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IEEE Electron devices technology and Manufacturing Conference (EDTM)

作者： Wei Guo Guangzhong Jian Feihong Wu Kai Zhou Guangwei Xu Xuanze Zhou Qiming He Xiaolong Zhao Shibing Long School of Microelectronics University of Science and Technology of China Hefei China Key Laboratory of Microelectronics Devices and Integration Technology Institute of Microelectronics of Chinese Academy of Sciences Beijing China

The β-Ga2O3 Schottky barrier diode (SBD) is fabricated and actualized a breakdown voltage of 472 V. A SPICE model for β-Ga2O3 Sbd is derived from experimental results and applied to DC-DC converter circuit simulatio... 详细信息

ISBN: (纸本)9781728181769;9781728181776

The β-Ga₂O₃ Schottky barrier diode (SBD) is fabricated and actualized a breakdown voltage of 472 V. A SPICE model for β-Ga₂O₃ Sbd is derived from experimental results and applied to DC-DC converter circuit simulation. Then the β-Ga₂O₃ SBD is implemented in a DC-DC converter circuit and acquired the conversion efficiency of 94.8%, indicating the great potential of Ga₂O₃-based devices and circuits.

关键词： Schottky diodes Electric potential Circuit simulation Schottky barriers DC-DC power converters Packaging SPICE

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Polarization tunable bidirectional photoresponse in Van der Waals α−In2Se3/NbX2 (X=S,Se,andTe) ferroelectric diodes

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Physical Review Materials 2023年第8期7卷 084412-084412页

作者： Shibo Fang Qiuhui Li Chen Yang Baochun Wu Shiqi Liu Jie Yang Jiachen Ma Zongmeng Yang Kechao Tang Jing Lu State Key Laboratory for Mesoscopic Physics and School of Physics Peking University Beijing 100871 People's Republic of China State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100871 People's Republic China Key Laboratory of Spintronics Materials Devices and Systems of Zhejiang Province Hangzhou 311305 People's Republic of China Key Laboratory of Material Physics School of Physics and Microelectronics Ministry of Education Zhengzhou University Zhengzhou 450001 People's Republic of China Research Center for Materials Architectures and Integration of Nanomembranes (MAIN) Chemnitz University of Technology 09126 Chemnitz Germany School of Integrated Circuits Peking University Beijing 100871 People's Republic of China Collaborative Innovation Center of Quantum Matter Beijing 100871 People's Republic of China Beijing Key Laboratory for Magnetoelectric Materials and Devices (BKL-MEMD) Peking University Beijing 100871 People's Republic of China Peking University Yangtze Delta Institute of Optoelectronics Nantong 226010 People's Republic of China Key Laboratory for the Physics and Chemistry of Nanodevices Peking University Beijing 100871 People's Republic of China

Ferroelectric diodes can generate a polarization-controlled bidirectional photoresponse to simulate inhibition and promotion behaviors in the artificial neuromorphic system with fast speed, high energy efficiency, and nonvolatility. However, the existing ferroelectric diodes based on ferroelectric oxides suffer from a weak bidirectional photoresponse (below 1 mA/W), difficult miniaturization, and a large response photon energy (over 3 eV). Here, we design a series of van der Waals α−In2Se3/NbX2 (X = S, Se, and Te) ferroelectric diodes with bidirectional photoresponse by using ab initio quantum transport simulation. These devices show a maximum bidirectional photoresponse of 30 (−19) mA/W and a minimum response photon energy of 1.3 eV at the monolayer thickness. Our work shows advanced optoelectronic applications of the van der Waals ferroelectric diodes in the future artificial neuromorphic system.

关键词： Ferroelectricity First-principles calculations Photocurrent 2-dimensional systems Diodes Ferroelectrics Density functional theory Landauer formula

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Structural phase transition of monochalcogenides investigated with machine learning

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Physical Review B 2022年第9期105卷 094116-094116页

作者： J. Zhang F. Zhang D. Wei L. Liu X. Liu D. Fang G. X. Zhang X. Chen D. Wang School of Microelectronics & State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 China Key Lab of Micro-Nano Electronics and System Integration of Xi'an City Xi'an Jiaotong University Xi'an 710049 China Guangxi Key Laboratory of Optical and Electronic Materials and Devices College of Materials Science and Engineering Guilin University of Technology Guilin 541004 China Engineering Research Center of Nanoelectronic Integration and Advanced Equipment Ministry of Education School of Physics and Electronic Science East China Normal University Shanghai 200062 China MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter School of Physics Xi' an Jiaotong University Xi'an 710049 China School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China Department of Applied Physics Aalto University Espoo 00076 Finland

As machine learning becomes increasingly important in science and engineering, it holds the promise to provide a universal approach applicable to various systems to investigate their crystalline phase transitions. Here, we build and train accurate artificial neural networks that can distinguish tiny energy difference, which is crucial to predict the crystalline phase transitions. Employing the trained artificial neural networks in Monte Carlo simulations as the surrogate energy function, we apply this approach to monochalcogenides, including bulk and two-dimensional monolayer SnTe and GeTe, investigating their crystalline phase transitions. The machine-learning approach, when viewed as providing a universal mathematical structure, can be transferred to the investigation of other materials when the training data set generated with ab initio methods are available. Moreover, the machine-learning approach resolves the difficulties associated with constructing the effective Hamiltonian for monochalcogenides, showing great potential with its accuracy and efficiency.

关键词： Ferroelectricity Structural phase transition Chalcogenides Machine learning

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Development and characterization of a dual-fiber Raman probe for accurate and rapid endometrial carcinoma detection

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Biomedical Optics Express 2025年第7期16卷 2914-2922页

作者： Xun Chen Zhaoqin Yang Yi Wang Luping Zhang Limin Feng Jing Chen Shijie Zhu Rongxin Fu Shangran Xie Zhiwei Huang Shuhua Yue Key Laboratory of Biomechanics and Mechanobiology (Beihang University) Ministry of Education Key Laboratory of Innovation and Transformation of Advanced Medical Devices Ministry of Industry and Information Technology National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering) School of Biological Science and Medical Engineering School of Engineering Medicine Beihang University Beijing 100191 China Department of Obstetrics & Gynecology Beijing Tiantan Hospital Capital Medical University Beijing 100050 China Su Zhou Surgi-Master High Tech Co. Ltd. Suzhou 215626 China School of Medical Technology Zhengzhou Research Institute Engineering Research Center of Integrated Acousto-opto-electronic Microsystems (Ministry of Education of China) Chongqing Institute of Microelectronics and Microsystems Beijing Institute of Technology Beijing 100081 China School of Optics and Photonics Beijing Institute of Technology Beijing 100081 China Optical Bioimaging Laboratory Department of Biomedical Engineering Faculty of Engineering National University of Singapore 117576 Singapore National University of Singapore (Suzhou) Research Institute Suzhou Jiangsu 215123 China NUS Graduate School for Integrative Sciences and Engineering Programme (ISEP) National University of Singapore 119077 Singapore

We report on the development and characterization of a dual-fiber optic Raman probe for enhancing real-time endometrial carcinoma biopsy. The fiber optic probe was designed with two miniaturized coating fibers with an outer diameter (OD) of 3.1 mm. We demonstrate that with the use of the Raman probe associated with the background subtraction algorithms, high-quality tissue Raman spectra covering the fingerprint (FP) (500−1800cm −1 ) can be acquired from different tissue types (e.g., muscle, fat, parathyroid gland, and thyroid gland). Using an anti-reflection coating filter and background subtraction algorithms, our probe has better signal-to-noise (SNR) than a conventional coating probe with a comparable OD. Meanwhile, our probe has less OD and 58% SNR compared with the handheld probe (OD = 10 mm). We developed a Raman fiber probe with a small outer diameter and high SNR (>90 in fat) simultaneously and used the small-size probe for accurate and rapid endometrial carcinoma detection. Specifically, a total of 220 fingerprint Raman spectra was obtained from 22 endometrial carcinoma (EC) patients (benign: 10, malignant: 12) and divided into two batches (110 spectra from 11 patients for each) from different patients for robustness test. The mean area under the receiver operating characteristic curves (AUC) for differentiating benign and malignant EC reached 0.946, with a mean accuracy of 93.1% and a mean time expense of 5 seconds by the ResNet model. Furthermore, the specific Raman features corresponding to biomolecules (e.g., amide I II, lipid, and collagen) were found to contribute to the accurate classification.

关键词： Augmented reality Fiber tapers Multimode fibers Optical filters Raman spectroscopy Single mode fibers

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Self-powered solar-blind photodiodes based on EFG-grown(100)-dominant β-Ga_(2)O_(3) substrate

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Chinese Physics B 2021年第1期30卷 483-486页

作者： Xu-Long Chu Zeng Liu Yu-Song Zhi Yuan-Yuan Liu Shao-Hui Zhang Chao Wu Ang Gao Pei-Gang Li Dao-You Guo Zhen-Ping Wu Wei-Hua Tang Laboratory of Information Functional Materials and Devices School of Science&State Key Laboratory of Information Photonics and Optical CommunicationsBeijing University of Posts and TelecommunicationsBeijing 100876China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China The Engineering Research Center for Semiconductor Integrated Technology Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China China Aerospace System Simulation Technology Co. Ltd.(Beijing)Beijing 100195China Division of Interdisciplinary and Comprehensive Research&Platform for Characterization and Test Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China Center for Optoelectronics Materials and Devices&Key Laboratory of Optical Field Manipulation of Zhejiang Province Department of PhysicsZhejiang Sci-Tech UniversityHangzhou 310018China School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026China College of Electronic and Optical Engineering&College of Microelectronics Nanjing University of Posts and TelecommunicationsNanjing 210046China National and Local Joint Engineering Laboratory for RF Integration and Micro-Packing Technologies Nanjing University of Posts and TelecommunicationsNanjing 210046China

We report the edge-defined-film-fed(EFG)-grown β-Ga_(2)O_(3)-based Schottky *** device has a reverse leakage current of ~nA and a rectified ratio of ~10^(4) at ±5 *** addition,the photodiode detector shows a dark current of 0.3 pA,a photo-responsivity(R) of 2.875 mA/W,a special detectivity(D*) of 10^(10) Jones,and an external quantum efficiency(EQE) of 1.4% at zero bias,illustrating a self-powered *** work may advance the development of the Ga_(2)O_(3)-based Schottky diode solar-blind photodetectors.

关键词： β-Ga_(2)O_(3)substrate Schottky photodiode solar-blind detection

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Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network

arXiv

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arXiv 2024年

作者： Xie, Jiayi Li, Hongfeng Cheng, Jin Cai, Qingrui Tan, Hanbo Zu, Lingyun Qu, Xiaobo Han, Hongbin The Department of Automation Tsinghua University Beijing100084 China Institute of Medical Technology Peking University Health Science Center Beijing100191 China The Institute of Medical Technology Peking University Health Science Center Beijing100191 China The School of Mathematical Sciences Fudan University Shanghai200433 China The National Integrated Circuit Industry Education Integration Innovation Platform School of Electronic Science and Engineering National Model Microelectronics College Xiamen University Xiamen361102 China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China The Department of Endocrinology and Metabolism Department of Cardiology Institute of Vascular Medicine Peking University Third Hospital Beijing100191 China Department of Radiology Peking University Third Hospital Beijing100191 China Peking University Third Hospital Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology Beijing100191 China NMPA key Laboratory of Evaluation of Medical Imaging Equipment and Technique Beijing100191 China

The brain extracellular space (ECS), an irregular, extremely tortuous nanoscale space located between cells or between cells and blood vessels, is crucial for nerve cell survival. It plays a pivotal role in high-level brain functions such as memory, emotion, and sensation. However, the specific form of molecular transport within the ECS remain elusive. To address this challenge, this paper proposes a novel approach to quantitatively analyze the molecular transport within the ECS by solving an inverse problem derived from the advection-diffusion equation (ADE) using a physics-informed neural network (PINN). PINN provides a streamlined solution to the ADE without the need for intricate mathematical formulations or grid settings. Additionally, the optimization of PINN facilitates the automatic computation of the diffusion coefficient governing long-term molecule transport and the velocity of molecules driven by advection. Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Péclet number. Experimental validation on two datasets of magnetic resonance images (MRIs) captured at different time points showcases the effectiveness of the proposed method. Notably, our simulations reveal identical molecular transport patterns between datasets representing rats with tracer injected into the same brain region. These findings highlight the potential of PINN as a promising tool for comprehensively exploring molecular transport within the ECS. © 2024, CC BY-NC-SA.

关键词： Molecules

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Structural disorder by octahedral tilting in inorganic halide perovskites: New insight with Bayesian optimization

arXiv

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arXiv 2023年

作者： Li, Jingrui Pan, Fang Zhang, Guo-Xu Liu, Zenghui Dong, Hua Wang, Dawei Jiang, Zhuangde Ren, Wei Ye, Zuo-Guang Todorović, Milica Rinke, Patrick Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education International Center for Dielectric Research School of Electronic Science and Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi’an Jiaotong University Xi’an710049 China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin150001 China Key Laboratory for Physical Electronics and Devices of the Ministry of Education Shaanxi Key Lab of Information Photonic Technique School of Electronic Science and Engineering Xi’an Jiaotong University Xi’an710049 China School of Microelectronics Key Lab of Micro-Nano Electronics and System Integration of Xi’an City Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi’an Jiaotong University Xi’an710049 China Department of Chemistry and 4D LABS Simon Fraser University British Columbia BurnabyV5A 1S6 Canada Department of Mechanical and Materials Engineering University of Turku TurkuFI-20014 Finland Department of Applied Physics Aalto University AALTO P.O.Box 11100 FI-00076 Finland

Structural disorder is common in metal-halide perovskites and important for understanding the functional properties of these materials. First-principles methods can address structure variation on the atomistic scale, but they are often limited by the lack of structure-sampling schemes required to characterize the disorder. In this work, structural disorder in the benchmark inorganic halide perovskites CsPbI3 and CsPbBr3 is computationally studied in terms of the three octahedral-tilting angles. The consequent variation in energetics and properties are described by three-dimensional potential-energy surfaces (PESs) and property landscapes, delivered by Bayesian Optimization Structure Search method with integrated density-functional-theory (DFT) calculations. The rapid convergence of the PES with about 200 DFT data points in three-dimensional searches demonstrates the power of active learning and strategic sampling with Bayesian optimization. Further analysis indicates that disorder grows with increasing temperature, and reveals that the materials band gap at finite temperatures is a statistical mean over disordered structures. © 2023, CC BY.

关键词： Lead compounds

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GaN chips for monitoring density and temperature of lead-acid batteries

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Chip 2025年第3期4卷

作者： Ye, Zhiyong Deng, Ganyuan Liu, Dongmiao Wang, Jingyan Gao, Xiaodi Li, Kwai Hei Zhu, Ling College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen 518060 China School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen University Shenzhen 518060 China State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen 518060 China

Lead-acid batteries are indispensable in various applications, and it is crucial to monitor their status. However, the existing sensing units for lead-acid batteries are limited by their bulky size, slow response time, and lack of temperature sensing and compensation capabilities. In the current work, a compact GaN-based sensing device was proposed to simultaneously measure the electrolyte density and temperature. The device comprises a light-emitting diode (LED) and a photodetector (PD) integrated on a GaN-on-sapphire chip in a monolithic configuration. The forward voltage of the LED reflects the electrolyte temperature, while the photocurrent of the PD varies with electrolyte density due to optical reflection changes at the exposed sapphire interface. The measured signals were processed using a decoupling matrix to achieve temperature compensation. The device exhibits a sensitivity of −29.1 μA/(g/cm³) for density in the range of 1.09 g/cm³ to 1.29 g/cm³, and -1.07 mV/°C for temperature in the range of 25 to 45 °C. The performance of the device was also validated through comparisons with commercial meters and real-time monitoring during the charging and discharging of the batteries. The device has notable advantages in size, cost, and fast response/recovery time (134.3/201.4 ms), rendering it a promising tool for monitoring lead-acid batteries.

关键词： Battery temperature GaN Lead-acid battery density

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Progress of power field effect transistor based on ultra-wide bandgap Ga_2O_3 semiconductor material

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Journal of Semiconductors 2019年第1期40卷 17-25页

作者： Hang Dong Huiwen Xue Qiming He Yuan Qin Guangzhong Jian Shibing Long Ming Liu Key Laboratory of Microelectronic Devices & Integration Technology Institute of Microelectronics of Chinese Academy of Sciences University of Chinese Academy of Sciences School of Microelectronics University of Science and Technology of China

As a promising ultra-wide bandgap semiconductor, gallium oxide(Ga_2O_3) has attracted increasing attention in recent years. The high theoretical breakdown electrical field(8 MV/cm), ultra-wide bandgap(～ 4.8 eV) and large Baliga's figure of merit(BFOM) of Ga_2O_3 make it a potential candidate material for next generation high-power electronics, including diode and field effect transistor(FET). In this paper, we introduce the basic physical properties of Ga_2O_3 single crystal, and review the recent research process of Ga_2O_3 based field effect transistors. Furthermore, various structures of FETs have been summarized and compared, and the potential of Ga_2O_3 is preliminary revealed. Finally, the prospect of the Ga_2O_3 based FET for power electronics application is analyzed.

关键词： gallium oxide(Ga_2O_3) ultra-wide bandgap semiconductor power device field effect transistor(FET)

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12-bit 2.6 GS/s RF DAC based on return-to-zero technology

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The Journal of China Universities of Posts and Telecommunications 2019年第4期26卷 36-42页

作者： Li Xiaopeng Wang Zhigong Zhang Yi Zhang Youtao Zhang Mi Institute of RF and OE ICs Southeast UniversityNanjing 210096China Nanjing Guobo Electronics Company Limited Nanjing 210016China Nanjing Electronic Devices Institute Nanjing 210016China National and Local Joint Engineering Laboratory of RF Integration and Micro-assembly Technology Nanjing 210046China College of Microelectronics Nanjing University of Posts and TelecommunicationsNanjing 210046China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China Science and Technology on Monolithic Intergrated Circuits and Modules Laboratory Nanjing 210016China

A 12-bit 2.6 GS/s radio frequency digital to analog converter(RF DAC)based on 1 um GaAs heterojunction bipolar transistor(HBT)process is *** DAC integrates a 4:1 multiplexer to reduce the data rate of input ports,which greatly facilitates the *** core adopts 4+8 segmented current steering structure.R-2R ladder network is used for 8 least significant bit(LSB)to realize binary current weighting and thermometer coding is used for 4 most significant bit(MSB).Return-to-zero(RZ)technology is used to expand the effective bandwidth of DAC output to the third Nyquist *** proposed DAC has a better output power flatness and spurious-free dynamic range(SFDR).Compared to traditional DAC,measured results demonstrate that the output power of this RZ DAC is increased by 33 dB and the SFDR is enhanced by 27 dB near the second Nyquist band.

关键词： DAC RZ Nyquist band

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