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arXiv 2022年

作者： Yu, Hongyu Hong, Liangliang Chen, Shiyou Gong, Xingao Xiang, Hongjun Institute of Computational Physical Sciences Department of Physics Fudan University Shanghai200433 China Shanghai Qi Zhi Institute Shanghai200030 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai200433 China

Machine Learning (ML) interatomic models and potentials have been widely employed in simulations of materials. Long-range interactions often dominate in some ionic systems whose dynamics behavior is significantly influenced. However, the long-range effect such as Coulomb and Van der Wales potential is not considered in most ML interatomic potentials. To address this issue, we put forward a method that can take long-range effects into account for most ML local interatomic models with the reciprocal space neural network. The structure information in real space is firstly transformed into reciprocal space and then encoded into a reciprocal space potential or a global descriptor with full atomic interactions. The reciprocal space potential and descriptor keep full invariance of Euclidean symmetry and choice of the cell. Benefiting from the reciprocal-space information, ML interatomic models can be extended to describe the long-range potential including not only Coulomb but any other long-range interaction. A model NaCl system considering Coulomb interaction and the GaxNy system with defects are applied to illustrate the advantage of our approach. At the same time, our approach helps to improve the prediction accuracy of some global properties such as the band gap where the full atomic interaction beyond local atomic environments plays a very important role. In summary, our work has expanded the ability of current ML interatomic models and potentials when dealing with the long-range effect, hence paving a new way for accurate prediction of global properties and large-scale dynamic simulations of systems with defects. © 2022, CC BY.

关键词： Defects

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Bayesian Inference on Introduced General Region: An Efficient Parametric Yield Estimation Method for Integrated Circuits

Bayesian Inference on Introduced General Region: An Efficien...

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Asia and South Pacific Design Automation Conference

作者： Zhengqi Gao Zihao Chen Jun Tao Yangfeng Su Dian Zhou Xuan Zeng State Key Lab of ASIC & System School of Microelectronics Fudan University School of Mathematics Fudan University University of Texas at Dallas

ISBN: (数字)9781450379991

ISBN: (纸本)9781728180571

In this paper, we propose an efficient parametric yield estimation method based on Bayesian Inference. By observing that nowadays analog and mixed-signal circuit is designed via a multi-stage flow, and that the circuit performance correlation of early stage and late stage is naturally symmetrical, we introduce a general region to capture the common features of the early and late stage. Meanwhile, two private regions are also incorporated to represent the unique features of these two stages respectively. Afterwards, we introduce classifiers one for each region to explicitly encode the correlation information. Next, we set up a graphical model, and consequently adopt Bayesian Inference to calculate the model parameters. Finally, based on the obtained optimal model parameters, we can accurately and efficiently estimate the parametric yield with a simple sampling method. Our numerical experiments demonstrate that compared to the state-of-the-art algorithms, our proposed method can better estimate the yield while significantly reducing the number of circuit simulations.

关键词： Correlation Graphical models Sampling methods Bayes methods Numerical models Yield estimation Integrated circuit modeling

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Crystal orientation-modulated ferroelectric and dielectric properties in Hf0.5Zr0.5O2 thin films

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Science China(Information Sciences) 2025年第6期 204-212页

作者： Yu-Chun LI Xiao-Xi LI Zhongshan XU Zi-Ying HUANG Yingguo YANG Xiao-Na ZHU Ming LI David Wei ZHANG Hong-Liang LU State Key Laboratory of Application-Specific Integrated Circuit and System Shanghai Institute of Intelligent Electronics and Systems School of Microelectronics Fudan University Zhangjiang Fudan International Innovation Center National Integrated Circuit Innovation Center Wide Bandgap Semiconductor Technology Disciplines State Key Laboratory School of Microelectronics Xidian University Jiashan Fudan Institute School of Integrated Circuits Peking University

Hafnium oxide（HfO2） is a promising ferroelectric material because of its robust electric dipoles at the *** HfO2is an oxygen-displacement-induced ferroelectric material, a comprehensive understanding of the intricate relationship between its electrical performance and oxygen-related processes is still limited. This study delves into the ferroelectric and dielectric properties of Zr-doped HfO2(Hf0.5Zr0.5O2, HZO) thin films, unveiling a reliance on the oxygen dose during the atomic layer deposition process. A superior remanent polarization（2Pr） of 58 μC/cm2and a high dielectric constant of 52.7 are obtained in the HZO capacitors with 10 and 1 s oxygen plasma durations, respectively. Our work establishes that the enhanced ferroelectricity observed in samples with longer oxygen dose time is attributed to the gradual out-of-plane orientation of the polar c-axis, as indicated by grazing incidence wide-angle X-ray scattering analysis. Meanwhile,the larger dielectric constant observed in samples with the shortest oxygen dose time（1 s） originates from the out-of-plane tilt of the b-axis in an orthorhombic-phase cell. These new insights into the controlled crystal orientation through oxygen dose modulation open avenues for optimizing the performance of the HfO2-based devices.

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Bimetallic Aupt Alloy Nanoparticles Decorated on Zno Nanowires Towards Efficient and Selective H2s Gas Sensing

SSRN

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SSRN 2022年

作者： Liu, Yiping Zhu, Liyuan Feng, Pu Dang, Congcong Li, Ming Lu, Hong-Liang Gao, Liming State Key Laboratory of Metal Matrix Composites School of Material Science and Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai200433 China Yiwu Research Institute Fudan University Chengbei Road Zhejiang Yiwu322000 China

Development of high-performance H2S sensor is imperative for monitoring H2S in the living environment. The metal oxide semiconductors (MOSs) have been regarded as the strongest candidates for H2S detection due to their high sensitivity, miniaturization, and good durability. However, a single MOS-based gas sensor is unable to selectively detect gases, which limits its practical application. Functionalization of noble metal nanoparticles (e.g., Pt, Pd, and Au) on the surface of MOS can improve its selectivity. Herein, ZnO nanowires decorated with AuPt bimetallic nanoparticles are designed and fabricated on MEMS for H2S detection. The AuPt@ZnO nanowires-based sensor shows a response of 17.7 to 20 ppm H2S at 300°C which is 4.0 times higher than that of pristine ZnO nanowires-based sensor. The sensor also exhibits rapid response-recovery process, brilliant long-term stability, and excellent selectivity to H2S among various interfering gases. The remarkable improvement of the sensing performance, especially selectivity, could be ascribed to the electronic and chemical sensitization and the synergistic effect of the AuPt bimetal. Thus, the AuPt@ZnO nanowires-based sensor has a great potential application for H2S detection. © 2022, The Authors. All rights reserved.

关键词： Sulfur compounds

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Machine-Learning Modeling of Elemental Ferroelectric Bismuth Monolayer

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Physical Review Letters 2024年第26期133卷 266103-266103页

作者： Yanxing Zhang Xinjian Ouyang Dangqi Fang Shaojie Hu Laijun Liu Dawei Wang School of Physics Henan Normal University Xinxiang 453007 China 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 MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter School of Physics Xi’an Jiaotong University Xi’an 710049 China Department of Physics Kyushu University 744 Motooka Fukuoka 812-8581 Japan Key Laboratory of Nonferrous Materials and New Processing Technology Ministry of Education College of Materials Science and Engineering Guilin University of Technology Guilin 541004 China

The bismuth monolayer has recently been experimentally identified as a novel platform for the investigation of two-dimensional single-element ferroelectric system. Here, we model the potential energy surface of a bismuth monolayer by employing a message-passing neural network and achieve an error smaller than 1.2 meV per atom. Empowered by the high accuracy and fast prediction of the machine learning model, we have embarked on in-depth and large-scale atomistic simulations. These explorations are tailored to understand the temperature-dependent phase transitions, with an emphasis on the difference between free-standing monolayers and those constrained by a substrate. Furthermore, with the large system used in the simulations, we are also able to observe ferroelectric domains within these systems and shed light on their intrinsic lattice thermal conductivity.

关键词： Ferroelectricity

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Ald-Fabricated Two-Dimensional MoO3-WO3 Nanohybrid Thin-Film Electrode for Ultrasensitive and Interference-Free Detection of Dopamine

SSRN

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SSRN 2023年

作者： Lopa, Nasrin Siraj Akbari, Mohammad Karbalaei Lu, Hong Liang Zhuiykov, Serge Ghent University Global Campus Incheon21985 Korea Republic of Department of Solid-Sate Science Faculty of Science Ghent University Krijgslaan 281/S1 GhentB-9000 Belgium State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai200433 China

Atomically thin 2D semiconductors and their hybrid electrodes show great promise in the advancement of neural sensors for detecting neurotransmitters either through implantation on the brain's surface or by direct detection in biological fluids. This research demonstrated the fabrication of a sub-10 nm thick 2D MoO3-WO3 heterostructure electrode via ALD for the first time to detect dopamine (DA). The developed thin-film with uniform surface morphology possessed monoclinic and orthorhombic crystal structures of WO3 and MoO3, respectively, with the existence of oxygen vacancies and their sub-stoichiometric phases. The MoO3-WO3 sensor showed excellent catalytic activity for the interference-free detection of DA by suppressing the redox activity of common interferences, ascorbic acid (AA) and uric acid (UA). The ultra-sensitivity of DA oxidation can be ascribed to the effective electrostatic interaction and chemical coordination between the positively charged DA (at pH 7.0) with the MoO3-WO3. In contrast, the predominant electrostatic repulsive force between the negatively charged AA and UA (at pH 7.0) with the MoO3-WO3 suppressed their electrochemical responses. The sensor showed a nanomolar detection limit (20 nM) and wide linear range for DA detection, which is highly appropriate for its determination in biological samples. Additionally, the sensor demonstrated excellent electrochemical stability, high reproducibility, and good recoveries of DA determination in diluted human serum samples. © 2023, The Authors. All rights reserved.

关键词： Ascorbic acid

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Preparation and characterization of SnO films via reactive sputtering for ambipolar thin-film transistor applications

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Semiconductor Science and Technology 2020年第2期36卷

作者： Huo, Jingyong Wang, Xiaolin Wu, Xiaohan Liu, Wen-Jun Ding, Shi-Jin State Key Laboratory of Asic and System School of Microelectronics Fudan University Shanghai200433 China

SnO films are prepared by reactive magnetron sputtering under various O2 partial pressures along with post-annealing in air. The results indicate that the O2 partial pressure during reactive sputtering process not only influences the composition of the SnO film but also its texture. For the SnO film deposited under 10% O2 partial pressure, its direct bandgap increases from 2.49 to 2.64 eV with elevating the post-annealing temperature from 250 °C to 400 °C. The above SnO-based channel thin-film transistors (TFTs) exhibit a typical ambipolar feature after post-annealing at ≥250 °C in air. For the TFTs annealed at 300 °C for 30 min, the extracted hole and electron field-effect mobility is 1.48 cm2V-1s-1 and 0.21 cm2V-1s-1, respectively. The performance of both p- and n-type TFTs could be further improved by optimizing fabrication process and post-annealing conditions because of a trade-off between hole and electron mobility. © 2020 IOP Publishing Ltd.

关键词： Thin films

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Structural phase transition involving octahedron tilting and ion migration in metal-halide perovskites: A machine-learning study

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Physical Review B 2023年第2期108卷 L020103-L020103页

作者： Xinjian Ouyang Weijia Chen Yanxing Zhang Feng Zhang Yuan Zhuang Xiao Jie Laijun Liu Dawei 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 School of Physics Henan Normal University Xinxiang 453007 China Key Laboratory of Nonferrous Materials and New Processing Technology Ministry of Education College of Materials Science and Engineering Guilin University of Technology Guilin 541004 China

Metal-halide perovskites exhibit excellent optoelectronic properties, making them suitable for various applications. In this work, we propose a novel approach, employing the message-passing neural networks (MPNNs), to model the potential energy surface (PES) of metal-halide perovskites. The MPNN model can learn the PES of perovskites with an error of less than 1 meV per atom, which is comparable to ab initio calculations. With the accurate and fast prediction of the MPNN model, we perform large-scale molecular dynamics simulations for CsPbBr3 and Cs2AgBiBr6, successfully identifying their temperature-dependent octahedron tilting patterns, ion displacement, and structural phases that are crucial to obtaining their electronic structure correctly. We also observe significant Ag migration and vacancy defects in Cs2AgBiBr6, which are further investigated using ab initio calculations, offering insights into its ambient stability. This work provides a comprehensive understanding of the structural phase transition in metal-halide perovskites, as well as information regarding ion migration.

关键词： Structural phase transition Perovskites Density functional calculations Machine learning

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Skipping the boundary layer: high-speed droplet-based immunoassay using Rayleigh acoustic streaming

arXiv

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arXiv 2022年

作者： Wang, Qi Ding, Zhe Wong, Gary Zhou, Jia Riaud, Antoine ASIC and System State Key Laboratory School of Microelectronics Fudan University Shanghai200433 China Viral Hemorrhagic Fevers Research Unit CAS Key Laboratory of Molecular Virology and Immunology Institut Pasteur of Shanghai Chinese Academy of Sciences Shanghai200031 China University of Chinese Academy of Sciences Beijing100049 China

Acoustic mixing of droplets is a promising way to implement biosensors that combine high speed and minimal reagent consumption. To date, this type of droplet mixing is driven by a volume force resulting from the absorption of high-frequency acoustic waves in the bulk of the fluid. Here, we show that the speed of these sensors is limited by the slow advection of analyte to the sensor surface due to the formation of a hydrodynamic boundary layer. We eliminate this hydrodynamic boundary layer by using much lower ultrasonic frequencies to excite the droplet, which drives a Rayleigh streaming that behaves essentially like a slip velocity. Three-dimensional simulations show that this provides a threefold speedup compared to Eckart streaming. Experimentally, we shorten a SARS-CoV-2 antibody immunoassay from 20 min to 40 s. Copyright © 2022, The Authors. All rights reserved.

关键词： Mixing

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Acoustic Radiation Force on Small Spheres Due to Transient Acoustic Fields

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Physical Review Applied 2021年第4期15卷 044034-044034页

作者： Qing Wang Antoine Riaud Jia Zhou Zhixiong Gong Michael Baudoin State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai 200433 China University of Lille CNRS Centrale Lille University Polytechnique Hauts-de-France UMR 8520 – IEMN Lille F-59000 France

Acoustic radiation force is a net force experienced by an object under the action of an acoustic wave. Most theoretical models require the acoustic wave to be periodic, if not purely monofrequency, and are therefore irrelevant for the study of acoustic radiation force due to acoustic pulses. Here, we introduce the concept of finite-duration pulses, which is the most general condition to derive the acoustic radiation force. In the case of small spheres, we extend the Gor’kov formula to unsteady acoustic fields such as traveling pulses and interfering wave packets. In the latter case, our study suggests that the concept of acoustic contrast is also relevant to express the acoustic radiation force. For negative acoustic contrast particles, the acoustic trapping region narrows with shorter pulses, whereas positive contrast particles (such as biological cells) can fall in secondary traps when the pulse width deviates from an optimal value. This theoretical insight may help to improve the selectivity of pulsed acoustic tweezers.

关键词： Acoustic interactions Acoustic wave phenomena Nonlinear acoustics Ultrasonics Optical tweezers Perturbation theory

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