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A Physics-based Lumped-charge Model for SiC MPS Diode Implemented in PSPICE

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A Physics-based Lumped-charge Model for SiC MPS Diode Implem...

Workshop on Wide Bandgap Power Devices and Applications in Asia (WiPDA Asia)

作者： Yaoqiang Duan Yingjie Jia Yifei Luo Xin Li Binli Liu School of Electrical and Electronics Engineering Huazhong University of Science and Technology Wuhan China National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan China

ISBN: (纸本)9781538643938

This paper presents a physics-based lumped-charge model for SiC MPS (Merged PiN Schottky) diode. According to the device configuration, the proposed model has been divided into two parts: the bipolar sub-circuit and the unipolar sub-circuit, and each region is modeled by the lumped-charge approach. Then, the model has been implemented into the PSPICE simulator in the form of an equivalent circuit. Besides, for the characterization of surge condition with significant temperature change, the proposed model is also temperature dependent. An accurate lumped thermal model of the module is established by the extraction of structural parameters with a scanning electron microscope. Finally, the model is verified by experiments with Cree CAS300M12BM2 power module, and the electro-thermal co-simulation is carried out.

关键词： Schottky diodes Junctions integrated circuit modeling Mathematical model Silicon carbide Semiconductor device modeling

Edge-epitaxial growth of InSe nanowires toward high-performance photodetectors

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arXiv 2019年

作者： Hao, Song Yan, Shengnan Wang, Yang Xu, Tao Zhang, Hui Cong, Xin Li, Lingfei Liu, Xiaowei Cao, Tianjun Gao, Anyuan Zhang, Lili Jia, Lanxin Long, Mingsheng Hu, Weida Wang, Xiaomu Tan, Pingheng Sun, Litao Cui, Xinyi Liang, Shi-Jun Miao, Feng National Laboratory of Solid-State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chse Academy of Sciences Shanghai200083 China SEU-FEI Nano-Pico Center Key Laboratory of MEMS of Ministry of Education Southeast University Nanjing210096 China State Key Laboratory of Superlattices and Microstructures Institute of Semiconductors College of Materials Science and Opto-Electronic Technology Chinese Academy of Sciences Beijing100083 China School of Electronic Science and Technology Nanjing University Nanjing210093 China State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University Nanjing210046 China

Semiconducting nanowires offer many opportunities for electronic and optoelectronic device applications due to their special geometries and unique physical properties. However, it has been challenging to synthesize semiconducting nanowires directly on SiO2/Si substrate due to lattice mismatch. Here, we developed a catalysis-free approach to achieve direct synthesis of long and straight InSe nanowires on SiO2/Si substrate through edge-homoepitaxial growth. We further achieved parallel InSe nanowires on SiO2/Si substrate through controlling growth conditions. We attributed the underlying growth mechanism to selenium self-driven vapor-liquid-solid process, which is distinct from conventional metal-catalytic vapor-liquid-solid method widely used for growing Si and III-V nanowires. Furthermore, we demonstrated that the as-grown InSe nanowire-based visible light photodetector simultaneously possesses an extraordinary photoresponsivity of 271 A/W, ultrahigh detectivity of 1.57×1014 Jones and a fast response speed of microsecond scale. The excellent performance of the photodetector indicates that as-grown InSe nanowires are promising in future optoelectronic applications. More importantly, the proposed edge-homoepitaxial approach may open up a novel avenue for direct synthesis of semiconducting nanowire arrays on SiO2/Si substrate. Copyright © 2019, The Authors. All rights reserved.

关键词： Nanowires

Hybrid quantum-classical convolutional neural networks

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arXiv 2019年

作者： Liu, Junhua Lim, Kwan Hui Wood, Kristin L. Huang, Wei Guo, Chu Huang, He-Liang Information Systems Technology and Design Singapore University of Technology and Design 8 Somapah Road 487372 Singapore SUTD-MIT International Design Center Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Engineering Product Develoment Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Guangxi Key Laboratory of Optoelectronic Information Processing Guilin University of Electronic Technology Guilin541004 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science and Technology of China Anhui Hefei230026 China Shanghai Branch Cas Ctr. for Excellence and Synergetic Innovation Centre in Quantum Information and Quantum Physics University of Science and Technology of China Anhui Hefei201315 China Henan Key Laboratory of Quantum Information and Cryptography Henan Zhengzhou450000 China

Deep learning has been shown to be able to recognize data patterns better than humans in specific circumstances or contexts. In parallel, quantum computing has demonstrated to be able to output complex wave functions with a few number of gate operations, which could generate distributions that are hard for a classical computer to produce. Here we propose a hybrid quantum-classical convolutional neural network (QCCNN), inspired by convolutional neural networks (CNNs) but adapted to quantum computing to enhance the feature mapping process. QCCNN is friendly to currently noisy intermediate-scale quantum computers, in terms of both number of qubits as well as circuit's depths, while retaining important features of classical CNN, such as nonlinearity and scalability. We also present a framework to automatically compute the gradients of hybrid quantum-classical loss functions which could be directly applied to other hybrid quantum-classical algorithms. We demonstrate the potential of this architecture by applying it to a Tetris dataset, and show that QCCNN can accomplish classification tasks with learning accuracy surpassing that of classical CNN. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic (vol 11, 5172, 2020)

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NATURE COMMUNICATIONS 2020年第1期11卷 5172页

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu Zhu, Biqing Guo, Rui Ke, Piyu Sun, Taochun Lu, Chenxi He, Pan Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Tanaka, Katsumasa Wei, Yiming Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Liu, Miaomiao Breon, Francois-Marie Lu, Yonglong Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing China. zhuliu@***. Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ Centre d'Etudes Orme de Merisiers Gif-sur-Yvette France. Department of Earth System Science Tsinghua University Beijing China. Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park PA USA. Department of Earth System Science University of California Irvine 3232 Croul Hall Irvine CA USA. Division of Geological and Planetary Sciences California Institute of Technology Pasadena CA USA. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing China. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. School of Environment Tsinghua University Beijing China. School of Mathematical School Tsinghua University Beijing China. Department of Mathematical Sciences Tsinghua University Beijing China. Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China. Institut Pierre-Simon Laplace Sorbonne Université / CNRS Paris France. Université Paris Dauphine Place du Maréchal de Lattre de Tassigny 75016 Paris France. Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China. Department of Electrical Engineering the State Key Lab of Control and Simulation of Power Systems and Generation Equipment Institute for National Governance and G

A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5

关键词： Climate sciences Atmospheric science Environmental sciences Environmental social sciences

Anchoring effect of distorted octahedra on the stability and strength of platinum metal pernitrides

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Physical Review Materials 2019年第1期3卷 013603-013603页

作者： Z. H. Fu T. G. Bi S. H. Zhang S. Chen E. Zurek D. Legut T. C. Germann T. Lookman R. F. Zhang School of Materials Science and Engineering Beihang University Beijing 100191 People's Republic of China Center for Integrated Computational Materials Engineering (International Research Institute for Multidisciplinary Science) and Key Laboratory of High-Temperature Structural Materials and Coatings Technology (Ministry of Industry and Information Technology) Beihang University Beijing 100191 People's Republic of China Department of Chemistry State University of New York at Buffalo Buffalo New York 14260-3000 USA IT4Innovations and Nanotechnology Centre VSB-Technical University of Ostrava CZ-70833 Ostrava Czech Republic Theoretical Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA

The successful preparation of platinum metal pernitrides (PmN2) in high-temperature and high-pressure experiments has aroused great scientific interest, since it has long been thought that these systems could not be prepared, and also because of their intriguing mechanical properties. Although it is now widely recognized that PmN2 phases can be stabilized under high pressure, the physical origin explaining their stability remains unknown. By means of high-throughput first-principles schemes, we reveal that the choice of specific space group of these pernitrides at high pressure can be quantified by the anchoring effect of distorted PmN6 octahedra. The competition between baddeleyite and marcasite is attributed uniquely to Pm dimerization, resulting in a profound enhancement of Pm-Pm bonding and N-N π antibonding, while Pm-N bonding plays a secondary role. The observed mechanical strength and atomic deformation mechanism of PmN2 suggest that they are ultraincompressible yet soft. This is attributed to the breaking of elongated Pm-N bonds in the PmN6 octahedra, which is accompanied by a continuous semiconductor-semimetal-metal transition for the semiconducting PmN2 during straining. These findings shed light on the physical origin of high-pressure stabilization and highlight the importance of exploring deformation mechanisms in designing novel strong solids.

关键词： Mechanical & acoustical properties Phase transitions First-principles calculations High-throughput calculations

Sparse Bayesian Learning-Based Adaptive Impedance control in Physical Human-Robot Interaction

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Sparse Bayesian Learning-Based Adaptive Impedance Control in...

IEEE International Conference on Robotics and Biomimetics

作者： Kelin Li Huan Zhao Thanana Nuchkrua Ye Yuan Han Ding State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology China AIM-HI National Chung Cheng University Taiwan Control Group Huazhong University of Science and Technology China

ISBN: (纸本)9781728103785;9781728103778

For the sake of reducing human partner's effort (operating force and time) in human-robot interaction (HRI), it is of significant importance for robot to modify its impedance parameters dynamically based on human intention. Thus, in this paper, a data-driven adaptive impedance control (AIC) scheme is proposed, including a Sparse Bayesian learning-based (SBL) human intention predictor (HIP) and a variable impedance controller (VIC). And it works as follows: First, HIP is proposed to predict human partner's future intention by using necessary time-series data. Then, the predicted intention is used as an input to modulate impedance parameters by VIC. Thus, the dynamic characteristics of robot is suitable for operator's coming actions. Based on this, robot can adaptively comply to human partner better. The proposed method is verified by simulation on a 2 degrees of freedom (DOF) robot and experiments on a 6-DOF UR5 robot. Results reveal the feasibility and effectiveness of the proposed scheme in interaction process.

关键词： Impedance Robots Mathematical model Hidden Markov models Damping Bayes methods Human-robot interaction

Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: A retrospective study

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arXiv 2020年

作者： Xu, Bing Wang, Jinfeng Li, Zhongjie Xu, Chengdong Liao, Yilan Hu, Maogui Yang, Jing Lai, Shengjie Wang, Liping Yang, Weizhong State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Sino-Danish College University of Chinese Academy of Sciences Beijing China Key Laboratory of Surveillance and Early-Warning on Infectious Disease Chinese Center for Disease Control and Prevention Beijing China School of Population Medicine & Public Health Chinese Academy of Medical Sciences/Peking Union Medical College Beijing China Sino-Danish Center for Education and Research Beijing China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing China National Engineering Research Center for Information Technology in Agriculture Beijing China WorldPop School of Geography and Environmental Science University of Southampton Southampton United Kingdom State KeyLaboratory of Resources andEnvironmental InformationSystem Institute of GeographicSciences and Natural ResourcesResearch Chinese Academy ofSciences Beijing100101 China

Background Acute lower respiratory infections (ALRIs) caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses, especially respiratory syncytial virus (RSV) and influenza virus. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. Methods We analysed monthly virus data on patients hospitalised with ALRI from 81 sentinel hospitals in 22 provinces in mainland China from Jan 1, 2009, to Sept 30, 2013. We considered seven common respiratory viruses: RSV, influenza virus, human parainfluenza virus, adenovirus, human metapneumovirus, human bocavirus, and human coronavirus. Meteorological data of the same period were used to analyse relationships between virus seasonality and seven meteorological factors according to region (southern vs northern China). The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs, on the respiratory viruses. Findings 28 369 hospitalised patients with ALRI were tested, 10 387 (36·6%) of whom were positive for at least one virus, including RSV (4091 [32·0%] patients), influenza virus (2665 [20·8%]), human parainfluenza virus (2185 [17·1%]), adenovirus (1478 [11·6%]), human bocavirus (1120 [8·8%]), human coronavirus (637 [5·0%]), and human metapneumovirus (615 [4·8%]). RSV and influenza virus had annual peaks in the north and biannual peaks in the south. Human parainfluenza virus and human bocavirus had higher positive rates in the spring–summer months. Human metapneumovirus had an annual peak in winter–spring, especially in the north. Adenovirus and human coronavirus exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power on m

关键词： Atmospheric pressure

Model-independent reconstruction of f(T) gravity from Gaussian Processes and alleviation of the H0 tension

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arXiv 2019年

作者： Cai, Yi-Fu Khurshudyan, Martiros Saridakis, Emmanuel N. Department of Astronomy School of Physical Sciences University of Science and Technology of China Hefei Anhui230026 China CAS Key Laboratory for Research in Galaxies and Cosmology University of Science and Technology of China Hefei Anhui230026 China School of Astronomy and Space Science University of Science and Technology of China Hefei Anhui230026 China Campus UAB Carrer de Can Magrans s/n Cerdanyola del Valles Barcelona08193 Spain International Laboratory for Theoretical Cosmology Tomsk State University of Control Systems and Radioelectronics Tomsk634050 Russia Department of Physics National Technical University of Athens Zografou Campus GR Athens157 73 Greece

We apply Gaussian processes and Hubble function data in f(T) cosmology, to reconstruct for the first time the f(T) form in a model-independent way. In particular, using H(z) datasets coming from cosmic chronometers as well as from the radial BAO method, alongside the latest released local value H0 = 73.52 ± 1.62 km/s/Mpc, we reconstruct H(z) and its derivatives, resulting eventually in a reconstructed region for f(T), without any assumption. Although the cosmological constant lies in the central part of the reconstructed region, the obtained mean curve follows a quadratic function. Inspired by this we propose a new f(T) parametrization, i.e. f(T) = −2Λ + ξT 2, with ξ the sole free parameter that quantifies the deviation from ΛCDM cosmology. Additionally, we confront three viable one-parameter f(T) models of the literature, which respectively are the power-law, the square-root exponential, and the exponential one, with the reconstructed f(T) region, and then we extract significantly improved constraints for their model parameters, comparing to the constraints that arise from usual observational analysis. Finally, we argue that since we are using the direct Hubble measurements and the local value for H0 in our analysis, with the above reconstruction of f(T), the H0 tension can be efficiently alleviated. Copyright © 2019, The Authors. All rights reserved.

关键词： Cosmology

Piezoelectric thermoelastic dissipation research of piezoelectric harvester under different vibration

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Piezoelectric thermoelastic dissipation research of piezoele...

2018 2nd International Conference on Electronic Information technology and Computer Engineering (EITCE 2018)

作者： Yuting Liu Jiahao Deng Yong Ye Zhuo Hou Zuodong Duan Sha Xu School of Mechatronical Engineering Beijing Institute of Technology Science and Technology on Electromechanical Dynamic Control Laboratory Beijing Institute of Technology College of Information Engineering Shenzhen University National Key Laboratory of Electronic Measurement Technology North University of China

Piezoelectric materials are widely used to form piezoelectric energy harvesters. Also, the thermoelastic dissipation always influences the energy harvesting efficiency, during the energy harvest process. Therefore, in this paper, we discuss the effect of thermoelastic dissipation on the piezoelectric harvester through numerical calculation, simulation and experiment. The piezoelectric thermoelastic coupling governing equations under different vibration are derived, which are based on the Euler-Bernoulli beam theory, thermal conduction model and piezoelectric field model. Then, the structure frequency shift and thermoelastic damping are studied via numerical calculation and simulation. Meanwhile, we show the influence of the temperature field on the piezoelectric structure under different vibration modes. Furth more, we research the variations of piezoelectric structure thermoelastic dissipation characteristics under different structure geometry sizes. Based on these analyses, the effect of piezoelectric thermoelastic dissipation on the piezoelectric harvester is researched

关键词： Piezoelectric thermoelastic dissipation research of piezoelectric harvester under different vibration