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Low-temperature spin Seebeck effect in nonmagnetic vanadium dioxide

physical Review B 2024年第2期110卷 024415-024415页

作者： Renjie Luo Tanner J. Legvold Liyang Chen Henry Navarro Ali C. Basaran Deshun Hong Changjiang Liu Anand Bhattacharya Ivan K. Schuller Douglas Natelson Department of Physics and Astronomy Applied Physics Graduate Program Rice Quantum Institute Department of Physics and Center for Advanced Nanoscience Materials Science Division Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low-temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature-dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination.

关键词： Spin Seebeck effect Paramagnets Strongly correlated systems

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Model-Free Control of Indoor Temperatures in Residential Buildings: Convergence Analysis

Model-Free Control of Indoor Temperatures in Residential Bui...

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Power and Energy Conference at Illinois (PECI)

作者： Tumin Wu Mohammed M. Olama Seddik M. Djouadi Department of Electrical Engineering and Computer Science University of Tennessee Knoxville Tennessee Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak Ridge Tennessee

Model-free control (MFC) has recently been applied in multiple fields, including indoor air temperature regulation in buildings. It is a data-enabled feedback tracking control strategy for complex systems using a simplified representation of the ultra-local approximation model through the unique information of input-output behavior. MFC is a prevailing control strategy for systems with unknown or poorly known system dynamic models. Thus, it is a relatively simple, but efficient, trajectory tracking controller. In this paper, we investigate the convergence rate of MFC when applied to controlling indoor temperatures in residential buildings subject to outdoor weather disturbances. Numerical results show that MFC is quite robust to external disturbances, and its rate of convergence is almost one, i.e., it converges Q-sublinearly (slower than linearly).

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Zeroth-Order and Vortex Bessel Beams from Single-Mode Fibers with 3D Printed Photonic Structures

Zeroth-Order and Vortex Bessel Beams from Single-Mode Fibers...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Innem V.A.K Reddy Andrea Bertoncini Carlo Liberale Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Electrical Engineering University at Buffalo NY USA Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia

ISBN: (纸本)9798350345995

Diffraction-free propagation and self-healing characteristics [1] of Bessel beams have generated significant interest in the scientific community. Zeroth-order Bessel beams (ZOBBs) have maximum intensity at the center and found many applications, including bio-imaging material processing, optical trapping, bio-imaging, and quantum communication. On the other hand, higher-order (vortex) Bessel beams (HOBBs) present a helical wavefront, so they have a node due to a phase singularity and carry orbital angular momentum (OAM). Over the past years, Bessel beams have been generated by using different approaches - which could be different for ZOBBs and HOBBs - namely by Fourier transforming a narrow circular beam with a lens, by using axicons or with holographic beam shaping techniques.

关键词： Beam shaping Fourier transforms Materials processing Optical trapping Optical vortices Single mode fibers

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Anomalous and Topological Hall Resistivity in Ta/CoFeB/MgO Magnetic Systems for Neuromorphic Computing Applications

arXiv

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arXiv 2023年

作者： Lone, Aijaz H. Zou, Xuecui Setti, Gianluca Fariborzi, Hossein Das, Debasis Fong, Xuanyao Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore

Topologically protected spin textures, such as magnetic skyrmions, have the potential for dense data storage as well as energy-efficient computing due to their small size and a low driving current. The evaluation of the writing and reading of the skyrmion's magnetic and electrical characteristics is a key step toward the implementation of these devices. In this paper, we present the magnetic heterostructure Hall bar device and study the anomalous Hall and topological Hall signals in the device. Using the combination of different measurements like magnetometry at different temperatures, Hall effect measurement from 2K to 300K, and magnetic force microscopy imaging, we investigate the magnetic and electrical characteristics of the magnetic structure. We measure the skyrmion topological resistivity at different temperatures as a function of the magnetic field. The topological resistivity is maximum around the zero magnetic field and it decreases to zero at the saturating field. This is further supported by MFM imaging. Interestingly the resistivity decreases linearly with the field, matching the behavior observed in the corresponding micromagnetic simulations. We combine the experimental results with micromagnetic simulations, thus propose a skyrmion-based synaptic device and show spin-orbit torque-controlled potentiation/depression in the device. The device performance as the synapse for neuromorphic computing is further evaluated in a convolutional neural network CNN. The neural network is trained and tested on the MNIST data set we show devices acting as synapses achieving a recognition accuracy close to 90%, on par with the ideal software-based weights which offer an accuracy of 92%. © 2023, CC BY.

关键词： Energy efficiency

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A hybrid channel transmission method for effective spectrum access in cognitive radio networks

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International Journal of Ad Hoc and Ubiquitous Computing 2023年第4期44卷 221-232页

作者： Dhurandher, Sanjay Kumar Kumar, Bhoopendra Woungang, Isaac Chao, Han-Chieh Department of Information Technology Netaji Subhas University of Technology New Delhi India National Institute of Electronics and Information Technology Delhi Centre New Delhi India CAITFS Division of Information Technology Netaji Subhas Institute of Technology University of Delhi Delhi India KIET Group of Institutions Delhi-NCR Ghaziabad India Department of Computer Science Ryerson University TorontoON Canada Department of Electrical Engineering National Dong Hwa University Hualien Taiwan Department of Computer Science and Information Engineering National Ilan University I-Lan Taiwan Institute of Computer Science and Innovation UCSI University Kuala Lumpur Malaysia

Cognitive radio is considered as a very influencing technique and has the great potential to solve the problem of shortage of the radio spectrum. A secondary user also called as a cognitive user may access the primary channel(s) with a certain restrictions in a cognitive radio network. Spectrum sensing is a very important activity during the process of spectrum access. This paper proposes a Markov chain-based proactive hybrid spectrum access method for maximising the radio spectrum usage by optimising the channel sensing process and establishing the channel switching conditions. Using the OMNeT++ simulator, the proposed method (proactive hybrid access) is compared against that of the conventional (reactive hybrid access), overlay, and underlay access methods, showing its superiority by about 20% in terms of performance improvement with respect to throughput, service delay, and PU detection probability. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Cognitive radio

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Efficient Perovskite quantum dots Light Emitting Diodes

Efficient Perovskite quantum dots Light Emitting Diodes

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International Conference on Display Technology, 2024

作者： Deng, Ming Li, Yanming Zhang, Xuanyu Xiang, Chaoyu Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Zhejiang 315211 China Division of Functional Materials and Nanodevices Ningbo Institute of Materials Technology and Engineering Hangzhou Bay Campus Chinese Academy of Sciences Zhejiang Ningbo315300 China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China Division of Functional Materials and Nanodevices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Ningbo315201 China Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Ningbo China Zhejiang Ningbo315100 China

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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

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URSI Radio science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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Improving Microgrid Reliability and Efficiency Through Energy Storage Systems with a Pyramidal Dilation Attention Convolutional Neural Network for Renewable Energy Integration 4

Improving Microgrid Reliability and Efficiency Through Energ...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Vijayakumar, Bondu Purushothaman, K.E. Khabiya, Priyanka Garg, Akriti Rajesha, N. Kaliappan, S. Madanapalle Institute of Technology & Science Department of Electrical and Electronics Engineering Andhra Pradesh Annamayya517325 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Tamil Nadu Chennai600062 India Mandsaur University Department of Computer Science Engineering Madhya Pradesh Mandsaur458001 India Mahatma Jyotiba Phule Rohilkhand University Department of Electrical Engineering Uttar Pradesh Bareilly243006 India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore641202 India Lovely Professional University Division of Research and Development Delhi Punjab Jalandhar144411 India

ISBN: (纸本)9798331540364

Microgrid (MG) design and deployment are heavily reliant on reliability. Integrating renewable energy sources (RESs) into power grids poses considerable challenges for maintaining grid reliability due to their intermittent nature. This paper proposes a novel approach to enhance grid stability by incorporating Energy Storage Systems (ESS) coupled with Pyramidal Dilation Attention Convolutional Neural Network (PDACNN). The goal of the proposed method is to improve efficiency and lower electricity costs. The proposed PDACNN optimizes the control of Energy Storage Systems by providing more trustworthy forecasts of energy demand as well as supply. By, then the proposed method is implemented in MATLAB and evaluated their performance with various existing methods. The PDACNN method surpasses existing techniques in both efficiency and cost-effectiveness. It achieves a high efficiency of 95.7% and reduces total electricity costs to $650/kWh, outperforming the Artificial Neural Network (ANN), and Recurrent NN (RNN) and Convolutional NN (CNN) methods. © 2024 IEEE.

关键词： Energy Storage Systems Grid Stability Microgrids Pyramidal Dilation Attention Convolutional Neural Network Reliability Renewable Energy Sources

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QContext: Context-Aware Decomposition for Quantum Gates

QContext: Context-Aware Decomposition for Quantum Gates

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Ji Liu Max Bowman Pranav Gokhale Siddharth Dangwal Jeffrey Larson Frederic T. Chong Paul D. Hovland Mathematics and Computer Science Division Argonne National Laboratory Department of Electrical & Computer Engineering Rice University Super.tech a division of Infleqtion Department of Computer Science University of Chicago

In this paper we propose QContext, a new com-piler structure that incorporates context-aware and topology- aware decompositions. Because of circuit equivalence rules and resynthesis, variants of a gate-decomposition template may exist. QContext exploits the circuit information and the hardware topology to select the gate variant that increases circuit optimization opportunities. We study the basis-gate-level context-aware decomposition for Toffoli gates and the native-gate-level context- aware decomposition for CNOT gates. Our experiments show that QContext reduces the number of gates as compared with the state-of-the-art approach, Orchestrated Trios [12].

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Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization 12

Cyber-Security Knowledge Graph Generation by Hierarchical No...

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12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Barron, Ryan Eren, Maksim E. Bhattarai, Manish Wanna, Selma Solovyev, Nicholas Rasmussen, Kim Alexandrov, Boian S. Nicholas, Charles Matuszek, Cynthia Los Alamos National Laboratory Theoretical Division Los Alamos United States Los Alamos National Laboratory Advanced Research in Cyber Systems Los Alamos United States University of Maryland Department of Computer Science and Electrical Engineering Baltimore CountyMD United States

ISBN: (纸本)9798350330366

Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume of scientific papers. As this textual data continues to expand, the importance of document organization methods becomes increasingly crucial for extracting actionable insights hidden within large text datasets. Knowledge Graphs (KGs) serve as a means to store factual information in a structured manner, providing explicit, interpretable knowledge that includes domain-specific information from the cybersecurity scientific literature. One of the challenges in constructing a KG from scientific literature is the extraction of ontology from unstructured text. In this paper, we address this topic and introduce a method for building a multi-modal KG by extracting structured ontology from scientific papers. We demonstrate this concept in the cybersecurity domain. One modality of the KG represents observable information from the papers, such as the categories in which they were published or the authors. The second modality uncovers latent (hidden) patterns of text extracted through hierarchical and semantic non-negative matrix factorization (NMF), such as named entities, topics or clusters, and keywords. We illustrate this concept by consolidating more than two million scientific papers uploaded to arXiv into the cyber-domain, using hierarchical and semantic NMF, and by building a cyber-domain-specific KG. © 2024 IEEE.

关键词： Cybersecurity

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