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Stacking monolayers at will:A scalable device optimization strategy for two-dimensional semiconductors

Nano Research 2022年第7期15卷 6620-6627页

作者： Xiaojiao Guo Honglei Chen Jihong Bian Fuyou Liao Jingyi Ma Simeng Zhang Xinzhi Zhang Junqiang Zhu Chen Luo Zijian Zhang Lingyi Zong Yin Xia Chuming Sheng Zihan Xu Saifei Gou Xinyu Wang Peng Gong Liwei Liu Xixi Jiang Zhenghua An Chunxiao Cong Zhijun Qiu Xing Wu Peng Zhou Xinyu Chen Ling Tong Wenzhong Bao State Key Laboratory of ASIC and System School of MicroelectronicsZhangjiang Fudan International Innovation CenterFudan UniversityShanghai 200433China The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518057China Department of Physics State Key Laboratory of Surface PhysicsInstitute of Nanoelectronic Devices and Quantum Computing and Key Laboratory of MicroFudan UniversityShanghai 200433China State Key Laboratory of ASIC and System School of Information Science and EngineeringFudan UniversityShanghai 200433China Shanghai Key Laboratory of Multidimensional Information Processing Department of Electronic Engineering East China Normal UniversityShanghai 200241China Shenzhen Six Carbon Technology Shenzhen 518055China Department of Chemistry and Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials Fudan UniversityShanghai 200433China

In comparison to monolayer(1L),multilayer(ML)two-dimensional(2D)semiconducting transition metal dichalcogenides(TMDs)exhibit more application potential for electronic and optoelectronic devices due to their improved current carrying capability,higher mobility,and broader spectral ***,the investigation of devices based on wafer-scale ML-TMDs is still restricted by the synthesis of uniform and high-quality ML *** this work,we propose a strategy of stacking MoS_(2) monolayers via a vacuum transfer method,by which one could obtain wafer-scale high-quality MoS_(2) films with the desired number of layers at *** optical characteristics of these stacked ML-MoS_(2) films(>2L)indicate a weak interlayer *** stacked MLMoS_(2) phototransistors show improved optoelectrical performances and a broader spectral response(approximately 300-1,000 nm)than that of 1L-MoS_(2).Additionally,the dual-gate ML-MoS_(2) transistors enable enhanced electrostatic control over the stacked ML-MoS_(2) channel,and the 3L and 4L thicknesses exhibit the optimal device performances according to the turning point of the current on/off ratio and the subthreshold swing.

关键词： two-dimensional semiconductor field-effect transistors chemical vapor deposition(CVD)synthesis interlayer coupling vacuum transfer method dual-gate transistor

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A Modified RC and Diode Co-Triggered ESD Clamp Circuit 1

A Modified RC and Diode Co-Triggered ESD Clamp Circuit

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1st Annual International EOS/ESD Symposium on Design and system, IEDS 2020

作者： Yang, Zhaonian Zhang, Yibo Mao, Pan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

ISBN: (纸本)9781585373284

This paper presents a new ESD clamp circuit which is co-triggered by RC and diode. It is immune to the false triggering caused by fast power-up events due to the diode detection mechanism. With the addition of a common source amplifier, the detection signal is enhanced, and the clamp device is turned on more quickly. The proposed circuit is designed in a 0.18 μm 1.8-V CMOS process and verified by numerical simulation. The characteristics and improvements of the new circuit are discussed. © 2021 EOS/ESD ASSOCIATION INC.

关键词： Diodes

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Analysis of Belief Propagation Based Cooperative Localization and Target Tracking Schemes

Analysis of Belief Propagation Based Cooperative Localizatio...

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2021 China Automation Congress, CAC 2021

作者： Li, Yichen Yu, Wenbin Wang, Lin Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665426473

The target tracking is an fundamental ability for many oceanic applications, such as ocean surveillance, underwater rescue and etc. Due to the good mobility of autonomous underwater vehicles (AUVs), they are the ideal devices to carry out the target tracking. However, their position accuracy severely affect the target tracking performance. Thus, in this paper, aiming at the problem of target tracking using multiple AUVs, we introduce two AUV cooperative localization and target tracking schemes. The two schemes are designed based on belief propagation and carry out the localization and tracking serially and in parallel, respectively. The features and differences of both schemes are compared and analyzed in detail. Moreover, their application prospects in underwater scenarios are discussed and further validated through simulations. As a result, two schemes have their own advantages in different situations and are suitable for multiple-AUV applications. © 2021 IEEE

关键词： Belief propagation

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ToF 3D vision detection and localization of soft packaging bags based on deep learning

ToF 3D vision detection and localization of soft packaging b...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Shen, Chengyang Chen, Weidong Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation

ISBN: (纸本)9781665436786

The detection of soft packaging bags is a key step in the process of soft packaging bags unpacking. Time-of-flight(ToF) camera is used as vision sensor and a multi-scale detection method based on deep learning is proposed to solve the deformation and shielding problems of soft packaging bags. This method is improved on the basis of YOLOv3. Aiming at the texture disorder and shape change caused by the deformation of the soft packaging bags, the deformation convolution is used to replace the standard convolution for feature extraction. In view of the slow detection speed of YOLOv3, the inverted residual module based on depth separable convolution is used to replace the residual module. Aiming at the problem of non-detection caused by the occlusion between soft packaging bags, the loss function in YOLOv3 is improved and the size of anchor box is adjusted. The test is carried out when there were different degrees of shielding between the soft packaging bags and different degrees of deformation of the soft packaging bags. The experimental results show that the detection speed of this method reaches 0.8s/frame, the recall rate reaches 99%, and the relative positioning accuracy reaches 2 cm. © 2021 IEEE.

关键词： Convolution

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Learning-based 3D Reconstruction in Autonomous Driving: A Comprehensive Survey

arXiv

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arXiv 2025年

作者： Liao, Liewen Yan, Weihao Yang, Ming Zhang, Songan Global Institute of Future Technology Shanghai Jiao Tong University Key Labeoratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiao Tong University Key Labeoratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Learning-based 3D reconstruction has emerged as a transformative technique in autonomous driving, enabling precise modeling of both dynamic and static environments through advanced neural representations. Despite data augmentation, 3D reconstruction inspires pioneering solution for vital tasks in the field of autonomous driving, such as scene understanding and closed-loop simulation. We investigates the details of 3D reconstruction and conducts a multi-perspective, in-depth analysis of recent advancements. Specifically, we first provide a systematic introduction of preliminaries, including data modalities, benchmarks and technical preliminaries of learning-based 3D reconstruction, facilitating instant identification of suitable methods according to sensor suites. Then, we systematically review learning-based 3D reconstruction methods in autonomous driving, categorizing approaches by subtasks and conducting multi-dimensional analysis and summary to establish a comprehensive technical reference. The development trends and existing challenges are summarized in the context of learning-based 3D reconstruction in autonomous driving. We hope that our review will inspire future researches. Copyright © 2025, The Authors. All rights reserved.

关键词： 3D reconstruction

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FoldExplorer: Fast and Accurate Protein Structure Search with Sequence-Enhanced Graph Embedding

arXiv

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arXiv 2023年

作者： Liu, Yuan Shen, Hong-Bin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

The advent of highly accurate protein structure prediction methods has fueled an exponential expansion of the protein structure database. Consequently, there is a rising demand for rapid and precise structural homolog search. Traditional alignment-based methods are dedicated to precise comparisons between pairs, exhibiting high accuracy. However, their sluggish processing speed is no longer adequate for managing the current massive volume of data. In response to this challenge, we propose a novel deep-learning approach FoldExplorer. It harnesses the powerful capabilities of graph attention neural networks and protein large language models for protein structures and sequences data processing to generate embeddings for protein structures. The structural embeddings can be used for fast and accurate protein search. And the embeddings also provide insights into the protein space. FoldExplorer demonstrates a substantial performance improvement of 5% to 8% over the current state-of-the-art algorithm on the benchmark datasets. Meanwhile, FoldExplorer does not compromise on search speed and excels particularly in searching on a large-scale dataset. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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SAR Image Compression Based on Low-Frequency Suppression and Target Perception 8th

SAR Image Compression Based on Low-Frequency Suppression and...

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8th EAI International Conference on Machine Learning and Intelligent Communications, MLICOM 2023

作者： Deng, Jiawen Huang, Lijia Wu, Yifan Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783031717154

Synthetic Aperture Radar (SAR) images are widely used in the field of remote sensing. To store and transmit the growing amount of SAR image data, more efficient compression algorithms are required. In this paper, a new framework for compressing SAR images is proposed based on deep learning. Firstly, we propose a new two-stage transformation based on low-frequency suppression of input data to achieve high information entropy and low quantization loss. To explore the redundancy between regions of interest and regions of non-interest, an image compression model for target perception is proposed to convert the input SAR image into a compact latent representation together with the target perception map. To evaluate the performance of the algorithm, we conducted experiments on SAR image dataset. The results show that the proposed algorithm is significantly better than the traditional processing algorithm in terms of data input, and can effectively preserve and improve the performance of the image compression model. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Image compression

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Evolutionary Dynamics of Cooperation on Coupled Networks

Evolutionary Dynamics of Cooperation on Coupled Networks

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control Theory and Applications (ICoCTA), International Conference on

作者： Zhenyu Shi Qi Su Department of Automation Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331506155

ISBN: (纸本)9798331506162

Network reciprocity has been recognized as a crucial mechanism for promoting the evolution of cooperation. However, prior studies on network reciprocity have predominantly focused on isolated networks, neglecting the interconnected nature of real-world systems. In reality, many large-scale systems are closely coupled, where the interaction patterns between systems differ significantly from those within individual networks. Motivated by this observation, we construct a strategy evolution model on coupled networks to explore the effects of such interconnections. Our findings reveal that coupled networks foster cooperation more effectively than isolated networks. This advantage persists across various network structures, suggesting the universality of this phenomenon. Interestingly, we discover that the strength of the coupling plays a pivotal role: weaker coupling between networks is more conducive to the emergence and stability of cooperation compared to stronger coupling. These results high-light the importance of considering cross-system interactions in understanding and designing mechanisms to enhance cooperative behavior.

关键词： Couplings Stability analysis Large-scale systems control theory Game theory

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3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

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Regenerative Biomaterials 2023年第1期10卷 294-305页

作者： Yanyan Cao Lei Sun Zixian Liu Zhizhong Shen Wendan Jia Peiyi Hou Shengbo Sang College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at *** regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral *** use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,*** this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D *** resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral ***,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in ***,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

关键词： additive manufacturing 3D printing electrospinning subchondral bone

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Cluster Consensus Problem on Time-varying Higher-Order Interaction Networks

Cluster Consensus Problem on Time-varying Higher-Order Inter...

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IEEE Conference on Decision and control

作者： Haoyu Wei Lulu Pan Haibin Shao Dewei Li Wenbin Yu Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper examines the cluster consensus problem of higher-order interaction networks on switching networks. The matrix-valued inter-agent coupling mechanism is employed to capture the higher-order interactions amongst neighboring agents. Specifically, for a higher-order interaction network with both positive definite and positive semi-definite coupling matrices, we examine the scenario in which the nullspace of positive semi-definite coupling matrices is constructed by a set of orthogonal basis vectors. From the perspective of the lower-order component graph -the projection of network structure onto the direction of each orthogonal basis–results on the explicit characterization of cluster consensus of higher-order interaction networks are provided. Moreover, for time-varying higher-order interaction networks, necessary and sufficient conditions are provided to ensure that a time-varying network shares the same steady-state values as the integral time-invariant network. Simulation results are provided to demonstrate the theory.

关键词： Couplings Sufficient conditions Network topology Simulation Switches Vectors Topology Steady-state Matrix decomposition Convergence

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