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Van der Waals integration inch-scale 2D MoSe_(2) layers on Si for highly-sensitive broadband photodetection and imaging

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Nano Research 2023年第8期16卷 11422-11429页

作者： Yupiao Wu Shuo-En Wu Jinjin Hei Longhui Zeng Pei Lin Zhifeng Shi Qingming Chen Xinjian Li Xuechao Yu Di Wu School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai 519082China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

As one of the most promising materials for two-dimensional transition metal chalcogenides(2D TMDs),molybdenum diselenide(MoSe_(2))has great potential in photodetectors due to its excellent properties like tunable bandgap,high carrier mobility,and excellent air *** 2D MoSe_(2)-based photodetectors have been reported to exhibit admired performance,the large-area 2D MoSe_(2)layers are difficult to be achieved via conventional synthesis methods,which severely impedes its future ***,we present the controllable growth of large-area 2D MoSe_(2)layers over 3.5-inch with excellent homogeneity by a simple post-selenization ***,a high-quality n-MoSe_(2)/p-Si van der Waals(vdW)heterojunction device is in-situ fabricated by directly growing 2D n-MoSe_(2)layers on the patterned p-Si substrate,which shows a self-driven broadband photoresponse ranging from ultraviolet to mid-wave infrared with an impressive responsivity of 720.5 mA·W^(−1),a high specific detectivity of 10^(13) Jones,and a fast response time to follow nanosecond pulsed optical *** addition,thanks to the inch-level 2D MoSe_(2)layers,a 4×4 integrated heterojunction device array is achieved,which has demonstrated good uniformity and satisfying imaging *** large-area 2D MoSe_(2)layer and its heterojunction device array have great promise for high-performance photodetection and imaging applications in integrated optoelectronic systems.

关键词： molybdenum diselenide large-area synthesis broadband photodetector integrated device array van der Waals(vdW)heterojunction

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Enhancing Robustness in Manipulability Assessment: The Pseudo-Ellipsoid Approach

Enhancing Robustness in Manipulability Assessment: The Pseud...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Erfan Shahriari Kim Kristin Peper Matej Hoffmann Sami Haddadin Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence Technical University of Munich (TUM) Germany Department of Mechanical Engineering Newman Laboratory for Biomechanics and Human Rehabilitation Massachusetts Institute of Technology (MIT) USA Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague (CTU) Czech Republic

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Manipulability analysis is a methodology employed to assess the capacity of an articulated system, at a specific configuration, to produce motion or exert force in diverse directions. The conventional method entails generating a virtual ellipsoid using the system’s configuration and model. Yet, this approach poses challenges when applied to systems such as the human body, where direct access to such information is limited, necessitating reliance on estimations. Any inaccuracies in these estimations can distort the ellipsoid’s configuration, potentially compromising the accuracy of the manipulability assessment. To address this issue, this article extends the standard approach by introducing the concept of the manipulability pseudo-ellipsoid. Through a series of theoretical analyses, simulations, and experiments, the article demonstrates that the proposed method exhibits reduced sensitivity to noise in sensory information, consequently enhancing the robustness of the approach.

关键词： Analytical models Visualization Accuracy Sensitivity analysis Noise Force Estimation Robustness Ellipsoids Standards

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Asynchronous Distributed Optimization via ADMM with Efficient Communication

Asynchronous Distributed Optimization via ADMM with Efficien...

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IEEE Conference on Decision and Control

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA US Hong Kong China Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden

In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers from processing delays. We present a distributed algorithm which combines the Alternating Direction Method of Multipliers (ADMM) strategy with a finite time quantized averaging algorithm. In our proposed algorithm, nodes exchange quantized valued messages and operate in an asynchronous fashion. More specifically, during every iteration of our algorithm each node (i) solves a local convex optimization problem (for the one of its primal variables), and (ii) utilizes a finite-time quantized averaging algorithm to obtain the value of the second primal variable (since the cost function for the second primal variable is not decomposable). We show that our algorithm converges to the optimal solution at a rate of O (1/ k) (where $k$ is the number of time steps) for the case where the local cost function of every node is convex and not-necessarily differentiable. Finally, we demonstrate the operational advantages of our algorithm against other algorithms from the literature.

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Inner approximations of convex sets and intersections of projectionally exposed cones

arXiv

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arXiv 2025年

作者： Lourenço, Bruno F. Roshchina, Vera Saunderson, James Department of Fundamental Statistical Mathematics Institute of Statistical Mathematics Japan School of Mathematics and Statistics UNSW Sydney Australia Department of Electrical and Computer Systems Engineering Monash University Australia

A convex cone is said to be projectionally exposed (p-exposed) if every face arises as a projection of the original cone. It is known that, in dimension at most four, the intersection of two p-exposed cones is again p-exposed. In this paper we construct two p-exposed cones in dimension 5 whose intersection is not p-exposed. This construction also leads to the first example of an amenable cone that is not projectionally exposed, showing that these properties, which coincide in dimension at most 4, are distinct in dimension 5. In order to achieve these goals, we develop a new technique for constructing arbitrarily tight inner convex approximations of compact convex sets with desired facial structure. These inner approximations have the property that all proper faces are extreme points, with the exception of a specific exposed face of the original set. Copyright © 2025, The Authors. All rights reserved.

关键词： Cones

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Residual-driven Fuzzy C-Means Clustering for Image Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 876-889页

作者： Cong Wang Witold Pedrycz ZhiWu Li MengChu Zhou Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R 2V4Canada School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071China the Faculty of Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071and also with the Institute of Systems EngineeringMacao University of Science and TechnologyMacaoChina Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in *** propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of *** on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown ***,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image *** experiments on synthetic,medical,and real-world images are *** results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.

关键词： Fuzzy C-Means image segmentation mixed or unknown noise residual-driven weighted regularization

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Towards Designing a Medication Assistive Intelligent System with Automated Insulin-dose Prediction for Elderlies

Towards Designing a Medication Assistive Intelligent System ...

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International Conference on electrical, computer and Communication engineering (ECCE)

作者： Abrar Ahmed Minhazul Islam Mahi M. Akhtaruzzaman Jamal Uddin Tanvin Fahim Shahryer Sachitra Halder Muhammad Towfiqur Rahman Md Shofiqul Islam Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh Department of Computer Science & Engineering University Asia Pacific (UAP) Dhaka Bangladesh Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Geelong Victoria

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Medication management poses significant challenges for many patients, particularly the elderlies, who often struggle with keeping track of their medication schedules and taking the correct dosages. To address this issue, this study aims to design an AI-integrated Medication Management and Assistive Unit (AMMAU) for elderlies with some important features like, schedule reminder, medicine recognition and count, early indication of shortage, sorted slots, and so on. Automated insulin-dose prediction and alert system makes the system unique and more demanding at these current scenarios. For this study, a suitable machine learning model is designed, analyzed, verified, and embedded in the proposed system so that the elderly diabetic patients can get alert, further compare with the current insulin-doses. Though, the proposed system is currently focusing on only the Basal insulin doses prediction, the system will definitely reduce the risks associated with wrong management of medication by degrading the chances of missed doses or taking wrong pills for elderlies at home.

关键词： Training Schedules Analytical models Prototypes Machine learning Predictive models Internet of Things Older adults Insulin Physical design

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Development of A Surveillance System to Detect Forest Fire and Smoke Using Deep Neural Networks 3

Development of A Surveillance System to Detect Forest Fire a...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Subramanian, Malliga Shanmugavadivel, Kogilavani Muthusamy, Suresh Bajaj, Mohit Rubanenko, Olena Danylchenko, Dmytro Kongu Engineering College Department of Computer Science and Engineering Erode India Department of Electronics and Communication Engineering Tamil Nadu Erode India Department of Electrical Engineering Dehradun248002 India Vinnytsia National Technical University Department of Electrical Stations and Systems Vinnytsya Ukraine National Technical University «kharkiv Polytechnic Institute» Department of Electric Power Transmission Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

Forest fires are a major environmental hazard, causing economic, ecological, and human harm. Forest fires are natural flames that occur in forests, shrubs, and grasslands. Wildfires are usually caused by lightning or human error and occur during dry hot summers. Predicting such an environmental issue is crucial to reducing the threat. WSN is one of the innovative technologies and approaches developed to anticipate and detect forest fires. The accuracy of such fire detection technologies ranges from 80% to 91%. In this work, deep learning identification systems based on Convolutional Neural Networks (CNN) namely VGG16 and Mobile Net via Teachable Machine are presented to automatically detect fire in its early phases. Fire, No Fire, Smoke, and Smoke Fire are the four classes of images of forest fires identified in this work. With 98.5% accuracy on the Fire Image dataset, Mobile Net via Teachable machine outperforms the literature when it comes to predicting the fire. © 2022 IEEE.

关键词： Fires

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Explaining complex systems: a tutorial on transparency and interpretability in machine learning models (part II)

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IFAC-PapersOnLine 2024年第15期58卷 497-501页

作者： Donatello Materassi Sean Warnick Cristian Rojas Maarten Schoukens Elizabeth Cross Department of Electrical and Computer Engineering University of Minnesota US Department of Homeland Security Science and Technology Directorate EECS/Division of Decision and Control Systems KTH Royal Institute of Technology Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands Department of Mechanical Engineering University of Sheffield

In the second segment of the tutorial, we transition from the granularity of local interpretability to a broader exploration of eXplainable AI (XAI) methods. Building on the specific focus of the first part, which delved into Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), this section takes a more expansive approach. We will navigate through various XAI techniques of more global nature, covering counterfactual explanations, equation discovery, and the integration of physics-informed AI. Unlike the initial part, which concentrated on two specific methods, this section offers a general overview of these broader classes of techniques for explanation. The objective is to provide participants with a comprehensive understanding of the diverse strategies available for making complex machine learning models interpretable on a more global scale.

关键词： eXplainable AI

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Resonant Terahertz Bolometric Detectors Using Plasmonic Response in Graphene-Channel FETs with b-P/h-BN Gate Barrier Layers

Resonant Terahertz Bolometric Detectors Using Plasmonic Resp...

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IEEE International Conference on Microwaves, Communications, Antennas and Electronic systems, COMCAS

作者： Maxim Ryzhii Victor Ryzhii Taiichi Otsuji Chao Tang Vladimir Mitin Michael S. Shur Department of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Research Institute of Electrical Communication Tohoku University Sendai Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai Japan Department of Electrical Engineering University at Buffalo SUNY Buffalo New York USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy New York USA

ISBN: (数字)9798350348187

ISBN: (纸本)9798350348194

We propose and model the terahertz bolometric detectors based on the graphene-channel field-effect transistors (GC-FETs) with the black-Phosphorus/hexagonal-Boron Nitride (b-P/h-BN) barrier layers. The GC is encapsulated in h-BN with a narrow b-P window (collector window) in the gate layer. The proposed device structure enables decreased electron scattering due to the elevated quality of the interfaces and promotes a more pronounced plasmonic response of the two-dimensional electron system in the GC. This improves the THz detector performance at the plasmonic resonances. Narrowing the collector window diminishes the Peltier effect and improves the detector characteristics.

关键词： Microwave antennas Performance evaluation Scattering Detectors Terahertz radiation Logic gates Plasmons

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Modeling and Benchmarking 5nm Ferroelectric FinFET from Room Temperature down to Cryogenic Temperatures

TechRxiv

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TechRxiv 2023年

作者： Parihar, Shivendra Singh Chatterjee, Swetaki Pahwa, Girish Chauhan, Yogesh Singh Amrouch, Hussam University of Stuttgart Germany Department of Electrical Engineering Indian Institute of Technology Kanpur India Department of Electrical Engineering & Computer Sciences University of California Berkeley United States Munich Institute of Robotics and Machine Intelligence Munich Germany Germany

The rise in quantum-computing systems, space electronics, and superconducting processors requires compatible cryogenic memories. The stringent operating conditions for these applications put additional constraints on the endurance and reliable operation of such memories. Ferroelectric-Field Effect Transistors (FeFETs) based on ferroelectric properties of the Hafnium Zirconium Oxide (HZO) can be an excellent choice for these systems. This requires a thorough characterization of FeFET at deep cryogenic temperatures. Also, the scalability of the FeFET to lower technology nodes implies a lower area and reduced leakage. In this work, we, therefore, fully characterize the 5 nm node Fe-FinFET from 10 K to 400 K. To this end, the underlying 5 nm node FinFET transistor is calibrated with experimental data from cryogenic temperatures to above-room temperatures. The material parameters of the Ferroelectric layer are also calibrated with reported measurement data. We propose that the reported endurance improvement of the HZO layer at cryogenic temperatures can improve the reliability of the Fe-FinFET. The observed wake-up and fatigue at higher temperatures are also nonexistent at cryogenic temperatures. Although the memory window is reduced at cryogenic temperature compared to room temperature, we can still hold multiple states. This is also verified through our simulations. Lastly, we demonstrate the variability in high and low threshold voltage (VTH) states due to extrinsic variation sources of the underlying transistor and ferroelectric material parameters. We observe a relatively lower variation at cryogenic temperature. © 2023, CC BY.

关键词： FinFET

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