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SSRN 2022年

作者： Wu, Tao Tao Zhu, Liyuan Wu, Xue-Yan Miao, Xiao-Yong Mao, Li-Wen Jin, Xuan-Hong Lu, Hong-Liang State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai 200433 China School of Optical-Electrical & Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China Yiwu Research Institute of Fudan University Chengbei Road Zhejiang Yiwu City322000 China

Hierarchical Nb 2 O 5 @ZnO hetero-branched nanorods used for highly responsive, selective, and stable hydrogen sulfide (H 2 S) sensors were synthesized through a sequential process combining a hydrothermal method, atomic-layer-deposition processing, and modified hydrothermal processing for branching ZnO nanowires. The Nb 2 O 5 @ZnO hetero-branched nanorod sensors exhibited a great response (R a /R g ) of 6.10 towards 20 ppm H 2 S at an optimal working temperature of 400 o C, whose resistance changing rate (~5.10) was 39.2- and 1.9-fold those of Nb 2 O 5 (~0.13) and Nb 2 O 5 @ZnO core-shell nanorod (~2.74) sensors, respectively. The heterojunction formed at the Nb 2 O 5 @ZnO interface and the characteristic reaction between ZnO and H 2 S effectively improved H 2 S sensing performance. Moreover, the branching of ZnO nanowires introduced abundant homojunctions and prominently enlarged the specific surface area, further increasing the response of hetero-branched sensors. Meanwhile, the Nb 2 O 5 @ZnO hetero-branched sensors maintained steady performance over a month, indicating good stability and repeatability. In a word, such hierarchical Nb 2 O 5 @ZnO hetero-branched nanorod gas sensors are promising for the development of sensitive and selective H 2 S detection. © 2022, The Authors. All rights reserved.

关键词： Zinc oxide

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Industry-Level Electrocatalytic CO2to CO Enabled by 2D Mesoporous Ni Single Atom Catalysts

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Angewandte Chemie 2024年第5期137卷

作者： Yao Ma Taishi Xiao Kerun Zhu Dr. Wei Zhang Ziqing Yin Prof. Angang Dong Prof. Zhengzong Sun Prof. Dongyuan Zhao Prof. Wei Li Department of Chemistry Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials State Key Laboratory of Molecular Engineering of Polymers and iChEM Fudan University Shanghai 200433 China School of Microelectronics and State Key Laboratory of ASIC and System Fudan University Shanghai 200433 China

Electrocatalytic CO 2 reduction reaction (eCO 2 RR) has captivated widespread attentions, yet achieving the requisite efficiency, selectivity and stability for industrial applications poses a persistent challenge. Here, we report the synthesis of 2D mesoporous Ni single atom catalysts in N-doped carbon framework via a bottom-up interfacial assembly strategy. The 2D mesoporous Ni−N−C catalyst showcases an ultrathin thickness (~6.7 nm) with well-distributed 5 to 40 nm-width mesopores in plane and a high surface area. As a result, the Ni single atom sites with a high density (~6.0 wt %) are almost completely exposed and can be accessible, and the mass transfer can be greatly promoted even at high current densities. Thus, a high current density of 446 mA cm −2 with >95 % CO selectivity in a flow cell can be obtained. Concurrently, the catalyst demonstrates an impressive stability, maintaining a 50-hours continuous electrolysis in the membrane electrode assembly test and achieving an energy efficiency of 42 %. Finite element analysis reveals that the 2D mesoporous design enhances CO 2 diffusion, ensuring efficient adsorption and swift CO desorption at high current densities. Our study paves a way for the fabrication of 2D mesoporous single atom catalysts with nearly 100 % accessibility and expedited mass transport.

关键词： Ni−N−C Mesoporous Mass Transfer Ultrathin Nanosheets CO2 Electroreduction

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High Performance Solar-Blind Photodetectors Based on Plasma-Enhanced Atomic Layer Deposition of Thin Ga2o3 Films Annealed Under Different Atmosphere

SSRN

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SSRN 2022年

作者： Chen, Yu-Chang Chen, Ding-Bo Zeng, Guang Li, Xiao-Xi Li, Yu-Chun Zhao, Xue-Feng Chen, Na Wang, Ting-Yun Zhang, David Wei Lu, Hong-Liang State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai200433 China Yiwu Research Institute of Fudan University Chengbei Road Zhejiang Yiwu City322000 China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute Communication and Data Science Shanghai University Shanghai200444 China

Solar-blind photodetectors (SBPDs) have attracted great interests for the potential applications as missile guidance, biological detection, and ultra-violet imaging. Despite the large number of Ga 2 O 3 -SBPDs reported, most of them with thick light absorption layers fail to achieve both high responsivity and fast response time simultaneously. In this work, high-performance SBPDs with 20 nm thick Ga 2 O 3 film were demonstrated with an extremely low dark current at 0.76 pA, a great photo-dark current ratio of 10 6 , a high responsivity of 6.18 A/W, and an ultra-fast decay time ~45 ms. Moreover, the films annealed in nitrogen exhibit a more pronounced amorphous-to-polycrystalline transition, while the samples after oxygen annealing show a lower recrystallization and less oxygen vacancy concentration. This finding opens up the pathways and provide an alternative strategy towards developing the high photoresponse performance required for future applications using solar-blind detection. © 2022, The Authors. All rights reserved.

关键词： Atomic layer deposition

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An efficient asynchronous batch Bayesian optimization approach for analog circuit synthesis

arXiv

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arXiv 2021年

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

In this paper, we propose EasyBO, an Efficient ASYnchronous Batch Bayesian Optimization approach for analog circuit synthesis. In this proposed approach, instead of waiting for the slowest simulations in the batch to finish, we accelerate the optimization procedure by asynchronously issuing the next query points whenever there is an idle worker. We introduce a new acquisition function which can better explore the design space for asynchronous batch Bayesian optimization. A new strategy is proposed to better balance the exploration and exploitation and guarantee the diversity of the query points. And a penalization scheme is proposed to further avoid redundant queries during the asynchronous batch optimization. The efficiency of optimization can thus be further improved. Compared with the state-of-the-art batch Bayesian optimization algorithm, EasyBO achieves up to 7.35× speed-up without sacrificing the optimization results. © 2021, CC BY-NC-SA.

关键词： Timing circuits

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Bayesian Optimization Approach for Analog Circuit Design Using Multi-Task Gaussian Process

Bayesian Optimization Approach for Analog Circuit Design Usi...

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IEEE International Symposium on Circuits and systems

作者： Jiangli Huang Shuhan Zhang Cong Tao Fan Yang Changhao Yan Dian Zhou Xuan Zeng State Key Lab of ASIC & System School of Microelectronics Fudan University China Department of Electrical Engineering University of Texas at Dallas Richardson TX U.S.A

ISBN: (纸本)9781728192017;9781728192024

In this paper, we propose an efficient Bayesian optimization approach for analog circuit synthesis based on the multi-task Gaussian process model. Instead of building the Gaussian process models separately for each circuit specification as the traditional Bayesian optimization methods do, we extend the Gaussian process to a vector-valued function with a shared covariance function to learn the dependencies between different specifications of circuits. The weighted expected improvement function is selected as the acquisition function to cope with the constraints. The experimental results show that the proposed method can reduce the number of simulations while achieving better optimization results.

关键词： Correlation Circuits and systems Optimization methods Gaussian processes Analog circuits Bayes methods Circuit synthesis

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Ultrafast Switching in Integrated Photonics using Antimony

Ultrafast Switching in Integrated Photonics using Antimony

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Conference on Lasers and Electro-Optics (CLEO)

作者： Samarth Aggarwal Tara Milne Nikolaos Farmakidis Johannes Feldmann Xuan Li Yu Shu Zengguang Cheng Martin Salinga Wolfram H P Pernice Harish Bhaskaran Department of Materials University of Oxford Oxford UK State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Institut für Materialphysik Westfälische Wilhelms-Universität Münster Münster Germany Department of Physics University of Münster Münster Germany

In this work, we demonstrate the use of Antimony as a reversible memory element in integrated photonics. We show antimony can be used as a multilevel memory with an ultrafast speed of operations.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

In this work, we demonstrate the use of Antimony as a reversible memory element in integrated photonics. We show antimony can be used as a multilevel memory with an ultrafast speed of operations.

关键词： Electric potential Metals Switches Antimony Laser applications Electo-optic effects Photonics

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Thickness Effect on (La_(0.26)Bi_(0.74))_2Ti_4O_(11) Thin-Film Composition and Electrical Properties

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Chinese Physics Letters 2018年第2期35卷 66-70页

作者： Hui-Zhen Guo An-Quan Jiang State Key Laboratory of ASIC & System School of MicroelectronicsFudan University

Highly oriented（00l）（La_（0.26）Bi_（0.74））_2Ti_4O_（11 ）thin films are deposited on（100） SrTiO_（3 ）substrates using the pulsed laser deposition *** grains form a texture of bar-like arrays along Sr Ti O_3110directions for the film thickness above 350 nm,in contrast to spherical grains for the reduced film thickness below 220 nm.X-ray diffraction patterns show that the highly ordered bar-like grains are the ensemble of two lattice-matched monoclinic（La,Bi）_4Ti_3O_（12 ）and TiO_（2 ）components above a critical film ***,the phase decomposes into the random mixture of Bi_2Ti_2O_（7 ）and Bi_4Ti_3O_（4 ）spherical grains in thinner *** critical thickness can increase up to 440 nm as the films are deposited on LaNiO_3-buffered SrTiO_（3 ）*** electrical measurements show the dielectric enhancement of the multi-components,and comprehensive charge injection into interfacial traps between（La,Bi）_4Ti_3O_（12 ）and TiO_（2 ）components occurs under the application of a threshold voltage for the realization of high-charge storage.

关键词： Bi Ti Thin-Film Composition and Electrical Properties LNO La

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Effectiveness Evaluation for Clinical Depression Detection Using Deep Learning Based Synthetic House-Tree-Person Test

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Chen, Zhuolong Yin, Xiaoqing Yang, Fan Li, Xiaofan Zhao, Zixuan Li, Xueying Liu, Jianghu Zhao, Yubin Xu, Cheng-Zhong Zheng, Fangfang Lin, Yong Sun Yat-Sen University School of Microelectronics Science and Technology 0000 China The Fifth Affiliated Hospital of Sun Yat-Sen University Department of Psychiatry 0000 China The Fifth Affiliated Hospital of Sun Yat-Sen University Pediatrics Department 0000 China Jinan University School of Intelligent System Science and Engineering 0000 China University of Macau State Key Laboratory of IoTSC Department of Computer and Information Science Macau0000 China

Depression is one of the most common mood disorders and the number of patients increases significantly in recent years. Due to the lack of biomarkers, conversation between patients and psychiatrists is still the main clinical diagnostic method which is easily influenced by subjectivity of both patients and psychiatrists. Synthetic House-tree-person test (S-HTP), a convenient and efficient mental assessment tool, minimizes subjective influences from patients, while its effectiveness is limited by the professional ability of analyst. Here we introduce a deep learning model DeHTP, a flexible and convenient depression detection method based on S-HTP without interaction between people. Experimental results demonstrate that DeHTP achieves 0.963 AUC and 0.9 accuracy, and outperforms the conventional manual analysis of S-HTP, which is conducted on the guideline of 50 conclusions from previous study related to depression. In addition, it reveals 22 depression-correlated drawing features aligned with conclusions above from the perspective of our proposed model. Leveraging the advantages of deep learning and S-HTP, this approach has the potential for widespread promotion and adoption as the available tool for daily self-mental monitoring, as well as the promising auxiliary diagnostic method in clinical. © 2013 IEEE.

关键词： Contrastive Learning

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Fast and Robust DCNN Based Lithography SEM Image Contour Extraction Models

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Journal of Microelectronic Manufacturing 2021年第1期4卷 16-22页

作者： Tao Zhou Xuelong Shi Chen Li Yan Yan Bowen Xu Shoumian Chen Yuhang Zhao Wenzhan Zhou Kan Zhou Xuan Zeng Shanghai Integrated Circuits R&D Center Co. Ltd.ShanghaiChina2012032 Shanghai Huali Microelectronics Corporation ShanghaiChina2013173 State Key Lab of ASIC&System School of MicroelectronicsFudan UniversityShanghaiChina201203

Scanning electron microscope(SEM)metrology is critical in semiconductor manufacturing for patterning process quality assessment and *** feature width and feature-feature space dimension measurements from critical dimension SEM(CDSEM)images,visual inspection of SEM image also offers rich information on the quality of ***,visual inspection alone leaves considerable room of ambiguity regarding patterning *** narrow the room of ambiguity and to obtain more statistically quantitative information on patterning quality,SEM-image contours are often extracted to serve such *** contours,important information such as critical dimension and resist sidewall angle at any location can be *** geometrical information can be used for optical proximity correction(OPC)model verification and lithography hotspot detection,*** contour extraction algorithms based on local information have insufficient capability in dealing with noisy and low contrast *** achieve reliable contours from noisy and low contrast images,information beyond local should be made use of as much as *** this regard,deep convolutional neural network(DCNN)has proven its great capability,as manifested in various computer vision *** the full advantages of this maturing technology,we have designed a DCNN network and applied it to the task of extracting contours from noisy and low contrast SEM *** turns out that the model is capable of separating the resist top and bottom contours *** addition,the model does not generate false contours,it also can suppress the generation of broken contours when ambiguous area for contour extraction is small and *** advanced image alignment algorithm with sub-pixel accuracy,contours from different exposure fields of same process condition can be superposed to estimate process variation band,furthermore,stochastic effect induced edge placement variation statistics can eas

关键词： SEM images contour extraction machine leaning(ML) deep convolution neural network(DCNN) edge placement variation

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Dense-Atrous U-Net with salient computing for Accurate Retina Vessel Segmentation 15

Dense-Atrous U-Net with salient computing for Accurate Retin...

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

作者： Li, Xiao-Min Chen, Geng-Sheng Wang, Shu-Yang State Key Laboratory of Asic and System Fudan University Shanghai201203 China School of Basic Medical Sciences Fudan University Department of Pathology Shanghai200032 China

ISBN: (纸本)9781728162355

Retina vessel segmentation is a fundamental step in the diagnosis of diabetic retinopathy. U-Net is one of the most popular methods for medical image segmentation. However, the consecutive pooling and convolution operations lead to the loss of spatial information. In this paper, we propose a densely connected U-Net with parallel atrous convolution block and salient computing block, which is named DAS-UNet. There are several advantages of DAS-UNet for vessel segmentation. First, the dense connectivity strengthen feature propagation. Second, the parallel atrous convolution block (PAC Block) employs different receptive fields to generate more abstract features for accurate segmentation. Third, we can highlight responsive region and suppress irrelevant regions through salient computing block (SCB), which allows us to obtain a clear vessel segmentation map than the U-Net. Comprehensive experiments on DRIVE benchmark indicates that DAS-UNet achieves a state-of-The-Art performance with a significantly clear result. © 2020 IEEE.

关键词： Convolution

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