and discrete objects. A new network structure, called MorNet, is proposed. It applies dilation and erosion operations in morphological opening and closing for connected and discrete region segmentation. MorNet effectively integrates global segmentation images, emphasizing small and discrete area segmentation and enhancing the segmentation of large continuous areas. This method enhances the understanding of the location of organs and diseased sites, enabling accurate segmentation. A side-out (SO) monitoring mechanism is introduced into the decoder to provide monitoring information for the original image and the predicted results. Compared with current UNet-like networks, our proposed method achieved the highest Dice scores (96.4635%, 94.0514%, 94.3444%) and PPV scores (94.2226%, 90.2361%, 91.5582%) for liver tumor, brain tumor, and liver segmentation tasks, respectively. The experimental results show that MorNet successfully combines the segmentation of connected and discrete regions. MorNet locates organs and lesions more accurately than current state-of-the-art medical image segmentation models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Integrating 3-D Deep Learning for Hand Point Cloud Segmentation to Enhance Biosensor-Based Human–Computer Interaction

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IEEE Sensors Journal 2025年第9期25卷 15307-15316页

作者： Xing, Zhizhong Meng, Zhijun Zheng, Gengfeng Yang, Lin Guo, Xiaojun Chen, Shaochun Kunming Medical University School of Rehabilitation Kunming650500 China North Sichuan Medical College Medical Imaging Key Laboratory of Sichuan Province Nanchong637000 China Fujian Special Equipment Inspection and Research Institute Fujian Key Laboratory of Special Intelligent Equipment Safety Measurement and Control Fuzhou350008 China Xi’an Jiaotong University School of Mechanical Engineering Xi’an710049 China Xi’an Aerospace Automation Company Ltd. Xi’an710065 China South China University of Technology School of Mechanical and Automotive Engineering Guangzhou510641 China

Against the dual backdrop of normalized pandemic prevention and control measures and the intensification of population aging, the demand for noncontact hand function intelligent rehabilitation is becoming increasingly urgent. With the rapid development of virtual reality and human-computer interaction, accurate gesture posture perception is key to achieving intelligent rehabilitation systems. We propose a segmentation method based on 3-D deep learning and laser point clouds, where the hand point cloud segmentation network (HPCSN) can directly process point cloud data. The HPCSN innovatively integrates local aggregation, dimensional abstraction enhancement, and disorder handling of 3-D hand point cloud information, and has demonstrated excellent performance in comparative experiments with cutting-edge models. Our achievement is not only of great significance for improving the personalization and interest of rehabilitation training, but also provides a new technological path for hand function rehabilitation in an aging society, especially showing tremendous potential in remote medical care and intelligent monitoring applications. Our research provides a scientific basis for the future development of new types of biosensors and electronic devices, which is expected to be applied in various fields such as biomedical diagnosis and rehabilitation robots. © 2001-2012 IEEE.

关键词： Diagnosis

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