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Growth windows of epitaxial NbNx films on c-plane sapphire and their structural and superconducting properties

Physical Review materials 2023年第7期7卷 074803-074803页

作者： John G. Wright Huili Grace Xing Debdeep Jena Department of Materials Science and Engineering Kavli Institute for Nanoscale Science and School of Electrical and Computer Engineering Cornell University Ithaca New York 14853 USA

NbN films are grown on c-plane sapphire substrates by molecular beam epitaxy. The structural and superconducting properties of the films are characterized to demonstrate that growth parameters such as substrate temperature and active nitrogen flux affect the structural phase of films, and thereby the superconducting critical temperature. Four phases of NbN are identified for films grown in different conditions. We demonstrate that atomically flat and highly crystalline β−Nb2N films can be grown at substrate temperatures of 1100∘C or higher, and that the superconducting critical temperature of phase-pure β−Nb2N films is 0.35

关键词： electrical conductivity electrical properties Crystal structures Superconductors Thin films Epitaxy Molecular beam epitaxy

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Photo-induced macro/mesoscopic scale ion displacement in mixed-halide perovskites:ring structures and ionic plasma oscillations

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Light(science & Applications) 2022年第10期11卷 2388-2398页

作者： Xiaoxiao Sun Yong Zhang Weikun Ge Laboratory for Thin Films and Photovoltaics Empa-Swiss Federal Laboratories for Materials Science and Technology8600 DuebendorfSwitzerland Department of Information Technology and Electrical Engineering ETH Zurich8093 ZurichSwitzerland Institute of Ion Beam Physics and Materials Research Helmholtz-Zentrum Dresden-RossendorfDresden 01328Germany Department of Electrical and Computer Engineering The University of North Carolina at CharlotteCharlotteNC 28223USA Department of Physics Tsinghua UniversityBeijing 10084People's Republic of China

Contrary to the common belief that the light-induced halide ion segregation in a mixed halide alloy occurs within the illuminated area,we find that the Br ions released by light are expelled from the illuminated area,which generates a macro/mesoscopic size anion ring surrounding the illuminated area,exhibiting a photoluminescence *** intriguing phenomenon can be explained as resulting from two counter-balancing effects:the outward diffusion of the light-induced free Br ions and the Coulombic force between the anion deficit and surplus *** after removing the illumination,the macro/mesoscopic scale ion displacement results in a built-in voltage of about 0.4 V between the ring and the ***,the displaced anions return to the illuminated area,and the restoring force leads to a damped ultra-low-frequency oscillatory ion motion,with a period of about 20-30 h and lasting over 100 *** finding may be the first observation of an ionic plasma oscillation in *** understanding and controlling the"ion segregation"demonstrate that it is possible to turn this commonly viewed"adverse phenomenon"into novel electronic applications,such as ionic patterning,self-destructive memory,and energy storage.

关键词： mixed removing return

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Ultrastrong Light-Matter and Matter-Matter Coupling

Ultrastrong Light-Matter and Matter-Matter Coupling

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO/PR 2022

作者： Kono, Junichiro Department of Electrical and Computer Engineering Department of Physics and Astronomy Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

This talk will describe our recent studies of light-matter and matter-matter coupling phenomena in condensed matter in the ultrastrong coupling regime. © IEEE 2022.

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Effects of Encapsulant Properties on the Thermo-Mechanical Reliability of Double-Side Cooled Power Modules for Traction Inverters

Effects of Encapsulant Properties on the Thermo-Mechanical R...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Boshkovski, Filip Nicholas, Carl Zhang, Zichen Paret, Paul Ngo, Khai. D. T. Lu, Guo-Quan Virginia Tech Department of Materials Science and Engineering Blacksburg United States Virginia Tech Cpes Bradley Department of Electrical and Computer Engineering Blacksburg United States National Renewable Energy Laboratory GoldenCO United States

ISBN: (纸本)9798350316445

Double-side cooled power modules are being developed for next-generation traction inverters due to their better heat extraction, lower profile, and lower parasitic inductances. However, due to their rigid structure, they cause reliability concerns arising from high thermo-mechanical stresses at the interconnection joints in the module. In this work, a materials-based approach using rigid encapsulants is presented for reducing thermo-mechanical fatigue. Finite-element thermo-mechanical simulations were performed to examine the effects of the elastic modulus and coefficient of thermal expansion of epoxy-based encapsulants on the bond deformation inside a double-side cooled power module. It was found that a rigid encapsulant with a high modulus of 6.0 GPa or above and a coefficient of thermal expansion around 20 ppm/°C would improve the thermo-mechanical reliability of double-side cooled power modules by decreasing the permanent bond deformation inside the modules by 50-60%. © 2023 IEEE.

关键词： double-side cooled modules rigid encapsulants thermo-mechanical reliability

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Ultrastable supported oxygen evolution electrocatalyst formed by ripening-induced embedding

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science (New York, N.Y.) 2025年第6735期387卷 791-796页

作者： Shi, Wenjuan Shen, Tonghao Xing, Chengkun Sun, Kai Yan, Qisheng Niu, Wenzhe Yang, Xiao Li, Jingjing Wei, Chenyang Wang, Ruijie Fu, Shuqing Yang, Yong Xue, Liangyao Chen, Junfeng Cui, Shiwen Hu, Xiaoyue Xie, Ke Xu, Xin Duan, Sai Xu, Yifei Zhang, Bo State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular Science Fudan University Shanghai China Collaborative Innovation Center of Chemistry for Energy Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials MOE Key Laboratory of Computational Physical Sciences Department of Chemistry Fudan University Shanghai China Department of Chemistry and Department of Electrical and Computer Engineering Northwestern University Evanston IL United States Hefei National Laboratory Hefei China

The future deployment of terawatt-scale proton exchange membrane water electrolyzer (PEMWE) technology necessitates development of an efficient oxygen evolution catalyst with low cost and long lifetime. Currently, the stability of the most active iridium (Ir) catalysts is impaired by dissolution, redeposition, detachment, and agglomeration of Ir species. Here we present a ripening-induced embedding strategy that securely embeds the Ir catalyst in a cerium oxide support. Cryogenic electron tomography and all-atom kinetic Monte Carlo simulations reveal that synchronizing the growth rate of the support with the nucleation rate of Ir, regulated by sonication, is pivotal for successful synthesis. A PEMWE using this catalyst achieves a cell voltage of 1.72 volts at a current density of 3 amperes per square centimeter with an Ir loading of just 0.3 milligrams per square centimeter and a voltage degradation rate of 1.33 microvolts per hour, as demonstrated by a 6000-hour accelerated aging test.

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Machine Learning for Unmanned Aerial Vehicles Navigation: An Overview

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SN computer science 2024年第2期5卷 256页

作者： Fagundes-Junior, Leonardo A. de Carvalho, Kevin B. Ferreira, Ricardo S. Brandão, Alexandre S. Núcleo de Especialização em Robótica Department of Electrical Engineering Graduate Program in Computer Science Federal University of Viçosa-UFV Av. Petter Henry Rolfs MG Viçosa 36570-900 Brazil

Unmanned aerial vehicles (UAVs) are a valuable source of data for a wide range of real-time applications, due to their functionality, availability, adaptability, and maneuverability. Working as mobile sensors, they can provide a cost-effective solution for extremely complex tasks, such as inspection, air-to-ground communications, search and rescue, surveillance, among others. Nevertheless, the robots needs to navigate in quite distinct environments and in different dynamism levels, usually facing unpredicted situations, very often using limited sensing and computing capabilities. A large number of solutions to this problem has been featured by the scientific community in the last years, some of them based on machine-learning (ML) methods. Due to its great capability to deal with big data and complexity, as well as its speedy and high-accuracy processing, the ML framework has been used to improve existing technologies and control techniques. In this context, its adoption in several UAV navigation strategies is expected to provide solutions for various problems where UAVs are used in real-time applications. Thus, in order to contextualize the most recent advances, this work provides a detailed survey of relevant researches in which ML techniques have been used in UAV navigation to improve some functional aspects, such as energy-efficiency, communication, execution time, resource management, obstacle avoidance, and path planning. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Autonomous navigation Path planning UAV-based solutions Visual-based navigation

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Meta-optic accelerators for object classifier

Meta-optic accelerators for object classifier

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Zheng, Hanyu Liu, Quan Zhou, You Kravchenko, Ivan I. Huo, Yuankai Valentine, Jason Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37212 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37212 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37212 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in a high-speed and robust classifier with 93.1% accurac...

ISBN: (纸本)9781957171258

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SODIUM-ION BATTERY CYCLE LIFE PREDICTION USING MACHINE LEARNING

SODIUM-ION BATTERY CYCLE LIFE PREDICTION USING MACHINE LEARN...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Liu, Linfeng Juwono, Filbert H. Wong, W.K. Purwanto, Erick Jin, Tingyan Zhen, Yuyang Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Department of Computing Xi'an Jiaotong-Liverpool University Suzhou China School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing China School of Instrument Science and Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781837242689

In this study, we explore the classification and prediction capabilities of three models-Genetic programming (GP), Logistic Regression (LR), and the Kolmogorov-Arnold Network (KAN)-on the task of sodium-ion battery life prediction. By leveraging a dataset composed of multiple battery characteristics, we aim to determine the remaining power of sodium-ion batteries using these machine learning models. The KAN model, being a novel approach, demonstrates superior performance across various metrics, including accuracy, precision, recall, and F1 score, when compared to the other two models. This highlights the potential of KAN as a robust model for complex classification tasks in the field of battery life prediction. © The Institution of engineering & Technology 2024.

关键词： Genetic programming

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Optical Fiber Temperature Sensors Embedded in a Metal Casting Mold 27

Optical Fiber Temperature Sensors Embedded in a Metal Castin...

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27th International Conference on Optical Fiber Sensors, OFS 2022

作者： Roman, Muhammad Balogun, Damilola Bartlett, Laura O'Malley, Ronald J. Gerald, Rex E. Huang, Jie Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO United States Department of Materials Science and Engineering Missouri University of Science and Technology RollaMO United States

We present a dip testing setup, which employs a copper mold instrumented with high resolution distributed fiber-optic sensors, to precisely map closely spaced thermal features that are imparted to the mold during stee... 详细信息

ISBN: (纸本)9781957171142

关键词： Fiber optic sensors

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Meta-optic accelerators for object classification

Meta-optic accelerators for object classification

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2023 Flat Optics: Components to Systems, FLatOptics 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in high-speed classifiers that are demonstrated for hand... 详细信息

ISBN: (纸本)9781957171289

关键词： Imaging systems Machine vision Neural networks Optical components Optical neural systems Optical systems

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