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Scalable Metagrating for Efficient Ultrasonic Focusing

Physical Review Applied 2021年第6期16卷 064014-064014页

作者： Yan Kei Chiang Li Quan Yugui Peng Shahrokh Sepehrirahnama Sebastian Oberst Andrea Alù David A. Powell School of Engineering and Information Technology University of New South Wales Canberra ACT 2610 Australia Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Centre for Audio Acoustics and Vibration University of Technology Sydney Broadway NSW 2007 Australia Physics Program Graduate Center City University of New York New York New York 10016 USA

Acoustic metalenses have been pursued over the past decades due to their pivotal role in a wide variety of applications. Recent research efforts have demonstrated that, at ultrasonic regimes, acoustic levitation can be realized with standing waves, which are created by the interference between incoming and reflected focused waves. However, the conventional gradient-metasurface approach to focus ultrasonic waves is complex, leading to poor scalability. In this work, we propose a design principle for ultrasonic metalenses, based on metagratings—arrays of discrete scatters with coarser features than gradient metasurfaces. We achieve beam focusing by locally controlling the excitation of a single diffraction order with the use of metagratings, with geometry adiabatically varying over the lens aperture. We show that our metalens can effectively focus impinging ultrasonic waves to a focal point with a full width at half maximum of 0.364 of the wavelength. The focusing performance of the metalens is demonstrated experimentally, validating our proposed approach. This metagrating approach to focusing can be adopted for different operating frequencies by scaling the size of the structure, which has coarse features suitable for high-frequency designs, with potential applications ranging from biomedical science to nondestructive testing.

关键词： Acoustic measurements Acoustic metamaterials Acoustic modeling Acoustic wave phenomena Beam optics Ultrasonics Bloch-Floquet theorem Ultrasound techniques

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Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

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Physical Review Applied 2025年第3期23卷 034035-034035页

作者： Niko R. Reed Danyal Bhutto Matthew J. Turner Declan M. Daly Sean M. Oliver Jiashen Tang Kevin S. Olsson Nicholas Langellier Mark J.H. Ku Department of Physics University of Maryland College Park Maryland USA Quantum Technology Center University of Maryland College Park Maryland USA Joint Quantum Institute University of Maryland College Park Maryland USA Department of Biomedical Engineering Boston University Boston Massachusetts USA A. A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA The MITRE Corporation McLean Virginia 22102 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Department of Physics Harvard University Cambridge Massachusetts USA Present address: VideaHealth Inc. Boston MA. Department of Materials Science and Engineering University of Delaware Newark Delaware 19716 USA Department of Physics and Astronomy University of Delaware Newark Delaware 19716 USA Present address: Northrop Grumman Mission Systems Linthicum Maryland 21090 USA.

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources.

关键词： Signal to noise ratio

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Van der Waals device integration beyond the limits of van der Waals forces via adhesive matrix transfer

arXiv

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arXiv 2023年

作者： Satterthwaite, Peter F. Zhu, Weikun Jastrzebska-Perfect, Patricia Tang, Melbourne Gao, Hongze Kitadai, Hikari Lu, Ang-Yu Tan, Qishuo Tang, Shin-Yi Chueh, Yu-Lun Kuo, Chia-Nung Lue, Chin Shan Kong, Jing Ling, Xi Niroui, Farnaz Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemistry Boston University BostonMA02215 United States Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan Department of Physics National Cheng Kung University Tainan70101 Taiwan Taiwan Consortium of Emergent Crystalline Materials National Science and Technology Council Taipei10601 Taiwan Program on Key Materials Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan70101 Taiwan Division of Materials Science and Engineering Boston University BostonMA02215 United States The Photonics Center Boston University BostonMA02215 United States

Pristine van der Waals (vdW) interfaces between two-dimensional (2D) and other materials are core to emerging optical and electronic devices. Their direct fabrication is, however, challenged as the vdW forces are weak and cannot be tuned to accommodate integration of arbitrary layers without solvents, sacrificial-layers or high-temperatures, steps that can introduce damage. To address these limitations, we introduce a single-step 2D material-to-device integration approach in which forces promoting transfer are decoupled from the vdW forces at the interface of interest. We use this adhesive matrix transfer to demonstrate conventionally-forbidden direct integration of diverse 2D materials (MoS2, WSe2, PtS2, GaS) with dielectrics (SiO2, Al2O3), and scalable, aligned heterostructure formation, both foundational to device development. We then demonstrate a single-step integration of monolayer-MoS2 into arrays of transistors. With no exposure to polymers or solvents, clean interfaces and pristine surfaces are preserved, which can be further engineered to demonstrate both n- and p-type behavior. Beyond serving as a platform to probe the intrinsic properties of sensitive nanomaterials without the influence of processing steps, our technique allows efficient formation of unconventional device form-factors, with an example of flexible transistors demonstrated. Copyright © 2023, The Authors. All rights reserved.

关键词： Van der Waals forces

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Synergetic Effect of Nonthermal Plasma and Supported Cobalt Catalyst in Plasma-Enhanced Co2 Hydrogenation

SSRN

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SSRN 2022年

作者： Song, Chunshan Wang, Jiajie Wang, Xiaoxing AlQahtani, Mohammad S. Knecht, Sean D. Bilén, Sven G. Chu, Wei Department of Chemical Engineering Sichuan University Chengdu610065 China Clean Fuels & Catalysis Program EMS Energy Institute Department of Energy and Mineral Engineering The Pennsylvania State University University ParkPA16802 United States Department of Chemical Engineering The Pennsylvania State University University ParkPA16802 United States School of Engineering Design Technology and Professional Programs The Pennsylvania State University University ParkPA16802 United States School of Electrical Engineering and Computer Science The Pennsylvania State University University ParkPA16802 United States Department of Chemistry Faculty of Science The Chinese University of Hong Kong NT Hong Kong Shatin China

Nonthermal plasma can provide an alternative to CO 2 utilization under mild conditions. Understanding the effect of plasma on catalysis is highly desired. Herein, a comparative study was performed on CO 2 hydrogenation under thermal catalytic and plasma catalytic conditions using an alumina-supported cobalt catalyst. Significant plasma-catalyst synergy was attained at the low-temperature range between 423 K and 498 K where the CO 2 conversion increased up to approximately 3.6 times of the sum of that using plasma or catalyst individually. The plasma-catalytic reaction showed a significantly lower activation energy (~40 kJ/mol), which is only half of that in the thermal catalytic reaction (~80 kJ/mol). Kinetic analysis and DRIFTS results indicate that CO 2 activation is promoted by plasma with the assistance of active H species from gas phase. Furthermore, the total H 2 adsorption capacity and the coverage of unrecyclable adsorbed H species on the metal surface were decreased under plasma. The promotion effect is very likely due to a new reaction pathway introduced by plasma. In addition, the structure and morphology changes of spent catalysts after thermal or plasma reaction were not significant, suggesting they contribute little to the synergetic effect observed under the conditions. © 2022, The Authors. All rights reserved.

关键词： Carbon dioxide

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Magneto-optics in a van der Waals magnet tuned by self-hybridized polaritons

arXiv

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arXiv 2023年

作者： Dirnberger, Florian Quan, Jiamin Bushati, Rezlind Diederich, Geoffrey Florian, Matthias Klein, Julian Mosina, Kseniia Sofer, Zdenek Xu, Xiaodong Kamra, Akashdeep García-Vidal, Francisco J. Alù, Andrea Menon, Vinod M. Department of Physics City College of New York New YorkNY10031 United States Department of Physics The Graduate Center City University of New York New YorkNY10016 United States Photonics Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Department of Electrical Engineering City College of the City University of New York New YorkNY10031 United States Intelligence Community Postdoctoral Research Fellowship Program University of Washington SeattleWA United States Department of Physics Department of Materials Science and Engineering University of Washington SeattleWA United States Department of Electrical and Computer Engineering Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Inorganic Chemistry University of Chemistry and Technology Prague Technickaá 5 Prague 6166 28 Czech Republic Universidad Autónoma de Madrid MadridE- 28049 Spain

Controlling quantum materials with light is of fundamental and technological importance. By utilizing the strong coupling of light and matter in optical cavities [1–3], recent studies were able to modify some of their most defining features [4–6]. In this work, we study the magneto-optical properties of a van der Waals magnet that supports strong coupling of photons and excitons even in the absence of external cavity mirrors. In this material – the layered magnetic semiconductor CrSBr – emergent light-matter hybrids called polaritons are shown to significantly increase the spectral bandwidth of correlations between the magnetic, electronic, and optical properties, enabling largely tunable optical responses to applied magnetic fields and magnons. Our results highlight the importance of exciton-photon self-hybridization in van der Waals magnets and motivate novel directions for the manipulation of quantum material properties by strong light-matter coupling. © 2023, CC BY.

关键词： Van der Waals forces

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Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging

arXiv

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arXiv 2021年

作者： Hu, Chenfei Kandel, Mikhail E. Lee, Young Jae Popescu, Gabriel Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Neuroscience Program University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a novel modality for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product (SBP) label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45, and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges. © 2021, CC BY.

关键词： Synthetic apertures

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Mini shufflenet for efficient parking space classification

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AIP Conference Proceedings 2023年第1期2480卷

作者： Sayuti Rahman Marwan Ramli Fitri Arnia Rusdha Muharar Haida Dafitri Dharmawati Mahyus Ihsan Doctoral Program School of Engineering Syiah Kuala University Banda Aceh Indonesia Department of Mathematics Syiah Kuala University Banda Aceh Indonesia Department of Electrical and Computer Engineering Syiah Kuala University Banda Aceh Indonesia Department of Informatics Technology Universitas Harapan Medan Medan Indonesia

Motorists driving around looking for parking spaces has negative impacts such as increasing traffic jams, noise, air pollution, wasting fuel, and panic. A smart parking system providing information on the availability of parking spaces is needed. This study aims to develop a parking system by providing information on the availability of car parking spaces. Classification of car parking spaces using Sufflenet V2 is by trimming it. Based on the tests carried out, pruning was on the number of Sufflenet V2 output channels. This trimming produces the smallest Mini Shufflenet size with almost half the parameter number of mAlexnet and less than 1/10 times the number of FLOPs of mAlexnet. Mini Shufflenet has better accuracy than mAlexnet in processing time per image that is almost the same as mAlexnet. Mini Shufflenet implemented is on low-end computing devices such as the Raspberry Pi for real-time data classification. So this architecture can be implemented in a low-cost parking system.

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Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicle Communication for Local File Sharing 15th

Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicl...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Mokhtar, Bassem Azab, Mohamed Fathalla, Efat Ghourab, Esraa M. Magdy, Mohamed Eltoweissy, Mohamed Electrical Engineering Department Alexandria University Alexandria Egypt Computer Engineering Program School of Engineering and Applied Sciences Nile University Giza Egypt Computer and Information Sciences Virginia Military Institute LexingtonVA24450 United States Department of Electrical and Computer Engineering Old Dominion University NorfolkVA United States College of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Alexandria Egypt

ISBN: (纸本)9783030301453

Recently, Vehicular Cloud Communication (VCC) has been gaining momentum targeting intelligent and efficient data transmission. VCC is a type of mobile ad-hoc network comprising heterogeneous vehicles sharing their resources to perform collaborative activities. In this paper, we propose a new semi-infrastructure file-browsing in order to provide Network as a service (NaaS) enabling internet-independent browsing. In our scenario, a central management platform plays the role of controlling and managing the selection of relaying vehicles supporting the source to destination file transmission procedure. Nagel-Schreckenberg rules for traffic cellular automata (CA) are used as the basis for our scenario simulation. Nagel-Schreckenberg rules simulate the behavior of a group of hypothetical vehicles moving across a highway. We study the reliability and efficiency of file transfer in such settings. Simulation results show that the number of selected relays required to establish the network highly impacts the probability of successfully sending the requested files. In addition, the distances between the selected relays influence the network throughput and the probability of network failure. Moreover, the density of relays strongly affects the overall delay that occurs due to the continuous re-transmission of the selected files among different hops. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Vehicle to vehicle communications

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Decision Making using Internet of Things and Machine Learning: A bibliometric approach to tracking main research themes

Decision Making using Internet of Things and Machine Learnin...

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2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020

作者： Gamboa-Rosales, N.K. Castorena-Robles, A. Casas-Valadez, M.A. Cobo, M.J. Castaneda-Miranda, R. Lopez-Robles, J.R. CONACYT-Autonomous University of Zacatecas Academic Unit of Electrical Engineering Zacatecas Mexico Monterrey Institute of Technology and Higher Education Biotechnology Engineering Queretaro Mexico Autonomous University of Zacatecas Academic Unit of Accounting and Administration Zacatecas Mexico University of Cadiz Department of Computer Science and Engineering Cadiz Spain Autonomous University of Zacatecas Post. Program of Eng. and Applied Tech. National Lab. CONACYT-SEDEAM Zacatecas Mexico

ISBN: (纸本)9781728196756

The internet has become an integral part of our life, we connect daily for informational, social, entertainment and even work and economic purposes. Therefore, it is completely normal to connect to the internet;But it is not only people, also these everyday objects or things in our environment who connect to the network to take advantage of its benefits. This next stage in the evolution of the internet, in which connectivity extends to the objects which surround us, is known as the Internet of Things. Sensors, Machines, Devices, Wearables are part of the Internet of Things and these can be identified to be recognized and interact without the need for a human being. With the Internet of Things, the connection extends to any type of object. All these interconnected devices and people produce an immense amount of data, when analyzed, they become a tool that allows organizations to make wise decisions in real time by having information on various market situations and ensuring a better understanding of behavior and consumer preferences. One of the disciplines of Artificial Intelligence responsible for analyzing this large amount of data is Machine Learning, whose sole purpose is to improve the Decision-Making process. To understand the relationship between Internet of Things, application of Machine Learning and the Decision Making process, a bibliometric analysis is carried out from 2013 to 2020 to know its evolution, trends, research areas, authors and other aspects using Scopus. © 2020 IEEE.

关键词： Decision making

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Linearity assessment between lower limb joint angles and angular accelerations at standard maximum vertical jumps with long-short and no countermovement

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Gait & Posture 2023年 106卷 S174-S175页

作者： Rodrigues, Carlos Correia, Miguel Abrantes, João Benedetti, Marco Nadal, Jurandir Faculty of Engineering- University of Porto Biomedical Engineering Program Porto Portugal INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal Faculty of Engineering- University of Porto Department of Electrical and Computer Engineering Porto Portugal CICANT - Centre for Research in Applied Communication- Culture and New Technologies MovLab - Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

IntroductionStandard maximum vertical jump (MVJ) has been applied to assess lower limb long countermovement (CM) on countermovement jump (CMJ) and short CM on drop jump (DJ) for comparison to squat jump (SJ) without CM [1,2]. Research questionNevertheless, the ability for lower limb joint accelerations depending on lower limb joint angles at long, short and no CM remains an open issue [3,4], in particular linearity assessment of these relations at long, short and no CM in association with MVJ whole-body impulsion. MethodsFor this reason, we applied piecewise linear detection of segmented subphases on lower limb joint angles ( θ)-angular acceleration ( α) diagrams for the hip (H), knee (K) and ankle (A) during impulse phases on CMJ, DJ and SJ. Selected sample corresponds to best MVJ trials based on higher flight-time of 3 CMJ, DJ and SJ repetitions for six healthy untrained subjects with ages (21.5±1.4) years, (76.7±9.3)kg mass and (1.79±0.06)m height. Adhesive reflective markers were applied at lower limb and torso, with sagittal hip, knee, and ankle θ, α obtained by inverse kinematics. H,K,A ( θ, α) diagrams were plotted and impulsion subphases segmented at selected instants of ∂ a/∂ q phase reversal with linear fit by the least-squares method, Fig. 1. Fig. 1. Hip, knee, ankle joint ( θ, α) diagrams at CMJ, DJ, SJ with segmented subphases time span(Δt), |∂α/∂θ| slope magnitudes and R² linear fit regression. ResultsSJ presented larger number of ( θ, α) subphases than DJ, both larger than CMJ with higher |∂ α/∂ θ| variation at DJ and SJ than CMJ, pointing to higher complexity of neuromuscular control and contributing to explain reduced SJ, DJ performance without CM (0.33±0.05)m and with short CM (0.27±0.03)m in relation to CMJ with long CM (0.36±0.04)m for untrained selected subjects, Fig. 1. Thus, despite the larger total time span Δt at CMJ (0.76±0.10)s in relation to SJ (0.36±0.08)s and DJ (0.23±0.05)s, CMJ presented lower number of subphases with longer time span

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