检索结果-内蒙古大学图书馆

Effect of alumina fibers on microstructure and mechanical properties of composite enamel coatings

Ceramics International 2025年第14期51卷 18865-18876页

作者： Chen, Xueying Guo, Yan Gao, Xinrui Shi, Shiyan Sun, Dongguang Jia, Xiaoyun Jiang, Weizhong Luo, Lida Wang, Qingwei State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Shanghai201620 China Engineering Research Center of Advanced Glass Manufacturing Technology Ministry of Education Donghua University Shanghai201620 China Key Laboratory of Special Glass and Enamel for China Light Industry Donghua University Shanghai201620 China Qingdao Haier Intelligent Cooking Appliances Co. Ltd China

Glass enamel coatings are widely used to protect metal against corrosion and weathering due to their exceptional chemical stability. However, the application potential of enamel coatings will be further enhanced if their mechanical properties, particularly impact resistance and toughness, can be improved. In this study, we investigated the influence of varying amounts of alumina fibers on the microstructure, phase composition, and mechanical properties of enamel coatings by fabricating composite enamel coatings. The impact strength, hardness and modulus of the resulting materials were evaluated by falling ball impact tests and nanoindentation tests. The results showed that the alumina fibers were well bonded to the enamel matrix, and the coating surface roughness and contact angle increased with fiber addition. The coating had the lowest porosity and best impact resistance at 0.5 wt% fiber addition. At this point, the modulus and hardness of the composite enamel coating demonstrated improved stability, with the overall hardness reaching its maximum value, and excessive addition of alumina fibers can lead to a reduction in coating performance. As a result, the alumina fibers appear feasible to use as reinforcing material to produce high performance composite enamel coatings. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Rockwell hardness

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Golden Jackal Optimization Algorithm for Mobile robotic Path Planning

An Adaptive Golden Jackal Optimization Algorithm for Mobile ...

引用

2024 International Conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Chen, Siwen Zheng, Xiujuan Shanghai United Imaging Healthcare Co. Ltd. Shanghai China Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Given the shortcomings of the traditional Golden Jackal Optimization (GJO) algorithm, including limited accuracy and slow convergence speed in solving mobile robot path planning problems, an improved adaptive Golden Jackal Optimization (IAGJO) method is proposed. Firstly, a nonlinear adaptive energy strategy is presented to adjust the energy decay pattern, balancing global and local search. Secondly, an enhanced position update mechanism based on Cauchy and Gaussian mutation increases population diversity and guide the search based on optimal individuals, thereby facilitating efficient exploration of unknown regions and avoiding local optima. Finally, the IAGJO algorithm is applied to mobile robot path planning (MRPP), demonstrating that the IAGJO achieves shorter path lengths and higher search efficiency, exhibiting significant advantages over existing methods. © 2025 SPIE.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Targeted-tuning competitive acidic CO2RR via metalloid antagonism sites

引用

Materials Today 2025年 83卷 54-63页

作者： Sheng, Beibei Cao, Dengfeng Qi, Zhenghang Shou, Hongwei Xia, Yujian Su, Xiaozhi Chen, Shuangming Wu, Chuanqiang Liu, Hengjie Chimtali, Peter Joseph Chu, Yongheng Liu, Chongjing Wu, Xiaojun Song, Li National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience Key Laboratory of Precision and Intelligent Chemistry School of Nuclear Science and Technology University of Science and Technology of China Hefei230029 China SINOPEC Shanghai Research Institute of Petrochemical Technology Co. Ltd. Shanghai201208 China Engineering Laboratory of Chemical Resources Utilization in South Xinjiang of Xinjiang Production and Construction Corps College of Chemistry and Chemical Engineering Tarim University Alar843300 China School of Chemistry and Materials Science CAS Center for Excellence in Nanoscience and Synergetic Innovation of Quantum Information & Quantum Technology Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei230026 China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley CA94720 United States Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201204 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

To mitigate the high separation costs associated with conventional neutral/alkaline electrocatalysis for CO2 reduction reactions (CO2RR), acidic CO2RR offers economic advantages and improved efficiency in CO2 utilization. However, it typically involves the cleavage of M−H bonds at a relatively negative potential, leading to the predominant formation of H2 and poor HCOOH selectivity. Herein, we develop a facile solid-phase thermal diffusion approach to controllably synthesize a novel metalloid-metal single atom alloys (m-SAAs) electrocatalyst Te1Bi with unique metalloid antagonistic sites, thus enabling high-efficient acidic CO2-to-HCOOH conversion. Electrochemical test and operando synchrotron radiation multi-techniques (SRMS) characterization reveal that metalloid Te sites bring steric hindrance effect and blocks *H coupling. Furthermore, it actively adsorbs OH− species as a proton source, allowing for effective separation of protons and electrons in space. Thus, leading to enhanced hydrogenation in acidic CO2RR to produce HCOOH. The flow cell test results demonstrate that the carefully designed Te1Bi catalyst exhibits a milder reaction potential, along with higher HCOOH Faraday efficiency (∼94.5 %) and single-pass carbon efficiency (SPCE, ∼40 %) in acidic media. This work significantly expands the family of SAAs and offers a novel perspective to analyze the regulation of competitive reactions through site-specific modifications for industrial acidic CO2RR. © 2024 Elsevier Ltd

关键词： Synchrotron radiation

来源：评论

学校读者我要写书评

暂无评论

Finite-Time Consensus of Second-Order Multiagent Systems With Input Saturation via Hybrid Sliding-Mode Control

引用

IEEE Transactions on Automation Science and engineering 2025年 22卷 14623-14632页

作者： Jiang, Xiaowei Jiao, Ranran Li, Bo Zhang, Xianhe Yan, Huaicheng China University of Geosciences School of Automation Wuhan430079 China Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Anhui University of Finance and Economics School of Finance Bengbu233030 China Hubei Normal University School of Electrical Engineering and Automation Huangshi435002 China Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China

This paper addresses the finite-time consensus (FTC) issue for second-order multi-agent systems (MASs) with nonlinear disturbances. To tackle the challenges posed by increasingly complex communication environments, an innovative integral sliding-mode surface is designed using event-triggered control. Furthermore, the study explores communication constraints between the leader and followers, employing impulsive control to facilitate communication only at specific intervals. A novel hybrid integral sliding-mode control protocol is advanced for the second-order MASs, which effectively eliminates the "Zeno phenomenon" and notably reduces both communication frequency and energy consumption, thereby enhancing overall communication efficiency. Ultimately, the efficacy of the put forward protocol is verified through simulation examples including comparison experiment. © 2004-2012 IEEE.

关键词： Protocols Sliding mode control Event detection Multi-agent systems Costs Training Topology Switches Sufficient conditions Stability analysis

来源：评论

学校读者我要写书评

暂无评论

Out-of-Distribution Fault Diagnosis of Industrial Cyber-Physical Systems Based on Orthogonal Anchor Clustering With Adaptive Balance

IEEE Transactions on Industrial Cyber-Physical Systems

引用

IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 48-60页

作者： Liu, Ruonan Hu, Puyuan Zhao, Siheng Sun, Zhijian Han, Te Pang, Zhibo Zhang, Weidong Shanghai Jiao Tong University Department of Automation Shanghai200240 China National Key Laboratory of Marine Engine Science and Technology Shanghai201108 China Crossocean of Suzhou Technology Suzhou215121 China Beijing Institute of Technology Center for Energy and Environmental Policy Research School of Management Beijing100081 China ABB Corporate Research Sweden Department of Automation Technology Vasteras722 26 Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm114 28 Sweden Henan University Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Kaifeng475001 China Shanghai Jiaotong University Department of Automation Shanghai200240 China

Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS), ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural networks have demonstrated competitive results for intelligent fault diagnosis, which are usually trained via the historical data of all fault modes. However, in real engineering, it is usually difficult to collect samples and exhaust all failures during the training stage. As a result, out-of-distribution fault diagnosis (OOD-FD) becomes a more realistic problem that requires the methods to not only accurately diagnose the known faults, but also effectively recognize unknown ones. Therefore, a novel orthogonal anchor clustering with focal attention (FA-OAC) is proposed in this paper for OOD-FD. Firstly, an orthogonal anchor clustering (OAC) algorithm is proposed to fix the class center of each fault mode orthogonally and distinguish the known and unknown faults at the class level. Then, because the identifiability of different fault modes changes a lot in OOD-FD, the focal attention mechanism is applied to dynamically adjust the attention to different fault modes according to the distance loss of OAC, thus addressing the identifiability imbalance problem. To verify the effectiveness of the proposed method, different OOD-FD tasks are designed based on two rotating machinery datasets. The experimental results and comparison with state-of-the-art fault diagnosis methods have demonstrated that the proposed method has improved the OOD-FD performance greatly and therefore provides an effective tool in real engineering. © 2023 IEEE.

关键词： Rotating machinery

来源：评论

学校读者我要写书评

暂无评论

Non-volatile and multistate terahertz response in semi-floating-gate graphene field-effect transistors

引用

Optics Express 2025年第11期33卷 22196-22207页

作者： Jingjing Fu Mengjian Xu Miao Cai Yifan Yao Shuo Lei Wen Cai Yating Cai Fei He Shichen Zhang Xunling Zhang Shicong Hou Shun Tang Qingyang Wang Xuguang Guo Yiming Zhu Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai 200093 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai 200092 China ymzhu@***

Two-dimensional (2D) material photodetector based on semi-floating gate (SFG) structure is expected to achieve multiple functions of information sensing, storage, and processing in a single device. Here, we demonstrated a terahertz (THz) detector based on the graphene/h-BN/graphene SFG structure. The device exhibits an excellent memory behavior and a gate-controlled non-volatile and multistate photothermoelectric (PTE) THz response. A theoretical model is established to systematically investigate the memory and PTE response characteristics, and the numerical results are well consistent with the experimental results. Our research provides valuable insights into the complex optoelectronic behavior of 2D material Semi-Floating-Gate Graphene Field-Effect Transistors (SFG-FETs) and paves the way for the realization of multifunctional photodetectors based on SFG-FET structures.

关键词： Electron beam lithography Infrared detectors Optical imaging Optical microscopy Photodetectors Polymethyl methacrylate

来源：评论

学校读者我要写书评

暂无评论

Multi-view Transformer-Based Network for Prerequisite Learning in Concept Graphs 23rd

Multi-view Transformer-Based Network for Prerequisite Learn...

引用

23rd International Semantic Web Conference, ISWC 2024

作者： Wang, Zhichun Shao, Yifeng Peng, Boci Li, Bangui Li, Yun Wang, Qianren Li, Nijun School of Artificial Intelligence Beijing Normal University Beijing China Engineering Research Center of Intelligent Technology and Educational Application Ministry of Education Beijing China School of Intelligence Science and Technology Peking University Beijing China School of Computer Science and Engineering Beihang University Beijing China Advanced Cognitive AI Lab Shanghai Huawei Technologies Shanghai China

ISBN: (纸本)9783031778438

Prerequisite learning is the task of identifying prerequisite relations among concepts, which is important for many AI-based educational applications. Previous approaches explore different kinds of learning resources to obtain useful features for predicting prerequisites. Early approaches use handcrafted features while recent approaches use neural networks to encode information of concepts. To further improve the results of prerequisite learning, we build concept graphs to include comprehensive information about concepts from open data and learning resources, and propose a Multi-view Transformer-based Network (MTN) to encode multi-view features of concepts in the graph. Multi-view features are fused to make accurate predictions of concept prerequisites. We evaluate our approach on four public datasets and compare it with recently published approaches. The results show that our approach can achieve state-of-the-art results in the task of prerequisite learning. The source code and data are available at https://***/kg-bnu/MTN. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

引用

Neural Regeneration research 2025年第5期20卷 1495-1504页

作者： Yunting Xiang Xiangxin Xing Xuyun Hua Yuwen Zhang Xin Xue Jiajia Wu Mouxiong Zheng He Wang Jianguang Xu School of Rehabilitation Science Shanghai University of Traditional Chinese MedicineShanghaiChina Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation Ministry of EducationShanghaiChina Department of Rehabilitation Medicine Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Department of Traumatology and Orthopedics Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghaiChina Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence(Fudan University) Ministry of EducationShanghaiChina Human Phenome Institute Fudan UniversityShanghaiChina

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected ***,differences among reconstruction strategies at the brain network level have not been *** study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve ***–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper ***-state brain functional magnetic resonance imaging was obtained 7 months after *** independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the *** in intra-network resting-state functional connectivity were compared among the *** muscle reinnervation was assessed by behavioral observation(elbow flexion)and *** results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural *** repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor *** thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve *** areas related to cognition and emotion were enhanced after end-to-side nerve *** study revealed important brain networks related to different nerve *** networks may be potential targets for enhancing motor recovery.

关键词： brain functional networks end-to-end nerve transfer end-to-side nerve transfer independent component analysis nerve repair peripheral plexus injury resting-state functional connectivity

来源：评论

学校读者我要写书评

暂无评论

A wave-powered ocean robot integrated with umbrella-shaped wave energy converter

引用

Energy 2025年 328卷

作者： Lu, Yunfei Wang, Bingbing Zhou, Boen Zhou, Songlin Chen, Weixing State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Research Center of Marine Intelligent Equipment and Robot Institute of Marine Equipment Shanghai Jiao Tong University Shanghai China

Extracting energy from waves offers a promising solution for ocean robots to address energy limitations and extend operational time. However, the compact size of ocean robots and the random nature of waves impose significant design challenges for wave energy converters. In response to these problems, this paper proposes an ocean robot that adopts a dual-mode operation principle and integrates an umbrella-shaped wave energy converter (U-WEC). In U-WEC mode, the robot deploys four foldable wings to harvest wave energy, while in robot mode, it folds the wings for a compact structure. The robot in U-WEC mode is designed with central symmetry and a float with low natural frequency, ensuring the adaptability to waves with random directions and low frequency. The operation principle of the robot is detailed along with the structure design. Then, a hydrodynamic model is established to calculate the motion responses of the robot in U-WEC mode. In the wave tank experiment, the dual-mode operation principle is first validated and then the wave energy conversion performance is tested, achieving an average power output of 2.59 W. Based on the proposed model verified with experimental results, the robot demonstrates insensitivity to wave directions and the capability to harness low-frequency waves, confirming its feasibility and potential for practical applications. © 2025 Elsevier Ltd

关键词： intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Efficient Image Super-Resolution With Feature Interaction Weighted Hybrid Network

引用

IEEE Transactions on Multimedia 2025年 27卷 2256-2267页

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Yang, Jian Qi, Guo-Jun Lin, Chia-Wen Beijing University of Posts and Telecommunications Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing100080 China Shanghai University School of Communication and Information Engineering Shanghai200444 China Nanjing University of Posts and Telecommunications IVIPLab Institute of Advanced Technology Nanjing210046 China Ministry of Education Key Laboratory of Artificial Intelligence Shanghai200240 China Soochow University Provincial Key Laboratory for Computer Information Processing Technology Suzhou215006 China Nanjing University of Science and Technology School of Computer Science and Technology Nanjing210094 China Westlake University Research Center for Industries of the Future School of Engineering Hangzhou310024 China OPPO Research SeattleWA98101 United States National Tsing Hua University Department of Electrical Engineering Institute of Communications Engneering Hsinchu300044 Taiwan

Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss of middle-layer features due to activation functions. To minimize the impact of intermediate feature loss on reconstruction quality, we propose a Feature Interaction Weighted Hybrid Network (FIWHN), which comprises a series of Wide-residual Distillation Interaction Block (WDIB) as the backbone. Every third WDIB forms a Feature Shuffle Weighted Group (FSWG) by applying mutual information shuffle and fusion. Moreover, to mitigate the negative effects of intermediate feature loss, we introduce Wide Residual Weighting units within WDIB. These units effectively fuse features of varying levels of detail through a Wide-residual Distillation Connection (WRDC) and a Self-Calibrating Fusion (SCF). To compensate for global feature deficiencies, we incorporate a Transformer and explore a novel architecture to combine CNN and Transformer. We show that our FIWHN achieves a favorable balance between performance and efficiency through extensive experiments on low-level and high-level tasks. © 1999-2012 IEEE.

关键词： Transformers Convolutional neural networks Computational modeling Feature extraction Training Superresolution Adaptation models Computer architecture Telecommunications Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：