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Amorphous Carbon-Modulated Mg3(Bi,Sb)2 and Electron-Poor CdSb for Ultralow-Cost Te-Free Refrigeration Modules

advanced FUNCTIONAL MATERIALS 2025年第4期35卷

作者： Xu, Wenlong Al-Maythalony, Bassem A. Li, Jiao Li, Xiang Fu, Liangwei Xu, Biao Nanjing Univ Sci & Technol Sch Chem & Chem Engn Nanjing 210094 Peoples R China Royal Sci Soc Adv Res Ctr Mat Discovery Res Unit Amman 11941 Jordan

The rapid advancement of Internet of Things (IoT) technology and AI microchips has increased the demand for efficient and cost-effective cooling solutions. However, traditional Bi2Te3-based thermoelectric modules face the challenge of low abundance tellurium (Te). Although Te-free modules using MgAgSb have been explored, they still suffer from a low price-to-performance ratio. To address these issues, this study investigates the development of alternative thermoelectric materials that are both cost-effective and Te free. In this work, the potential of cost-effective Te-free alternatives is explored for thermoelectric applications by developing a high-performance module composed of amorphous carbon-modulated Mg-3(Bi,Sb)(2) and electron-poor CdSb. The modules of CdSb/Bi2Te3 and CdSb/Mg-3(Bi,Sb)(2) demonstrate superior refrigeration performance, achieving a maximum temperature difference (Delta T-max) of 49.2 and 46 K, respectively. Notably, the material cost of CdSb/Mg-3(Bi,Sb)(2) module is only 5.5% of Te-free modules built on MgAgSb, highlighting a significant economic advantage. This work provides a viable, ultralow-cost approach to meet general refrigeration needs, thereby enhancing the practical value and application potential of thermoelectric materials.

关键词： amorphous carbon electron-poor compound low cost refrigeration device Te-free material thermoelectric

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Multimodal Fabric Defect Classification Using Channel Switching and Multiscale Feature Fusion

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Li, Song Sun, Wei Liang, Qiaokang Sun, Jian Liu, Chongpei Hunan Univ Coll Elect & Informat Engn Natl Engn Res Ctr Robot Visual Percept & Control T Changsha Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Hunan Univ Coll Robot Changsha 410082 Peoples R China

Human perception relies on the important sensory modes of vision and touch, which provide complementary information about the surrounding environment. Robots can leverage this multimodal sensing capability. In this study, we propose a defect recognition and classification method based on multiscale and channel-switching fusion, integrating visual and tactile modalities to achieve superior performance. Defect features are extracted by processing tactile data from GelSight sensors and captured visual images through deep neural networks. However, due to the heterogeneity between the two modalities and the diversity in defect sizes and shapes, commonly used methods including feature map superposition or concatenation operations increase computational costs and reduce model classification efficiency. To address this challenge, we designed a channel-switching module and a multiscale fusion module. The channel-switching module assigns different weights to each channel in the feature map to solve the problem of mutual exclusivity or unbalanced fusion in traditional methods, while the multiscale fusion module effectively processes features of different shapes by merging features from different scales. Results obtained on a newly collected fabric dataset show that the proposed defect classification method improves classification accuracy compared to learning from single-modal data, with significant improvement in complex backgrounds. The proposed fusion network framework achieves robust defect classification performance exceeding 90%.

关键词： Fabrics Visualization Feature extraction Defect detection Sensors Cameras Tactile sensors Switches Surface treatment Accuracy Channel switching deep learning defect classification fabric defect detection visual-tactile fusion

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Grasp Stability Assessment Through Spatio-Temporal Attention Mechanism and Adaptive Gate Fusion

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IEEE SENSORS JOURNAL 2025年第1期25卷 1872-1884页

作者： Li, Song Sun, Wei Liang, Qiaokang Sun, Jian Liu, Chongpei Hunan Univ Coll Elect & Informat Engn Natl Engn Res Ctr Robot Visual Percept & Control T Changsha 410000 Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410000 Peoples R China Hunan Univ Coll Robot Changsha 410000 Peoples R China

In the field of robotic grasping and manipulation, accurately assessing the stability of handheld objects plays a critical role in achieving proficient manipulation. Methods relying solely on visual or tactile information for slip detection often have limited applicability across different scenarios. Relevant studies have shown that combining visual and tactile sensing can significantly improve grasping performance. This study proposes a novel deep neural network architecture, specifically adopting a spatiotemporal attention mechanism to fuse multilevel spatiotemporal features, effectively integrating deep high-level features with shallow low-level features. It extracts important slip features across temporal and spatial dimensions from both visual RGB image sequences and tactile image sequences, thereby facilitating stability prediction. The gating mechanism builds a resilient network architecture that adaptively fuses features with appropriate weights, maintaining highly accurate and robust predictive performance even when sensor signal quality degrades. Validation results from both public and custom datasets demonstrate that the proposed model is highly effective in accurately predicting grasp stability, even in the presence of missing, occluded, noisy, or corrupted visual or tactile sensor signals. The practicality of this approach extends to various downstream applications in robotics, including grasp force control, generation of grasping strategies, and proficient manipulation in challenging scenarios.

关键词： Visualization Adaptation models Attention mechanisms Grasping Logic gates Robot sensing systems Feature extraction Stability analysis Spatiotemporal phenomena Sensors Grasp outcomes assessment multimodal fusion slip detection tactile sensing visual-tactile perception

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Two-Step Deep Learning Approach for Estimating Vegetation Backscatter: A Case Study of Soybean Fields

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REMOTE SENSING 2025年第1期17卷 41-41页

作者： Zhu, Dong Zhao, Peng Zhao, Qiang Li, Qingliang Zhang, Jinpeng Yang, Lixia Anhui Univ Informat Mat & Intelligent Sensing Lab Anhui Prov Hefei 230601 Peoples R China China Res Inst Radiowave Propagat Natl Key Lab Electromagnet Environm Qingdao 266108 Peoples R China

Precisely predicting vegetation backscatter involves various challenges, such as complex vegetation structure, soil-vegetation interaction, and data availability. Deep learning (DL) works as a powerful tool to analyze complex data and approximate the nonlinear relationship between variables, thus exhibiting potential applications in microwave scattering problems. However, few DL-based approaches have been developed to reproduce vegetation backscatters owing to the lack of acquiring a large amount of training data. Motivated by a relatively accurate single-scattering radiative transfer model (SS-RTM) and radar measurements, we, for the first time to our knowledge, introduce a transfer learning (TL)-based approach to estimate the radar backscatter of vegetation canopy in the case of soybean fields. The proposed approach consists of two steps. In the first step, a simulated dataset was generated by the SS-RTM. Then, we pre-trained two baseline networks, namely, a deep neural network (DNN) and long short-term memory network (LSTM), using the simulated dataset. In the second step, limited measured data were utilized to fine-tune the previously pre-trained networks on the basis of TL strategy. Extensive experiments, conducted on both simulated data and in situ measurements, revealed that the proposed two-step TL-based approach yields a significantly better and more robust performance than SS-RTM and other DL schemes, indicating the feasibility of such an approach in estimating vegetation backscatters. All these outcomes provide a new path for addressing complex microwave scattering problems.

关键词： backscattering coefficient radiative transfer model soybean field transfer learning deep neural network long short-term memory network

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Integrating Pt single atoms and Mo into PtNi/C through Mo doping-displacement synchronisation strategy for enhanced HER at all pH values

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FUEL 2025年 381卷

作者： Zhang, Chao Liu, Qian Ming, Shujun Wang, Chao Lv, Zhiguo Zhuang, Tao Qingdao Univ Sci & Technol Coll Chem Engn State Key Lab Base Ecochem Engn Key Lab Multiphase Flow React & Separat Engn Shand Qingdao 266042 Peoples R China Huanggang Normal Univ Sch Chem & Chem Engn Hubei Key Lab Proc & Applicat Catalyt Mat Huanggang 438000 Peoples R China Wuhan Univ Technol State Key Lab Adv Technol Mat Synth & Proc Wuhan 430070 Peoples R China Qingdao Univ Sci & Technol Key Lab Rubber Plast Shandong Prov Key Lab Rubber plast Minist Educ Qingdao 266042 Peoples R China

This paper proposes a Mo doping-displacement synchronization strategy to integrate Pt SAs and Mo atoms into PtNi/C, synthesizing Pt SAs/Mo-doped PtNi octahedra/carbon support catalyst (Pt SAs/Mo-PtNi/C). In this approach, Mo atoms are doped into PtNi alloy octahedra and displace some Pt atoms, forming Mo-PtNi octahedra. Importantly, the substituted Pt atoms can adhere to carbon substrate, creating Pt SAs. Pt SAs/Mo-PtNi/C exhibits lower overpotentials (38, 59, and 110 mV at 10 mA cm(-2) ) and smaller Tafel slopes (44, 51, and 139 mV dec-1) in acidic, alkaline, and neutral environments. Additionally, the electron pathway of Mo-PtNi -> Pt SAs/C has been confirmed, and Pt SAs/Mo-PtNi/C exhibits an optimized hydrogen adsorption energy (Delta GH*=-0.29 eV). Furthermore, catalyzed by Pt SAs/Mo-PtNi/C, the H-O bond length of H2O extends to 1.11 angstrom and the bond angle reduces to 102.741 degrees, directly confirming that the Pt SAs and doped Mo could facilitate H-O bond breaking. The proposed Mo doping-displacement synchronization strategy not only simplifies the fabrication process of Pt SAs catalyst, but also improves its durability and activity across a wide pH range, thereby potentially advancing hydrogen production technologies.

关键词： Pt single atoms Mo PtNi alloy HER Synchronisation strategy

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A Deep Investigation on Stealthy DVFS Fault Injection Attacks at DNN Hardware Accelerators

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2025年第1期44卷 39-51页

作者： Xu, Junge Zhang, Fan Jin, Wenguang Yang, Kun Wang, Zeke Jiang, Weixiong Ha, Yajun Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310027 Peoples R China Zhengzhou Xinda Inst Adv Technol Zhengzhou 450001 Peoples R China ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

With increasing computation of various applications, dynamic voltage and frequency scaling (DVFS) is gradually deployed on FPGAs to improve performance and save energy. However, its reliability and security have not been sufficiently evaluated, which incurs quite many concerns. In this article, we propose an evaluation framework for deep investigation of stealthy DVFS fault injection attacks on the state-of-the-art deep neural networks (DNNs) deployed on modern FPGAs. The evaluation framework mainly consists of a DVFS attack striker and a time-to-digital converter (TDC)-based hardware profiler. Two modes of evaluation are derived, and their effectiveness is demonstrated on a platform composed of a SkyNet accelerator and three ImageNet models built on a Xilinx deep learning processor unit (DPU). Experimental results show that more than 99% detection accuracy loss can be measured targeting at all tested DNN models under prospective operation mode but without any performance degradation in frame per second (FPS). In our investigation of sensitive layer mode, more than 93% average accuracy loss with 84.7% fault probability can be measured on a single bundle of the SkyNet. We characterize the vulnerabilities of different DNN layers subject to DVFS attacks through leveraging the TDC-based hardware profiler to precisely control the timing of fault injection.

关键词： Circuit faults Field programmable gate arrays Artificial neural networks Voltage control Hardware acceleration Deep learning Energy efficiency Deep learning accelerator dynamic voltage and frequency scaling (DVFS) fault injection attack image recognition time-to-digital converter (TDC)

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Distributed photovoltaic power fluctuation flattening strategy based on hybrid energy storage

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FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Chen, Haoyu Cheng, Jiangzhou Li, Zhenhua Abu-Siada, A. Li, Hongbin Three Gorges Univ Coll Elect Engn & New Energy Yichang Peoples R China Curtin Univ Dept Elect & Comp Engn Perth WA Australia State Key Lab Adv Electromagnet Engn & Technol Wuhan Peoples R China

Aiming at mitigating the fluctuation of distributed photovoltaic power generation, a segmented compensation strategy based on the improved seagull algorithm is proposed in this paper. In this regard, a hybrid energy storage system comprising a lithium battery and supercapacitor is utilized. The internal power distribution of the hybrid energy storage system is adjusted using wavelet packet decomposition, and the state of charge is employed to adapt the primary power distribution. The start and end times for charging and discharging are determined by combining the time of use, electricity price, state-of-charge information, and load size at night to realize the economic operation of the system. The opposing search operator strategy and mutation operation are used to improve the seagull algorithm, optimize the controller parameters of the DC/DC converter, and improve its response time. Combined with the historical measured data of a distributed photovoltaic in Hubei Province, simulation results show that the proposed strategy can effectively smoothen the fluctuation of distributed photovoltaic generated power while reducing the charging and discharging frequencies of the energy storage system, hence improving its stability and service life.

关键词： distributed photovoltaic power fluctuation hybrid energy storage segmentation compensation policy seagull algorithm

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Research on Online Compensation of Electronic Transformer Based on Ensemble Learning Stacking Algorithm 18th

Research on Online Compensation of Electronic Transformer Ba...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Li, Zhenhua Yang, Xinqiang Li, Hongbin Li, Zhenxin Gong, Xiaoyu College of Electrical Engineering and New Energy China Three Gorges University YiChang443002 China State Key Laboratory of Strong Electromagnetic Engineering and New Technology Huazhong Universityof Science and Technology Wuhan430074 China School of Economics and Management China Three Gorges University Yichang443002 China

ISBN: (纸本)9789819714469

The electronic transformer is affected by factors such as running time and environment, and the error performance in the long-term operation process is not stable enough to cause inaccurate energy measurement. This paper proposes an online error compensation method for electronic transformers based on Stacking integration algorithm. Firstly, the mutual information (MI) coefficient is used to reduce the dimension of the original feature set to obtain the optimal correlation feature set. Then, the high correlation features are used as the input of the model, and the K-fold (KF) cross-validation method is used to train each sub-model. Finally, the real-time error of the transformer is predicted and the error of the transformer is calibrated online. The example analysis shows that the prediction loss of the proposed method is less than 5 %, which is applied to the output compensation of the secondary end of the 0.2 stage transformer, so that the measurement accuracy of the transformer is improved to 0.1. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Error compensation

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Control of Variable Speed Pumped Storage Unit Based on Power Electronic Transformer Under Unbalance of Power Grid Voltage 27

Control of Variable Speed Pumped Storage Unit Based on Power...

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27th International Conference on Electrical Machines and Systems, ICEMS 2024

作者： Huang, Pei Peng, Xiang Dian, Renjun School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan China

ISBN: (纸本)9784886864406

To enhance the power density and improve the grid-connection capability of the variable-speed pumped storage unit, this paper proposes a topology for full-power variable-speed pumped storage based on power electronic transformer. This topology does not require a power frequency transformer and can isolate the double frequency fluctuation of the high-voltage DC bus voltage in the event of asymmetric faults in the grid, so as not to affect the control of the motor side and improve the unit's ability to adapt to the power grid. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Power grids

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Quasi-distributed optical fiber sensing for the coupled vibration analysis of high-speed train-bridge coupled system under earthquakes

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SENSORS AND ACTUATORS A-PHYSICAL 2024年 374卷

作者： Xiang, Ping Xie, Xiaonan Zhang, Xuebing Wu, Han Chen, Zhizhan Wang, Li Liu, Xiaochun Yang, Delei Wang, Huaping Cent South Univ Sch Civil Engn Changsha 410075 Hunan Peoples R China Xiangtan Univ Coll Civil Engn Xiangtan 411105 Hunan Peoples R China Univ Huanghuai Dept Bldg Engn 6 Kaiyuan Rd Zhumadian Henan Peoples R China Lanzhou Univ Sch Civil Engn & Mech Lanzhou Peoples R China City Univ Hong Kong Depsrtment Civil & Architectural Engn Hong Kong Peoples R China

Due to the extensive construction of high-speed rail lines passing through seismically active areas, the possibility of a sudden earthquake occurring during train operation is very high. Additionally, the earthquake will intensify the dynamic response of trains and bridges, causing serious bridge damage. In this work, the dynamic response behavior of the bridge structures in the coupled train-bridge system under the earthquake is investigated based on the 4-table shaking table system. Shaking table experiments are also conducted on a high-speed railroad model of simple-supported girder bridge at a scale of 1/10 with the simulated layers of China Railway Track System type II (CRTS II) ballastless track slabs. The strain responses of various components, including rails, track plates, base plates, and beams, were measured on the bridge using quasi-distributed fiber optic gratings, both with and without seismic actions. Additionally, the seismic isolation characteristics of the fasteners and the CA mortar layer were investigated. The dynamic performance of the coupled train-bridge system under earthquakes was studied in both the time and frequency domains.

关键词： Train-bridge system Earthquake Dynamics performances Frequency Quasi-distributed fiber Bragg grating

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