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Optimizing strain response in lead-free(Bi_(0.5)Na_(0.5))TiO_(3)-BaTiO_(3)-NaNbO_(3)solid solutions via ferroelectric/(non-)ergodic relaxor phase boundary engineering

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Journal of Materiomics 2023年第2期9卷 244-255页

作者： Zhe Wang Jinyan Zhao Nan Zhang Wei Ren Kun Zheng Yi Quan Jian Zhuang Yijun Zhang Luyue Jiang Lingyan Wang Gang Niu Ming Liu Zhuangde Jiang Yulong Zhao Zuo-Guang Ye Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education&International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'an710049China School of Microelectronics Xidian UniversityXi'an710071China State Key Laboratory for Mechanical Manufacturing System Xi'an Jiaotong UniversityXi'an710049China Department of Chemistry and 4D LABS Simon Fraser UniversityBurnabyBritish ColumbiaV5A 1S6Canada

Lead-free bismuth sodium titanate(Bi_(0.5)Na_(0.5))TiO_(3)(BNT)and related solid solutions are potential piezoelectric materials for such applications as actuators and transducers if their excellent strain responses and piezoelectric properties can be *** this work,a large strain response of 0.61%is achieved in lead-free(0.94-x%)(Bi_(0.5)Na_(0.5))TiO_(3)-0.06BaTiO_(3)-x%NaNbO_(3)(x=0 e6,BNT-6BT-xNN)ceramics with the composition of x=3.5 in a pseudo-cubic *** of ferroelectric(FE)and relaxor(RE)domain structures is observed in all the unpoled ceramics and the enhanced strain response is believed to be related to the evolution of the ergodic relaxor(ER)and non-ergodic(NR)states thanks to the substitution of antiferroelectric ***-6BT-3.5NN is a critical composition near the FE/NR/ER phase boundary close to room temperature(RT)and its high strain response arises from a synergistic combination of a reversible electric-field-induced phase transition and an active domain switching in the mixed NR/ER *** work provides new insights into the dynamic interplay between mesoscopic domains and macroscopic electrical properties in the BNT-based piezoceramics.

关键词： Lead-free piezoceramics Strain responses Relaxor behavior Domain state Reversible phase transition Phase boundary engineering

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Fabrication of p-MoTe2/n-MoS2 heterostructure and its electrical characterization

Fabrication of p-MoTe2/n-MoS2 heterostructure and its electr...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Xinyu Chen Yangye Sun Ling Tong Simeng Zhang Xiaoxi Li Jingyi Ma Xiaojiao Guo Minxing Zhang Zhengzong Sun Wenzhong Bao State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials Fudan University Shanghai China

We demonstrate the fabrication and characterization of large-area van der Waals heterostructure array composed of chemical vapor deposition (CVD) grown multilayer (ML) 2H-MoTe₂ and single-layer (SL) 2H-MoS₂, which exhibits excellent rectifier properties. The transfer characteristics of field-effect transistors (FETs) are also investigated. Our work acquires excellent homogeneity and device performance, which facilitates the application of two-dimensional (2D) materials in electronics.

关键词： Fabrication Performance evaluation Films Field effect transistors Two dimensional displays Rectifiers Heterojunctions

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Manipulating the Electrical Characteristics of Two-Dimensional Semiconductor Transistors by Gate Engineering

Manipulating the Electrical Characteristics of Two-Dimension...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Jingyi Ma Ling Tong Xiaojiao Guo Xinyu Chen Minxing Zhang Chenjian Wu Wenzhong Bao State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China School of Electronic Information Soochow University Suzhou China

Various methods have been investigated to manipulate the electrical properties of Mos2 transistors to achieve applicable logic levels, which are essential for integrated multistage logic circuits. A doping-free strategy by using metal gates with different work functions is demonstrated to modulate threshold voltage VTH, which is critical for optimizing the matching levels of electrical properties. The optimized inverters show controllable inverter threshold voltages from 0.2 V to 0.6 V and the obtained voltage gain is over 35.

关键词： Performance evaluation Logic circuits Metals Logic gates Threshold voltage Inverters Transistors

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Memristor-Based Bayesian Spiking Neural Network for Ibd Diagnosis

SSRN

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SSRN 2024年

作者： Ma, Jianxia Li, Xiaowen Wu, Qiqiao Chen, Yuanwen Yang, Jianguo Jin, Yang Department of Gastroenterology Hua Dong Hospital FuDan University Shanghai200040 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200438 China State Key Laboratory of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Zhangjiang Lab. Shanghai201210 China

Traditional deep learning methods, such as deep neural networks, have achieved remarkable success in image processing, natural language processing, graph computation, and other fields. However, in the diagnosis of Inflammatory Bowel Disease (IBD), conventional deep learning methods are highly susceptible to generating overconfident results, which can lead to great loss of life and property if it results in misdiagnosis of the patient. In this work, we propose a memristor-based IBD diagnostic system inspired by the idea of variational inference based on Bayes' law. The memristors in our system are used for both synaptic weight storage and entropy sources so that an efficient Bayesian inference system can be realized. Our memristor-based true random number generator can produce probability-tunable bitstreams required for Bayesian inference with a mean-square error that is reduced by 10.9× than that of a conventional pseudo-random generator. The proposed system consists of a coarse-grained and a fined-grained spiking neural network, and an optimized strategy that trims the neuron’s threshold is proposed for maintaining the appropriate model sparsity and reducing information loss. With Bayesian inference, our work achieves lower diagnostic error rates, which are reduced by 10.79% and 0.49% for the coarse-grained and fine-grained networks, respectively. The proposed system is easy to hardware implement and presents a novel solution for community-wide IBD diagnosis. © 2024, The Authors. All rights reserved.

关键词： Mean square error

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Self-supervised On-device Federated Learning from Unlabeled Streams

arXiv

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arXiv 2022年

作者： Shi, Jiahe Wu, Yawen Zeng, Dewen Tao, Jun Hu, Jingtong Shi, Yiyu The State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai200433 China The Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States The Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States

The ubiquity of edge devices has led to a growing amount of unlabeled data produced at the edge. Deep learning models deployed on edge devices are required to learn from these unlabeled data to continuously improve accuracy. Self-supervised representation learning has achieved promising performances using centralized unlabeled data. However, the increasing awareness of privacy protection limits centralizing the distributed unlabeled image data on edge devices. While federated learning has been widely adopted to enable distributed machine learning with privacy preservation, without a data selection method to efficiently select streaming data, the traditional federated learning framework fails to handle these huge amounts of decentralized unlabeled data with limited storage resources on edge. To address these challenges, we propose a Self-supervised On-device Federated learning framework with coreset selection, which we call SOFed, to automatically select a coreset that consists of the most representative samples into the replay buffer on each device. It preserves data privacy as each client does not share raw data while learning good visual representations. Experiments demonstrate the effectiveness and significance of the proposed method in visual representation learning. Copyright © 2022, The Authors. All rights reserved.

关键词： Data privacy

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3d Tubular Graphene Sponge/Pedot:Pss Based Stretchable and Flexible Device for Noninterfering Pressure-Temperature Detection

SSRN

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SSRN 2023年

作者： Zhao, Zeng-Cai Ding, Si-Tong Wen, Xiao-Hong Ma, Hong-Ping Zhao, Xue-Feng School of Science Hangzhou Dianzi University Hangzhou310018 China State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai200433 China Institute of Wide Bandgap Semiconductors and Future Lighting Academy for Engineering & Technology Fudan University Shanghai200433 China

Skin-like pressure- and temperature-sensing capabilities are two important indicators for artificial human skins and flexible wearable sensors. However, artifact interference between measured signals has always been the technical difficulty in realizing multi-parameter real-time and highly sensitive monitoring. Herein, a stretchable and flexible pressure-temperature sensitive device based on 3D tubular graphene sponge/PEDOT:PSS composite is designed and fabricated. The hybrid Ag NWs/CNTs composite based embedded stretchable electrodes is selected as the signal transmission lines, which had the ability to resist tensile strain failure. The pressure-resistance module and the temperature-voltage module exhibits distinguishable features of detecting pressure and temperature stimulus simultaneously. The detection sensitivity of pressure and temperature stimuli is 43 kPa-1 and 24.5 μV/K, respectively. Moreover, a 3×3 sensor array is demonstrated to verify its monitoring effects in static and dynamic surroundings, illustrating its promising applications, such as health monitoring components, biomimetic soft wearable devices and human-machine interaction. © 2023, The Authors. All rights reserved.

关键词： Graphene

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EVDMARL: Efficient Value Decomposition-based Multi-Agent Reinforcement Learning with Domain-Randomization for Complex Analog Circuit Design Migration 24

EVDMARL: Efficient Value Decomposition-based Multi-Agent Rei...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Sun, Handa Bi, Zhaori Jiang, Wenning Lu, Ye Yan, Changhao Yang, Fan Hu, Wenchuang Wang, Sheng-Guo Zhou, Dian Zeng, Xuan State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China School of Microelectronics Fudan University Shanghai China Frontier Institute of Chip and System Fudan University Shanghai China School of Information Science and Technology Fudan University Shanghai China Precision Medicine Center of West China Hospital Sichuan University Chengdu China Department of Et Department of Ece University of North Carolina at Charlotte Charlotte United States Department of Electrical Engineering University of Texas at Dallas RichardsonTX United States University of Texas Dallas United States

ISBN: (纸本)9798400706011

Automated analog circuit design migration significantly alleviates the burden on designers in circuit sizing under various operating conditions. Conventional methods model the migration problem as black-box optimization, requiring excessive iterations of costly simulations to converge. Reinforcement learning exhibits significant promise in transfer learning, as it enables the generation of circuits that fulfill specifications efficiently. The paper proposes a novel value decomposition-based multi-agent reinforcement learning framework, aiming to model complex analog circuits and eliminate the need for manually defined specifications of sub-circuits for new operating conditions. Additionally, it incorporates domain randomization techniques to efficiently generate circuits that meet unforeseen scenarios with minimal simulations. Experiment demonstrates that our algorithm can efficiently generate circuits meeting specifications under new operating conditions in few number of steps, outperforming state-of-the-art methods. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Reinforcement learning

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An efficient batch constrained Bayesian optimization approach for analog circuit synthesis via multi-objective acquisition ensemble

arXiv

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arXiv 2021年

作者： Zhang, Shuhan Yang, Fan Yan, Changhao Zhou, Dian Zeng, Xuan State Key Lab of ASIC & System Microelectronics Department Fudan University China Department of Electrical Engineering The University of Texas Dallas United States

Bayesian optimization is a promising methodology for analog circuit synthesis. However, the sequential nature of the Bayesian optimization framework significantly limits its ability to fully utilize real-world computational resources. In this paper, we propose an efficient parallelizable Bayesian optimization algorithm via Multi-objective ACquisition function Ensemble (MACE) to further accelerate the optimization procedure. By sampling query points from the Pareto front of the probability of improvement (PI), expected improvement (EI) and lower confidence bound (LCB), we combine the benefits of state-of-the-art acquisition functions to achieve a delicate tradeoff between exploration and exploitation for the unconstrained optimization problem. Based on this batch design, we further adjust the algorithm for the constrained optimization problem. By dividing the optimization procedure into two stages and first focusing on finding an initial feasible point, we manage to gain more information about the valid region and can better avoid sampling around the infeasible area. After achieving the first feasible point, we favor the feasible region by adopting a specially designed penalization term to the acquisition function ensemble. The experimental results quantitatively demonstrate that our proposed algorithm can reduce the overall simulation time by up to 74× compared to differential evolution (DE) for the unconstrained optimization problem when the batch size is 15. For the constrained optimization problem, our proposed algorithm can speed up the optimization process by up to 15× compared to the weighted expected improvement based Bayesian optimization (WEIBO) approach, when the batch size is 15. © 2021, CC BY-NC-SA.

关键词： Timing circuits

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A 915MHz $19\mu \mathrm{W}$ Blocker-Enhanced Wake-Up Receiver with Frequency-Hopping Two-Tone Modulation Achieving 53dB Tolerance to In-Band Interference

A 915MHz $19\mu \mathrm{W}$ Blocker-Enhanced Wake-Up Receive...

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IEEE Symposium on Radio Frequency Integrated Circuits (RFIC)

作者： Heyu Ren Dawei Ye Binbin Chen Xu Jin Wenjun Gong Rongjin Xu C.-J. Richard Shi State Key Laboratory of ASIC and System Fudan University China Institute of Brain-inspired Circuits and Systems (iBiCAS) Fudan University China Department of Electrical and Computer Engineering University of Washington USA

ISBN: (数字)9781665496117

ISBN: (纸本)9781665496124

A 915MHz ultra-low-power blocker-enhanced wake- up receiver (BE-WuRx) is presented in a 65nm CMOS process. Employing the proposed frequency-hopping two-tone modulation (FH-TTM), the BE-WuRx can dynamically convert the in-band blocker power to data power, and achieves a −63.6dBm sensitivity without blocker and a −90dBm enhanced sensitivity with a −25dBm CW interferer, while just consuming $\mathbf{19}\mathbf{\mu}\mathbf{W}$ . With the −63.6dBm sensitivity, the BE-WuRx performs 53dB tolerance to the in-band blocker, exhibiting 14dB improvement compared to the case that FH- TTM is off. The wake-up latency is 6.4ms for a quiet channel and 6.4 to 64ms for a congested channel.

关键词： Sensitivity Frequency modulation Amplitude shift keying Receivers Interference Frequency conversion CMOS process

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Tunable Plasmons in Large-Area WTe2 Thin Films

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Physical Review Applied 2021年第1期15卷 014010-014010页

作者： Chong Wang Yangye Sun Shenyang Huang Qiaoxia Xing Guowei Zhang Chaoyu Song Fanjie Wang Yuangang Xie Yuchen Lei Zhengzong Sun Hugen Yan State Key Laboratory of Surface Physics and Department of Physics Fudan University Shanghai 200433 China Key Laboratory of Micro and Nano-Photonic Structures (Ministry of Education) Fudan University Shanghai 200433 China School of Microelectronics and State Key Laboratory of ASIC and System Fudan University Shanghai 200433 China Institute of Flexible Electronics Northwestern Polytechnical University Xi’an 710072 China

The observation of electrically tunable and highly confined plasmons in graphene has stimulated the exploration of interesting properties of plasmons in other two-dimensional materials. Recently, hyperbolic plasmon resonance modes have been observed in exfoliated WTe2 films, a type-II Weyl semimetal with layered structure, providing a platform for the assembly of plasmons with hyperbolicity and exotic topological properties. However, the plasmon modes were observed in relatively thick and small-area films, which restrict the tunability and application for plasmons. Here, large-area (approximately cm) WTe2 films with different thicknesses are grown by the chemical vapor deposition method, in which plasmon resonance modes are observed in films with different thicknesses down to about 8 nm. Hybridization of plasmon and surface polar phonons of the substrate is revealed by mapping the plasmon dispersion. The plasmon frequency is demonstrated to be tunable by changing the temperature and film thickness. Our results facilitate the development of a tunable and scalable WTe2 plasmonic system for revealing topological properties and towards various applications in sensing, imaging, and light modulation.

关键词： Optoelectronics Phonons Plasmonics Topological effects in photonic systems 2-dimensional systems Semimetals Transition metal dichalcogenides Chemical vapor deposition

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