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Interfacial Thermal Transport and Energy Dissipation in Multilayer PdSe2 Field Effect Transistors

Advanced Materials 2025年第0期 e2503264页

作者： Xie, Jiaqiu Yu, Zehao Sun, Yuanchen Gan, Qikang Liu, Chenhan Wang, Lei Zhang, Lifa Zhao, Yunshan Phonon Engineering Research Center of Jiangsu Province Ministry of Education Key Laboratory of NSLSCS Center for Quantum Transport and Thermal Energy Science Institute of Physics Frontiers and Interdisciplinary Sciences School of Physics and Technology Nanjing Normal University Nanjing210023 China National Laboratory of Solid-State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Micro- and Nano-scale Thermal Measurement and Thermal Management Laboratory Jiangsu Key Laboratory for Numerical Simulation of Large-Scale Complex Systems School of Energy and Mechanical Engineering Nanjing Normal University Nanjing210046 China

The continuous miniaturization of 2D electronic circuits results in increased power density during device operation, leading to heat localization and placing higher demands on their performance thresholds. The risk to thermal breakdown and subsequent damage, due to the energy dissipation in the 2D semiconductor field-effect transistors (FETs) supported on the bulk substrates, represents a significant challenge in maintaining their optimal performance. Herein, this study investigates energy dissipation behavior in multilayer PdSe2 FETs for the first time. The high-field breakdown behavior is firstly studied in multilayer PdSe2 FETs on SiO2/Si substrates, where a maximum current density of ≈2.74 MA cm−2 is observed, which is comparable to that of multilayer black phosphorus FET and significantly higher—by about five times—than that of multilayer MoS2 FET. Additionally, the thermal boundary conductance (TBC) of PdSe2/SiO2 interface is measured at room temperature using Raman thermometry. The TBC is found to be ≈12–13 MW m−2 K−1, which is relatively low compared to the other known solid–solid interfaces, indicating that enhancing the performance of PdSe2 FETs can be possible by optimizing the TBC at the PdSe2/SiO2 interface. These findings provide valuable insights for design of high-quality and high-performance PdSe2 electronic and optoelectronic devices. © 2025 Wiley-VCH GmbH.

关键词： Multilayers

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Developing nonlinear adaptive optimal regulators through an improved neural learning mechanism

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Science China(Information Sciences) 2017年第5期60卷 252-254页

作者： Ding WANG Chaoxu MU The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information EngineeringTianjin University

Optimal feedback design of dynamical systems is a significant topic in automatic control community and information *** for nonlinear systems,optimal control design always leads to coping with the nonlinear Hamilton-Jacobi-Bellman ***,it is intractable to acquire the analytic solution of the nonlinear Hamilton-JacobiBellman equation for general nonlinear systems.

关键词： Developing nonlinear adaptive optimal regulators through an improved neural learning mechanism

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Improving Performance of Repetitive control for Nonlinear systems via Improved Disturbance Compensation

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IEEE Transactions on Industrial Informatics 2025年

作者： Tian, Shengnan Wang, Yibing Zhang, Manli Li, Yang Lu, Chengda Liu, Kang-Zhi She, Jinhua Wu, Min China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Chiba University Department of Electrical and Electronic Engineering Chiba263-8522 Japan Tokyo University of Technology School of Engineering Hachioji192-0982 Japan

In practice, repetitive control (RC) is a type of learning control that exhibits good tracking performance. However, existing nonlinear RC methods lack analysis and design of the learning property, which results in limited performance. This study addresses the learning-enhanced issue. First, a new fuzzy Lyapunov candidate is constructed for stability analysis, which contains an integral term associated with the membership function and a double integral term. The design of the learning-dependent term integrates the nonlinear membership function information, which enhances the learning ability. Second, an additional first-order low-pass filter is incorporated into the conventional equivalent input disturbance estimator. The new filter acts as an integrator that adjusts the bandwidth of the disturbance compensation and gradually eliminates the disturbances in the output error. Third, a recursive optimization algorithm is used to design the controllers. Experimental comparisons on motor drive systems demonstrate the effectiveness and superiority of the method. © 2005-2012 IEEE.

关键词： Membership functions

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Precedence graph-oriented approach to optimise single-product flow-line configurations of reconfigurable manufacturing system

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2009年第10期22卷 923-940页

作者： Dou, J. P. Dai, X. Meng, Z. [a]Key Laboratory of Measurement and Control of Complex Systems of Engineering (School of Automation Southeast University) Ministry of Education China

To facilitate the configuration selection of reconfigurable manufacturing systems, it needs to generate K (predefined number) best configurations as candidates for a given demand period. This paper presents a systematic approach for the problem of generating single-product flow-line (SPFL) configurations. The problem is to determine the SPFL configuration's parameters including number of workstations, number of paralleling machines and machine type as well as assigned operations for each workstation. Given an operation precedence graph (PG) and machine options for each operation, the objective is to minimise the capital costs of SPFL configurations subject to space limitation, investment limitation, and capacity constraint as well as precedence constraints among operations. For linear PG with one feasible operation sequence (FOS), a constrained K-shortest paths (CKSP) formulation is developed and a CKSP algorithm is introduced to generate K-best configurations including the optimal and near-optimal ones. For simple PG (a small number of FOSs), the K-best configurations are found by repeatedly solving the CKSP problem associated with every FOS. For general PG (numerous FOSs), a GA based approach is proposed to identify K-best configurations through searching within the optimal configurations associated with all FOSs. Case studies illustrate the effectiveness and efficiency of our approach.

关键词： reconfigurable manufacturing system configuration generation flow-line precedence graph constrained K-shortest paths genetic algorithm

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 PP卷 PP页

作者： Jun Chen Liling Yang Wei Yu Wenping Gong Zhanchuan Cai Jiayi Ma School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Faculty of Engineering China University of Geosciences Wuhan China School of Computer Science and Engineering Macau University of Science and Technology Taipa Macau China Electronic Information School Wuhan University Wuhan China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. The code will be posted at: https://***/Liling-yang/SDSFusion.

关键词： Degradation Image fusion Semantics Training Visualization Meteorology Feature extraction Lighting Image segmentation Brightness

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ASTARS Aided NOMA Covert Communication Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Yue, Xinwei Song, Xinlong Zhao, Jingjing Huang, Chongwen Jin, Hongxu Xiang, Wei Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing102206 China Beijing Information Science and Technology University Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing102206 China Beihang University School of Electronic and Information Engineering Beijing100191 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China Hangzhou310027 China Zunyi Normal University School of Information Engineering Zunyi563006 China La Trobe University School of Computing Engineering and Mathmatical Sciences MelbourneVIC3086 Australia

The active simultaneously transmitting and reflecting surface (STARS) has been proposed as a complement of passive STARS (PSTARS) to inhibit the double path-loss. This paper applies the active STARS (ASTARS) to aid in non-orthogonal multiple access (NOMA) covert communications over cascaded rice fading channels, where two wardens are located on the opposite sides of ASTARS to monitor the transmission information. More specifically, we derive approximate expressions for detection error probability of two wardens. The optimal detection threshold and minimum detection error probability are presented in the worst covert scenarios. The covert transmission rate expressions for a coupe of covert users are further deduced by taking into account imperfect/perfect successive interference cancellation. The experimental simulation results are presented to confirm that: 1) The detection error probability of ASTARS-NOMA networks is superior to that of ASTARS assisted-orthogonal multiple access (ASTARS-OMA) and PSTARS aided NOMA networks;2) As the number of active elements increases, the covert transmission rates of ASTARS-NOMA networks become larger relative to ASTARS-OMA;and 3) ASTARS-NOMA has ability to provide the enhanced system throughput in delay-tolerant transmission mode. © 2025 IEEE.

关键词： Fading channels

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Sensing With Random Communication Signals

arXiv

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arXiv 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi National Mobile Communications Research Laboratory Southeast University Nanjing210096 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin10587 Germany Southern University of Science and Technology Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security and also The Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing211189 China

Communication-centric Integrated Sensing and Communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025, CC BY-SA.

关键词： Signaling

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Event-triggered receding horizon control via actor-critic design

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Science China(Information Sciences) 2020年第5期63卷 131-145页

作者： Lu DONG Xin YUAN Changyin SUN School of Automation Southeast University College of Electronics and Information Engineering Tongji University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University

In this paper, we propose a novel event-triggered near-optimal control for nonlinear continuoustime systems. The receding horizon principle is utilized to improve the system robustness and obtain better dynamic control performance. In the proposed structure, we first decompose the infinite horizon optimal control into a series of finite horizon optimal problems. Then a learning strategy is adopted, in which an actor network is employed to approximate the cost function and an critic network is used to learn the optimal control law in each finite horizon. Furthermore, in order to reduce the computational cost and transmission cost, an event-triggered strategy is applied. We design an adaptive trigger condition, so that the signal transmissions and controller updates are conducted in an aperiodic way. Detailed stability analysis shows that the nonlinear system with the developed event-triggered optimal control policy is asymptotically *** results on a single-link robot arm with different noise types have demonstrated the effectiveness of the proposed method.

关键词： event-triggered control receding horizon control actor-critic design optimal control nonlinear systems neural networks

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Intelligent Monitoring Based on Integrated Temporal Dictionary Learning with Isometric Mapping for Geological Drilling Process

Intelligent Monitoring Based on Integrated Temporal Dictiona...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Tianyu Ma Sheng Du Haipeng Fan Cheng Huang School of Future Technology China University of Geosciences Wuhan China School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Geological drilling process, owing to complex geological environment and harsh downhole conditions, generates data including characteristics such as pressure, rotational speed, and depth, which are frequently high-dimensional and noisy. These characteristics make real-time monitoring more complex. Existing methods in the geological drilling process, such as rule-based systems and threshold techniques, struggle to handle the complexity and high dimensionality of drilling data, leading to high false alarm rates and low detection accuracy. This paper develops an integrated temporal dictionary learning with isometric mapping method for monitoring geological drilling process. Specifically, Isometric Mapping is employed to perform dimensionality reduction on high-dimensional data, thereby retaining the structural features in the lower-dimensional space. Subsequently, Lasso regularization is applied for sparse coding to extract essential features from the reduced data. To address the fluctuations arising from the iterative dictionary learning process, a temporal smoothing term is incorporated to ensure the stability of the dictionary across different time steps. After that, the reconstruction errors were adopted to achieve comprehensive statistical indicators. Then the overall monitoring was realized for the plant-wide process. The effectiveness and robustness of the proposed method are demonstrated through case studies on the Tennessee-Eastman process and the actual geothermal drilling process.

关键词： Drilling Smoothing methods Accuracy Geology Velocity control Feature extraction Robustness Kernel Monitoring Principal component analysis

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Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation

arXiv

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arXiv 2025年

作者： Zhang, Dengke Tang, Quan Liu, Fagui Mei, Haiqing Chen, C.L. Philip The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of New Network Pengcheng Laboratory Shenzhen518000 China The China Tobacco Guangdong Industrial Corporation Guangzhou510385 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Semi-supervised semantic segmentation has witnessed remarkable advancements in recent years. However, existing algorithms are based on convolutional neural networks and directly applying them to Vision Transformers poses certain limitations due to conceptual disparities. To this end, we propose TokenMix, a data augmentation technique specifically designed for semi-supervised semantic segmentation with Vision Transformers. TokenMix aligns well with the global attention mechanism by mixing images at the token level, enhancing learning capability for contextual information among image patches. We further incorporate image augmentation and feature augmentation to promote the diversity of augmentation. Moreover, to enhance consistency regularization, we propose a dual-branch framework where each branch applies image and feature augmentation to the input image. We conduct extensive experiments across multiple benchmark datasets, including Pascal VOC 2012, Cityscapes, and COCO. Results suggest that the proposed method outperforms state-of-the-art algorithms with notably observed accuracy improvement, especially under limited fine annotations. Copyright © 2025, The Authors. All rights reserved.

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