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First-principles study of bulk and two-dimensional structures of the AMnBi family of materials (A=K,Rb,Cs)

Physical Review B 2020年第3期102卷 035444-035444页

作者： Ziming Zhu Chunyan Liao Si Li Xiaoming Zhang Weikang Wu Zhi-Ming Yu Rui Yu Wei Zhang Shengyuan A. Yang Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 China Research Laboratory for Quantum Materials Singapore University of Technology and Design Singapore 487372 Singapore School of Materials Science and Engineering Hebei University of Technology Tianjin 300130 China Key Lab of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) Beijing Key Lab of Nanophotonics & Ultrafine Optoelectronic Systems and School of Physics Beijing Institute of Technology Beijing 100081 China School of Physics and Technology Wuhan University Wuhan 430072 China Fujian Provincial Key Laboratory of Quantum Manipulation and New Energy Materials College of Physics and Energy Fujian Normal University Fuzhou 350117 China School of Physics and Technology Center for Quantum Transport and Thermal Energy Science Nanjing Normal University Nanjing 210023 China

Magnetic materials with high mobilities are intriguing subjects of research from both fundamental and application perspectives. Based on first-principle calculations, we investigate the physical properties of the already synthesized AMnBi (A=K, Rb, Cs) family materials. We show that these materials are antiferromagnetic (AFM), with Néel temperatures above 300 K. They contain AFM ordered Mn layers, while the interlayer coupling changes from ferromagnetic (FM) for KMnBi to AFM for RbMnBi and CsMnBi. We find that these materials are narrow gap semiconductors. Owing to the small effective mass, the electron carrier mobility can be very high, reaching up to 105cm2/(Vs) for KMnBi. In contrast, the hole mobility is much suppressed, typically lower by two orders of magnitude. We further study their two-dimensional (2D) single layer structures, which are found to be AFM with fairly high mobility ∼103cm2/(Vs). Their Néel temperatures can still reach room temperature. Interesting, we find that the magnetic phase transition is also accompanied by a metal-insulator phase transition, with the paramagnetic metal phase possessing a pair of nonsymmorphic-symmetry-protected 2D spin-orbit Dirac points. Furthermore, the magnetism can be effectively controlled by the applied strain. When the magnetic ordering is turned into FM, the system can become a quantum anomalous Hall insulator with gapless chiral edge states.

关键词： Edge states First-principles calculations Magnetic phase transitions Spin-orbit coupling Topological materials Transport phenomena

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Anomaly Detection of Predicted Frames Based on U-Net Feature Vector Reconstruction

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Journal of Physics: Conference Series 2020年第1期1627卷

作者： Yong Qiang Shumin Fei Yiping Jiao Liuwen Li Key Laboratory of Measurement and Control of CSE (Ministry of Education) School of Automation Southeast University Nanjing 210096 China School of Computer Engineering Jinling Institute of Technology Nanjing 211169 China

Anomaly detection in surveillance video scenes is one of the current research hotspots. Due to the small sample collection of anomalous events, the lack of negative sample labeling data training in anomaly detection research adds a lot of difficulties. Therefore, we adopt the method of unsupervised training and improve the method of anomaly detection based on the reconstruction of the potential features of the predicted frame and ground truth based on u-net. We reduce the reconstruction error between the potential features of u-net in the predicted frame and the potential features of the real frame. Then through other constraints, the reconstruction error of the entire predicted frame is minimized according to the generative adversarial training. Due to the use of normal behavior sample training, when the abnormal behavior is detected, the reconstruction error value exceeds the set threshold to judge whether abnormal behavior occurs in the surveillance video. Experiments prove that our improved method is effective and accurate.

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Abnormal Behavior Detection Based on the Potential Field Forces in Surveillance Scenarios

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Journal of Physics: Conference Series 2020年第1期1487卷

作者： Yong Qiang Shumin Fei Liuwen Li Key Laboratory of Measurement and Control of CSE (Ministry of Education) School of Automation Southeast University Nanjing 210096 China School of Computer Engineering Jinling Institute of Technology Nanjing 211169 China

In a social environment, there is a natural mutual force between people. This paper proposes a method for detecting group abnormal behavior based on the potential field method. The movement of a pedestrian is described as the movement towards the target under the combined action of several forces. Forces on pedestrians include the attractive force for themselves and the repulsive force between pedestrians. By calculating the resultant force between them, the behavior of pedestrians is judged according to a set threshold. It is verified through experiments on public data sets that our method has high accuracy and robustness.

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Combinatorial large-area MoS2/Anatase-TiO2 interface: A pathway to emergent optical and opto-electronic functionalities

arXiv

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arXiv 2021年

作者： Maji, Tuhin Kumar Aswin, J.R. Mukherjee, Subhrajit Alexander, Rajath Mondal, Anirban Das, Sarthak Sharma, R.K. Chakraborty, N.K. Dasgupta, K. Sharma, Anjanashree M.R. Hawalder, Ranjit Pandey, Manjiri Naik, Akshay Majumdar, Kausik Pal, Samir Kumar Adarsh, K.V. Ray, Samit Kumar Karmakar, Debjani Department of Chemical Biological and Macromolecular Sciences S.N.Bose National Centre for Basic Sciences Sector III JD Block Kolkata700106 India Department of Physics Indian Institute of Science Education and Research Bhopal462066 India Department of Physics IIT Kharagpur Kharagpur West Bengal721302 India Advanced Carbon Materials Section Bhabha Atomic Research Centre Trombay Mumbai400085 India Department of Electrical Communication Engineering Indian Institute of Science Bangalore560012 India Raja Rammana Centre for Advance Technology Parmanu Nagar Sahkar Nagar Extension 1 CAT Rd Rajendra Nagar Indore Madhya Pradesh45201 India Material Science Division Bhabha Atomic Research Centre Trombay Mumbai400085 India Centre for Nano Science and Engineering Indian Institute of Science Bangalore Karnataka560012 India Centre for Materials for Electronics Technology Off Pashan Road Panchwati Pune411008 India Accelerator Control Division Bhabha Atomic Research Centre Trombay Mumbai400085 India Technical Physics Division Bhabha Atomic Research Centre Trombay400085 India

Interface of transition metal dichalcogenide (TMDC) and high-k dielectric transition metal oxides (TMO) had triggerred umpteen discourses due to the indubitable impact of TMO in reducing the contact resistances and restraining the Fermi-level pinning for the metal-TMDC contacts. In the present work, we focus on the unresolved tumults of large-area TMDC/TMO interfaces, grown by adopting different techniques. Here, on a pulsed laser deposited (PLD) MoS2 thin film, a layer of TiO2 is grown by using both atomic layer deposition (ALD) and PLD. These two different techniques emanate TiO2 layers with different crystalline properties, thicknesses and interfacial morphologies, subsequently influencing the electronic and optical properties of the interfaces. In contrast to the earlier reports of n-type doping for exfoliated MoS2/TiO2 interfaces, large-area MoS2/Anatase-TiO2 films had demonstrated a ptype doping of the underneath MoS2, irrespective of the adopted deposition technique. In addition, they manifest a boost in the extent of p-type doping with increasing thickness of TiO2, as emerged after analyzing the core-level shifts of the X-ray photoelectron spectra (XPS). Density functional analysis of the MoS2/Anatase-TiO2 interfaces, for pristine and in presence of a wide range of interfacial defects, could explain the interdependence of doping and the terminating atomic-surface of TiO2 on MoS2. The theoretical results resemble well with the realistic scenario of large-area growths after incorporating minimization of surface-strain via mutual rotation of the constituent layers. The optical properties of the interface, encompassing the photoluminescence (PL), transient absorption and z-scan two-photon absorption indicate the presence of defect-induced localized mid-gap levels in MoS2/TiO2 (PLD), resulting quenched exciton signals. On the contrary, the relatively defect-free interface in MoS2/TiO2 (ALD) demonstrates a clear presence of both A and B excitons of MoS2. This outc

关键词： Electronic structure

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Deep active learning for efficient training of a LiDAR 3D object detector

arXiv

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arXiv 2019年

作者： Feng, Di Wei, Xiao Rosenbaum, Lars Maki, Atsuto Dietmayer, Klaus Robert Bosch GmbH Corporate Research Driver Assistance Systems and Automated Driving Renningen71272 Germany Institute of Measurement Control and Microtechnology Ulm University Ulm89081 Germany School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

Training a deep object detector for autonomous driving requires a huge amount of labeled data. While recording data via on-board sensors such as camera or LiDAR is relatively easy, annotating data is very tedious and time-consuming, especially when dealing with 3D LiDAR points or radar data. Active learning has the potential to minimize human annotation efforts while maximizing the object detector's performance. In this work, we propose an active learning method to train a LiDAR 3D object detector with the least amount of labeled training data necessary. The detector leverages 2D region proposals generated from the RGB images to reduce the search space of objects and speed up the learning process. Experiments show that our proposed method works under different uncertainty estimations and query functions, and can save up to 60% of the labeling efforts while reaching the same network performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Object detection

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Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

arXiv

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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well. © 2021, CC BY-NC-ND.

关键词： Machine learning

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Author Correction: Enhancing rice production sustainability and resilience via reactivating small water bodies for irrigation and drainage

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Nature communications 2023年第1期14卷 4529页

作者： Sisi Li Yanhua Zhuang Hongbin Liu Zhen Wang Fulin Zhang Mingquan Lv Limei Zhai Xianpeng Fan Shiwei Niu Jingrui Chen Changxu Xu Na Wang Shuhe Ruan Wangzheng Shen Menghan Mi Shengjun Wu Yun Du Liang Zhang Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430077 PR China. Key Laboratory for Environment and Disaster Monitoring and Evaluation of Hubei Wuhan 430077 PR China. University of Chinese Academy of Sciences Beijing 100049 PR China. Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 PR China. State Environmental Protection Key Laboratory of Soil Health and Green Remediation Huazhong Agricultural University Wuhan 430070 PR China. Interdisciplinary Research Center for Territorial Spatial Governance and Green Development Huazhong Agricultural University Wuhan 430070 PR China. Institute of Plant Protection Soil and Fertilizer Sciences Hubei Academy of Agricultural Sciences Wuhan 430064 PR China. Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing 400714 PR China. Liaoning Academy of Agricultural Sciences Shenyang 110161 PR China. Institute of Soil & Fertilizer and Resources & Environment Jiangxi Academy of Agricultural Sciences Nanchang 330200 PR China. Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430077 PR China. lzhang@***. Key Laboratory for Environment and Disaster Monitoring and Evaluation of Hubei Wuhan 430077 PR China. lzhang@***. University of Chinese Academy of Sciences Beijing 100049 PR China. lzhang@***.

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Research on the selection method of FY-3D/MWHTS clear sky observation data based on neural network

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Journal of Physics: Conference Series 2020年第1期1656卷

作者： Qiurui He Xiao Guo Deguang Li Yanling Jin Lanjie Zhang Ruanyu Zhang Luoyang Normal University Luoyang Henan 471934 China Hebi Institute of Engineering and Technology Hebi 451191 China Beijing Information Science and Technology University Beijing 100101 China Shanghai Institute of Aerospace Measurement and Control Communications Shanghai 201109 China

The selection of clear sky data in space-borne remote sensing data is very important for its data application. For FY-3D satellite microwave humidity and temperature sounder (MWHTS), an inversion system of atmospheric cloud water content by MWHTS is established based on neural network. The cloud water content inversion value is used to select clear sky data from MWHTS observation data. The experimental results show that FY-3D/MWHTS clear sky data selection method based on neural network can effectively select MWHTS observation data, thus improving the simulation brightness temperatures accuracy of MWHTS by radiative transfer model. This method can be used to select clear sky data by using space-borne observation data itself. It is easy to operate and has important practical value for climate change research, numerical weather forecast, etc., based on space-borne observation data.

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The Design of a High Precision Capacitive Pressure Sensor Based on Comb Electrode

The Design of a High Precision Capacitive Pressure Sensor Ba...

引用

Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Xuejiao Li Libo Zhao Xiangguang Han Ping Yang Guoxi Luo Nan Zhu Zhikang Li Songli Wang Xin Yan Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Collaborative Innovation Center of Suzhou Nano Science and Technology Xi’an Jiaotong University Xi’an China Flight Automatic and Control Institute Xi’an China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

MEMS capacitive sensors promise wide applications in the field of high precision pressure sensing because of their low temperature drift, low power consumption and high precision. Based on the deformation principle of diaphragm under pressure, we present the design and fabrication process of a novel high precision MEMS capacitive pressure sensor, which consists of island-diaphragm composited structure and comb electrode. Furthermore, a finite element simulation analysis is conducted to demonstrate the excellent performance of the sensor. The simulation results show that the capacitance output non-linearity in load pressure range of 75-125 kPa and 125-200 kPa are 0.083%FS and 0.074%FS, with the sensitivities of 9.3 fF/kPa and 10.6 fF/kPa, respectively.

关键词： Electrodes Pressure sensors Strain Capacitance Silicon Simulation Micromechanical devices

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Design of controllers for T1DM blood Glucose Insulin Dynamics based on Constrained Firefly Algorithm 4

Design of Controllers for T1DM blood Glucose Insulin Dynamic...

引用

4th International Conference on Electrical Energy Systems, ICEES 2018

作者： Shijo, Johnson K. Palani, Thanaraj K. Kumar, S. Senthil Department of Control and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai600119 India Department of Electronics Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai600119 India Electronics and Communication Engineering Tagore Institute of Engineering and Technology Salem India

ISBN: (纸本)9781538636954

In this work, different conventional controller design for the Type-l diabetic blood glucose insulin dynamics are attempted based on the constrained Firefly Algorithm (FA). Blood glucose insulin dynamics based on Bergman Minimal model is studied and implemented which enables the user to simulate and track the behavior of blood glucose levels of diabetic patients with respect to meal disturbance. Here, FA search space is constrained so as to obtain fast convergence in estimating the controller parameters. Integral error based comparisons are conducted on P, PI and PID controllers for selection of best suited controller to be implemented for the simulation. The model response is tested and also compared based on the time domain parameters such as rise time, settling time and peak overshoot to study the effectiveness. In this experimental work, the constrained FA has shown reliable results in tuning the PID controller parameters for proper control of the blood glucose level after meal disturbance. © 2018 IEEE.

关键词： controllers

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