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IEEE International Symposium on Circuits and systems

作者： Yifan Qian Chang Meng Yawen Zhang Weikang Qian Runsheng Wang Ru Huang University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai China Institute of Microelectronics Peking University Beijing China MoE Key Laboratory of Artificial Intelligence Shanghai Jiao Tong University Shanghai China State Key Laboratory of ASIC & System Fudan University Shanghai China

Approximate computing is an emerging circuit design paradigm. It improves the energy efficiency of circuits by introducing some errors. Recent works propose to apply approximate multipliers to design low-power neural network (NN) accelerators. Different from existing methods, in this paper, we advocate a method that integrates approximate logic synthesis (ALS) into the design loop of low-power NN accelerators. ALS automatically synthesizes a good approximate circuit and can take input distribution into consideration. With the help of ALS, the NN computation pattern can be exploited to design an approximate multiplier that fits better with the NN. The experimental results show that the proposed method can generate an extremely small approximate multiplier with area only 4.2% of the accurate version, while it can still achieve a high accuracy of 97.9% for LeNet-5 on MNIST dataset.

关键词： Circuits and systems Approximate computing Artificial neural networks Energy efficiency Circuit synthesis

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The Effect of Device Redundancy in Timeliness of Information

The Effect of Device Redundancy in Timeliness of Information

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IEEE International Conference on Communications (ICC)

作者： Kang Lang Zhengchuan Chen Nikolaos Pappas Howard H. Yang Yunjian Jia Tony Q. S. Quek School of Microelectronics and Communication Engineering Chongqing University Chongqing China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Department of Computer and Information Science Linköping University Linköping Sweden Zhejiang University/University of Illinois at Urbana-Champaign Institute Zhejiang University Haining China Information System Technology and Design Pillar Singapore University of Technology and Design Singapore

Emerging interaction-based Internet of Things (IoT) applications have stringent demand for timeliness, imposing critical challenges to the design of status update system. Using redundant devices to update the status of the same process is a promising way to improve timeliness, but this approach can result in out of order update arrivals, making it difficult to analyze timeliness. To that end, the present paper conducts a theoretical study toward the Age of Information (AoI) of a multi-queue status update system where multiple sensors observe one physical process and update a common monitor. Based on the stochastic hybrid systems method, the average AoI of the considered system is derived in closed form. The theoretical results are consistent with the simulation results, verifying the correctness of the theoretical analysis. It is shown that the logarithm of the average AoI is linearly decreasing with the logarithm of the number of sensors.

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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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Transistor engineering based on 2D materials in the post-silicon era

Nature Reviews Electrical Engineering

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Nature Reviews Electrical Engineering 2024年第5期1卷 335-348页

作者： Senfeng Zeng Chunsen Liu Peng Zhou State Key Laboratory of Integrated Chip and Systems School of Microelectronics Zhangjiang Fudan International Innovation Center Fudan University Shanghai China Frontier Institute of Chip and System Shanghai Key Lab for Future Computing Hardware and System Fudan University Shanghai China

The miniaturization of metal–oxide–semiconductor field-effect transistors (MOSFETs) has been the driving force behind the development of integrated circuits over the past 60 years; however, owing to short channel effect, reducing the gate length of MOSFETs to sub-10 nm represents a fundamental challenge. Two-dimensional materials (2DMs) with atomic scale thicknesses and non-dangling bonds interface enable sub-10 nm scale length, making them suitable candidates for advanced tech nodes beyond sub-3 nm. Although the performance metrics of a single 2DMs transistor have equalled or surpassed those of silicon, leaving no doubt about the potential of 2DMs at the laboratory level, the way of moving 2DMs from ‘lab to fab’ remains unclear. In this Review, we analyse the similarities and differences between 2DMs MOSFETs and silicon MOSFETs in the integrated circuits engineering process; we present potential solutions for channel, contact and dielectric engineering using 2DM to address the scaling challenges faced by a silicon-based device at the advanced tech node. Finally, we summarize the challenges in translating the performance of individual 2DMs devices into large-scale integrated circuits, including large-scale and stable transfer technology, high-quality material synthesis with controllable layers. Once these technical issues are properly solved, 2DMs can take full advantage of their properties at a farther scaling.

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Rapid Synthesis of Fast-Charging TiNb2O7 for Lithium-Ion Storage via Ultrafast Carbothermal Shock

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Micromachines 2025年第5期16卷 490页

作者： Xianyu Hu Yunlei Zhong Xiaosai Hu Xiyuan Feng Fengying Ye State Key Laboratory of ASIC & System School of Microelectronics Fudan University Shanghai 200433 China. Key Laboratory of Multifunctional Nanomaterials and Smart Systems Division of Advanced Materials Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215123 China. College of Textiles and Clothing Yancheng Institute of Technology Yancheng 224051 China. School of Microelectronics Northwestern Polytechnical University No. 1 Dongxiang Road Chang'an District Xi'an 710129 China.

The development of fast-charging lithium-ion batteries urgently requires high-performance anode materials. In this paper, through an ultrafast carbothermal shock (CTS) strategy, titanium niobium oxide (TiNbO, TNO) with an optimized structure was successfully synthesized within 30 s. By regulating the synthesis temperature to 1200 °C, the TNO-1200 material was obtained. Its lattice parameters (a-axis: 17.6869 Å) and unit-cell volume (796.83 Å) were significantly expanded compared to the standard structure (a-axis: 17.51 Å, volume ~790 Å), which widened the lithium-ion migration channels. Rietveld refinement and atomic position analysis indicated that the partial overlap of Ti/Nb atoms and the cooperative displacement of oxygen atoms induced by CTS reduced the lithium-ion diffusion energy barrier. Meanwhile, the cation disorder suppressed the polarization effect. Electrochemical tests showed that after 3000 cycles at a current density of 10 C, the specific capacity of TNO-1200 reached 125 mAh/g, with a capacity retention rate of 98%. EDS mapping confirmed the uniform distribution of elements and the absence of impurity phases. This study provides an efficient synthesis strategy and theoretical basis for the design of high-performance fast-charging battery materials through atomic-scale structural engineering.

关键词： TiNb2O7 fast-charging ultrafast carbothermal shock widened lithium-ion migration channels

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Maxwell-Wagner Relaxations in Ca-, Sm- and Nd-doped Ceria

Research Square

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Research Square 2021年

作者： Ahmed, Rida Wang, Shuting T. ur Rehman, Sajid Sun, Jie Wang, Jin Si, Renjun Zhu, An Kang Yu, Yi Li, Qiuju Wang, Chunchang Laboratory of Dielectric Functional Materials School of Physics & Material Science Anhui University Hefei230601 China High Magnetic Field Laboratory Chinese Academy of Sciences Anhui Hefei230031 China State Key Laboratory of ASIC & System School of Microelectronics Fudan University Shanghai200433 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China

Doped ceria, i.e. Ce1-xMxO2-d with M being dopant metal, has been a focus of great attention for SOFCs due to its high oxygen conduction. In the past literature, the dielectric relaxations in these materials have been ascribed to be caused by defect associates (MCeʺ-Vö) possessing different MCeʺ and Vö distances. But we believe that with changing measurement and analysis techniques it is necessary to invest our time to re-examine the already reported materials and to again take a detailed investigation of the underlying phenomenon behind their dielectric relaxations. Thus, we have used solid-state reaction to prepare Ce1-xMxO2-δ with M=Ca, Sm, and Nd in x=0.1, 0.2, and 0.3 ratios, respectively. The as-prepared and post annealed samples were tested for dielectric properties from 300-1080 K with varying frequencies. The low-temperature relaxation (R1) was argued to be a Maxwell-Wagner relaxation caused by humidity sensitivity. The high-temperature relaxation (R2) was ascribed to be caused by hopping motion of oxygen vacancies. This fact was also supported by detailed analysis of impedance spectra. While, according to the previous reports this relaxation is because of oxygen-vacancy-dopant defect pair. © 2021, CC BY.

关键词： Oxygen vacancies

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Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver

arXiv

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arXiv 2024年

作者： Chen, Hegan Yang, Jichang Chen, Jia Wang, Songqi Wang, Shaocong Wang, Dingchen Tian, Xinyu Yu, Yifei Chen, Xi Lin, Yinan He, Yangu Wu, Xiaoshan Li, Yi Zhang, Xinyuan Lin, Ning Xu, Meng Li, Yi Zhang, Xumeng Wang, Zhongrui Wang, Han Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automation. Recent advances in machine learning provide data-driven methods for developing digital twins using discrete-time data and finite-depth models on digital computers. However, this approach fails to capture the underlying continuous dynamics and struggles with modelling complex system behaviour. Additionally, the architecture of digital computers, with separate storage and processing units, necessitates frequent data transfers and Analogue-Digital (A/D) conversion, thereby significantly increasing both time and energy costs. Here, we introduce a memristive neural ordinary differential equation (ODE) solver for digital twins, which is capable of capturing continuous-time dynamics and facilitates the modelling of complex systems using an infinite-depth model. By integrating storage and computation within analogue memristor arrays, we circumvent the von Neumann bottleneck, thus enhancing both speed and energy efficiency. We experimentally validate our approach by developing a digital twin of the HP memristor, which accurately extrapolates its nonlinear dynamics, achieving a 4.2-fold projected speedup and a 41.4-fold projected decrease in energy consumption compared to state-of-the-art digital hardware, while maintaining an acceptable error margin. Additionally, we demonstrate scalability through experimentally grounded simulations of Lorenz96 dynamics, exhibiting projected performance improvements of 12.6-fold in speed and 189.7-fold in energy efficiency relative to traditional digital approaches. By harnessing the capabilities of fully analogue computing, our breakthrough accelerates the development of digital twins, offering an efficient and rapid solution to meet the demands of Industry 4.0. © 2024, CC BY-NC-SA.

关键词： Energy utilization

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Hydrodynamic constraints on the energy efficiency of droplet electricity generators

arXiv

引用

arXiv 2020年

作者： Wang, Cui Zhou, Jia Riaud, Antoine Xu, Wanghuai Wang, Zuankai State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai200433 China Department of Mechanical Engineering City University of Hong Kong Hong Kong999077 Hong Kong

Electric energy generation from falling droplets has seen a hundred-fold rise in efficiency over the past year. However, even these newest devices can only extract a small portion of the droplet energy. In this paper, we theoretically investigate the contributions of hydrodynamic and electric losses in limiting the efficiency of droplet electricity generators (DEG). Noting that the electromechanical energy conversion occurs during the recoil that immediately follows droplet impact, we identify three limits on existing droplet electric generators: (i) the impingement velocity is limited in order to maintain the droplet integrity;(ii) much of droplet mechanical energy is squandered in overcoming viscous shear force with the substrate;(iii) insufficient electrical charge of the substrate. Of all these effects, we found that up to 83% of the total energy available was lost by viscous dissipation during spreading. Minimizing this loss by using cascaded DEG devices to reduce the droplet kinetic energy may increase future devices efficiency beyond 10%. Copyright © 2020, The Authors. All rights reserved.

关键词： Electric losses

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Effective Lifetime of Non-Equilibrium Carriers in Semiconductors from Non-Adiabatic Molecular Dynamics Simulations

arXiv

引用

arXiv 2022年

作者： Wang, Shanshan Huang, Menglin Wu, Yu-Ning Chu, Weibin Zhao, Jin Walsh, Aron Gong, Xin-Gao Wei, Su-Huai Chen, Shiyou State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai 200433 China Department of Electronics East China Normal University Shanghai 200241 China ICQD/Hefei National Laboratory for Physical Sciences at the Microscale CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics Department of Physics University of Science and Technology of China Anhui Hefei230026 China Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Shanghai Qi Zhi Institute Shanghai 200030 China Beijing Computational Science Research Center Beijing100193 China

The lifetime of non-equilibrium electrons and holes in semiconductors is crucial for solar cell and optoelectronic applications. Non-adiabatic molecular dynamics (NAMD) simulations based on time-dependent density functional theory (TDDFT) are widely used to study excited-state carrier dynamics. However, the calculated carrier lifetimes are often different from experimental results by orders of magnitude. In this work, by revisiting the definition of carrier lifetime and considering different recombination mechanisms, we report a systematic procedure for calculating the effective carrier lifetime in realistic semiconductor crystals that can be compared directly to experimental measurements. The procedure shows that considering all recombination mechanisms and using reasonable densities of carriers and defects are crucial in calculating the effective lifetime. When NAMD simulations consider only Shockey-Read-Hall (SRH) defect-assisted and band-to-band non-radiative recombination while neglect band-to-band radiative recombination, and the densities of non-equilibrium carriers and defects in supercell simulations are much higher than those in realistic semiconductors under solar illumination, the calculated lifetimes are ineffective and thus differ from experiments. Using our procedure, the calculated effective lifetime of the halide perovskite CH3NH3PbI3 agrees with experiments. It is mainly determined by band-to-band radiative and defect-assisted non-radiative recombination, while band-to-band non-radiative recombination is negligible. These results indicate that it is possible to calculate carrier lifetimes accurately based on NAMD simulations, but the directly calculated values should be converted to effective lifetimes for comparison to experiments. The revised procedure can be widely applied in future carrier lifetime simulations. Copyright © 2022, The Authors. All rights reserved.

关键词： Molecular dynamics

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Unijunction Transistor on Silicon-On-Insulator Substrate 15

Unijunction Transistor on Silicon-On-Insulator Substrate

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15th IEEE International Conference on Solid-state and Integrated Circuit Technology, ICSICT 2020

作者： Chen, Y.X. Liu, J. Xiao, K. Zaslavsky, A. Cristoloveanu, S. Liu, F.Y. Li, B. Wan, J. State Key Lab of ASIC and System School of Information Science and Engineering Fudan University Shanghai China Brown University Department of Physics and School of Engineering ProvidenceRI02912 United States IMEP-LAHC INP-Grenoble/Minatec CS 50257 Grenoble38016 France Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China

ISBN: (纸本)9781728162355

A unijunction transistor based on fully-depleted silicon-on-insulator substrate is proposed. The device structure is similar to a junction field effect transistor. By conducting the TCAD simulation, we observe sharp switching and large hysteresis in emitter current-emitter voltage curves with the turn-on voltage linearly controlled by the second base voltage. The operation of the device is mainly determined by the emitter-channel PN junction, which is induced by the backgate voltage. The impact of the backgate voltage on the electrical characteristics is analyzed by changes in the channel potential. © 2020 IEEE.

关键词： Silicon on insulator technology

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