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Suspension printing of liquid metal in yield-stress fluid for resilient 3D constructs with electromagnetic functions

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npj Flexible Electronics 2022年第1期6卷 507-517页

作者： Qian Wu Fengbo Zhu Ziliang Wu Yu Xie Jin Qian Jun Yin Huayong Yang The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310028China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310028China College of Materials Science&Engineering Taiyuan University of TechnologyTaiyuan 030024China MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Department of Engineering MechanicsZhejiang UniversityHangzhou 310027China

Liquid metal is an ideal conductive material for soft electronics because of its high conductivity and fluidity at room ***,the large surface tension and high mass density of liquid metal make forming three-dimensional(3D)dangling structures a challenging *** here is a suspension printing strategy for direct deposition of galinstan-based liquid metal into 3D dangling structures with high shape fidelity and spatial resolution(~150μm).Acrylamide/nanoclay suspension served as a yieldstress fluid support bath,with selected hydrogen peroxide to immediately oxidize the gallium skin and strengthen the extruded liquid metal,thus continuous liquid metal filaments were deposited *** subsequent photo-curing of acrylamide/nanoclay works as a resilient outer packaging,giving rise to a~500%tensile deformation for liquid metal-hydrogel *** suspension printing strategy should broaden the opportunity of using 3D and functional liquid metal constructs for soft yet resilient electromagnetic devices.

关键词： stress deformation liquid

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Hybrid of Spans and Table-Filling for Aspect-Level Sentiment Triplet Extraction 30

Hybrid of Spans and Table-Filling for Aspect-Level Sentiment...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Nuo, Minghua Guo, Chaofan College of Computer Science Inner Mongolia University Inner Mongolia Hohhot010021 China National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Hohhot010021 China Inner Mongolia Key Laboratory of Mongolian Information Processing Technology Inner Mongolia Hohhot010021 China

ISBN: (纸本)9782493814104

Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task in sentiment analysis research. Recently, researchers have proposed different tagging schemes, containing tagging of words, tagging of word-pairs, and tagging of spans. However, the first two of these methods are often insufficient for the identification of multi-word terms, while the span tagging can label the entire phrase span, but it lacks the interactive information between words. In this paper, we propose Hybrid of Spans and Table-filling (S&T) model which combining span with table-filling. Specifically, S&T model achieve full fusion of syntactic and contextual features through cross-attention and generate the structures of word-pair table through Biaffine. Then, our model converts it to a span table by computing semantic distance based on syntactic dependency tree, which can enrich each unit of span table with semantic and interactive information. Meanwhile, the initial sentence features are constructed as simple phrase tables to enhance textual information of the phrase itself. In decoding, we define 8 types of labels for identifying three dimensions including aspect, opinion, and sentiment. Finally, the extensive experiments on widely-used dataset show S&T model achieves competitive results in ASTE task, the results certify the effectiveness and robustness of our S&T model. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Filling

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Revealing processing stability landscape of organic solar cells with automated research platforms and machine learning

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InfoMat 2024年第7期6卷 51-61页

作者： Xiaoyan Du Larry Lüer Thomas Heumueller Andrej Classen Chao Liu Christian Berger Jerrit Wagner Vincent M.Le Corre Jiamin Cao Zuo Xiao Liming Ding Karen Forberich Ning Li Jens Hauch Christoph J.Brabec Helmholtz Institute Erlangen‐Nürnberg for Renewable Energy(HI ERN) Forschungszentrum Jülich GmbHErlangenGermany Institute of Materials for Electronics and Energy Technology(i‐MEET) Friedrich‐Alexander‐Universität Erlangen‐Nürnberg(FAU)ErlangenGermany School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinanthe People’s Republic of China Key Laboratory of Theoretical Organic Chemistry and Functional Molecule of Ministry of Education School of Chemistry and Chemical EngineeringHunan University of Science and TechnologyXiangtanthe People’s Republic of China Center for Excellence in Nanoscience Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijingthe People’s Republic of China Institute of Polymer Optoelectronic Materials&Devices Guangdong Basic Research Center of Excellence for Energy&Information Polymer MaterialsState Key Laboratory of Luminescent Materials&DevicesSouth China University of Technology

We use an automated research platform combined with machine learning to assess and understand the resilience against air and light during production of organic photovoltaic(OPV)devices from over 40 donor and acceptor *** standardized protocol and high reproducibility of the platform results in a dataset of high variety and veracity to deploy machine learning models to encounter links between stability and chemical,energetic,and mor-phological *** find that the strongest predictor for air/light resilience during production is the effective gap Eg,eff which points to singlet oxygen rather than the superoxide anion being the dominant agent in degradation under processing conditions.A similarly good prediction of air/light resilience can also be achieved by considering only features from chemical structure,that is,information which is available prior to any experimentation.

关键词： air stability automated screening donor/acceptor combinations machine learning organic solar cells

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Variable step size kernel LMS adaptive filtering algorithm 24

Variable step size kernel LMS adaptive filtering algorithm

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2024 International Conference on Virtual Reality, Image and Signal Processing, ICVISP 2024

作者： Li, Longyu Guo, Haodong Zhang, Xia Cao, Xiaodong School of Physics Science and Information Engineering Liaocheng University Shandong Liaocheng China Shandong Provincial Key Laboratory of Optical Communications Science and Technology Liaocheng University Shandong Liaocheng China University of Chinese Academy of Sciences Beijing China Institute of Semiconductors Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400710926

A variable step size kernel LMS adaptive filtering algorithm based on symmetric nonlinear function is proposed to solve the problem of mutual restriction between steady-state error and convergence speed in least mean squares (LMS) filtering algorithm. The algorithm makes use of the nonlinear properties of the inverse hyperbolic tangent function, and significantly improves the filtering effect by limiting its definition domain and taking the absolute value of the function value. In addition, we apply this filtering algorithm to the PLL simulation system, and the results show that the third-order filter generated by this algorithm has better filtering effect and faster convergence speed in the PLL simulation system. © 2024 Copyright held by the owner/author(s).

关键词： Wiener filtering

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Correcting ghost in single-shot spatiotemporal encoding by deep learning

Correcting ghost in single-shot spatiotemporal encoding by d...

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2023 International Conference on Intelligent systems, Communications, and Computer Networks, ISCCN 2023

作者： Xia, Liyang Liu, Kewen Liu, Xinjie Bao, Qingjia Liu, Chaoyang School of Information Engineering Wuhan University of Technology Wuhan China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Centre for Magnetic Resonance Innovation Academy for Precision Measurement Science and Technology Wuhan China

ISBN: (纸本)9781510666238

SPatiotemporal ENcoding (SPEN) has good robustness to inhomogeneous magnetic fields and chemical shifts. However, the eddy current and gradient delay in the acquisition process may cause a certain phase difference between the odd and even line data in the phase encoding dimension, resulting in severe ghost in the reconstructed images. This work proposes a deep learning model for correcting ghost in single-shot SPEN. Experimental results show that the proposed model can effectively correct ghost. © 2023 SPIE.

关键词： Signal encoding

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Structural regulation of Ti_(3)C_(2)2D-nanosheets for enhancing photothermal and electrochemical catalytic properties

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Nano Research 2025年第5期18卷 659-671页

作者： Yaoyang Pu Shaojun Liu Yujun Yang Zhixian Mao Yufeng Zhou Huajie Yin Liangcan He Xiang Mao College of Biomedical Engineering Chongqing Medical UniversityChongqing 400016China State Key Laboratory of Ultrasound in Medicine and Engineering Chongqing Medical UniversityChongqing 400016China Key Laboratory of Laboratory Medical Diagnostics Ministry of EducationDepartment of Laboratory MedicineChongqing Medical Laboratory Microfluidics and SPRi Engineering Research CenterChongqing Medical UniversityChongqing 400016China Key Laboratory of Materials Physics Centre for Environmental and Energy NanomaterialsAnhui Key Laboratory of Nanomaterials and NanotechnologyCAS Center for Excellence in NanoscienceInstitute of Solid State PhysicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China School of Medicine and Health Key Laboratory of Micro-Systems and Micro-structures Manufacturing(Ministry of Education)Harbin Institute of TechnologyHarbin 150001China Zhengzhou Research Institute Harbin Institute of TechnologyZhengzhou 450046China

Two-dimensional(2D)MXene materials are promising candidates for the development of heterogeneous materials,yet deciphering structural impacts on their inherent physical properties poses significant *** introduce structurally regulated 2D Ti_(3)C_(2)nanosheets that were fabricated using high intensity focused ultrasound(HIFU)*** nanosheets were easily produced in large quantities with a high yield of 94.4%and exhibited excellent photothermal and electrochemical catalytic *** utilizing this monolayer H-Ti_(3)C_(2)(HIFU-treated Ti_(3)C_(2)),the heterogeneous integration exhibited promising performance in subsequent *** integrating with a hydrogel matrix(H-Ti_(3)C_(2),0.1 wt.%),it demonstrated a photothermal conversion efficiency reaching 43.08%,and the maximum temperature increased by 48.14%under near-infrared(NIR)***,these 2D nanosheets were also utilized in fabricating electrochemical sensors to evaluate electrochemical-catalytic ***,it confirmed that the electrocatalytic activity of heterogeneous Au/H-Ti_(3)C_(2)in electrochemical dopamine(DA)detection,and it proved the exhibition of sensitivity(0.012μA/μM),low detection limit(0.15μM),and excellent anti-interference performance and *** enhanced activity was ascribed to synergistic effect of Au and the increased number of accessible active sites on the *** work not only sheds light on the structure-property relationship of 2D Ti_(3)C_(2)but also broadens the application scope of typical dimensional materials for controlling and producing in biological and sensing applications.

关键词： Ti_(3)C_(2)nanosheet heterogeneous-gel photothermal antibacterial catalyst electrochemical sensing

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Improvement of betanin biosynthesis in Saccharomyces cerevisiae by metabolic engineering

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Synthetic and systems Biotechnology 2023年第1期8卷 54-60页

作者： Lijuan Zhang Xue Liu Jiawei Li Yonghui Meng Guang-Rong Zhao Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin UniversityYaguan Road 135Jinnan DistrictTianjin300350China Georgia Tech Shenzhen Institute Tianjin UniversityDashi 1st RdNanshan DistrictShenzhen518055China

Betanin is a member of natural pigment betacyanins family and has extensive application in the food industry as an important natural red food *** relatively inefficient production in nature however hampers access to this phytochemicals through traditional crop-based *** bioproduction therefore represents an attractive ***,we present the construction of a Saccharomyces cerevisiae strain for betanin *** minimizing metabolic crosstalk,screening and modifying biosynthetic enzymes,enhancing pathway flux and optimizing fermentation conditions,a final titer of betanin of 28.7 mg/L was achieved from glucose at 25℃ in baffled shake-flask,which is the highest reported titer produced by yeast to our *** work provides a promising step towards developing synthetic yeast cell factories for de novo biosynthesis of value-added betanin and other betacyanins.

关键词： Natural pigment Betanin Saccharomyces cerevisiae Synthetic biology Metabolic engineering

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An Unsupervised Spatial-Temporal-Spectral Fusion Model for Hyperspectral Images Using a Global Shared Convolutional Neural Network 2

An Unsupervised Spatial-Temporal-Spectral Fusion Model for H...

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2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Wang, Xueteng Zheng, Ke Yu, Haoyang Hu, Jiaochan Jia, Jia Gao, Lianru Dalian Maritime University Information Science and Technology College Dalian China Liaocheng University College of Geography and Environment Liaocheng China Dalian Maritime University Environmental Sciences and Engineering College Dalian China Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Computational Optical Imaging Technology Beijing China

ISBN: (纸本)9798331515669

Hyperspectral images (HSI) are renowned for their high spectral resolution and extensive wavelength coverage, but they often suffer from limited spatial and temporal resolution due to imaging sensor constraints. This may make it difficult for hyperspectral images to play a role in the acquisition of fine surface information and the observation of continuity of time scales. Spatial-temporal-spectral fusion (STSF) has the purpose of synthesizing different information which from multisource satellite data which has the advantage in temporal, spatial, and spectral aspect respectively to reconstruct HSI with high spatial resolution and high temporal resolution. However most existing spatial-temporal-spectral fusion methods are restricted to the assumption of linear relationship of space temporal and spectrum. Furthermore, the spatial-temporal-spectral fusion methods mostly cannot directly process the current hyperspectral data which has a lower temporal resolution based on Landsat and MODIS. This paper proposed an unsupervised STSF model for hyperspectral images using a global shared convolutional neural network (UGSCNN). The proposed method has two models: 1) Spatial-spectral down model: combine spectral linear theory with deep learning to down sample the space and the spectrum;2) Spectral up model: utilize the shared global information to up sample the spectrum. To verify the proposed method, we compared it with others using simulated and real on-board data, proving its effectiveness and practical fusion results. © 2024 IEEE.

关键词： Convolutional neural networks

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NcoVis: A Visual Analysis Framework for Exploring Academic Collaboration Networks under New Collaborative Relationships 25

NcoVis: A Visual Analysis Framework for Exploring Academic C...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Yu, Ye Wu, Yao Liang, Xi Ma, Cheng Lu, Qiang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China School of Computer Science and Information Hefei University of Technology Hefei China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China

ISBN: (纸本)9781665405270

Academic collaboration has become one of the topics of large-scale social network analysis. The information extracted from academic collaboration also shows the contextual value in combination with other data. For academic collaborative social networks with intricate collaborative relationships, previous research methods mainly focused on network structure and community discovery, lacking in mining the characteristics of relationships in collaborative networks. There were some limitations in the research perspective. In this work, we propose a collaborative relationship representation method that is more suitable for academic collaborative social networks. It marks the attribute characteristics of nodes in collaborative relationships and highlights collaborative relationships in visualization. By adopting this new representation of collaborative relationships, we designed a visual analysis framework NcoVis, to visualize academic collaborative social networks. We further visually analyze the link relationship groups guided by nodes, and explore the potential representation of the structure and attribute characteristics of link relationships, so that analysts can explore the theme and structural change characteristics of link relationships, communities and the whole network in collaborative social networks. To prove the proposed framework, we conducted a case study on the academic collaboration literature data set, and analyzed the questionnaire with Likert scale through the user evaluation experiment, which verified the effectiveness of our method and the practicability of NcoVis. © 2022 IEEE.

关键词： Visualization

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Enhancing Suppression of Chain Transfer via Catalyst Structural Evolution in Ethylene(Co)Polymerization

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Chinese Journal of Chemistry 2023年第12期41卷 1509-1516页

作者： Beihang Ding Lihang Jiang Xiaohui Kang Shengyu Dai Institutes of Physical Science and Information Technology Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of Education Anhui University Hefei Anhui 230601 China College of Pharmacy Dalian Medical University Dalian Liaoning 116044 China School of Chemical and Environmental Engineering Anhui Polytechnic University Wuhu Anhui 241000 China

Usually,the aniline-based late-transition-metal catalysts often require bulky steric substituents on both sides of the ortho-aryl position to achieve efficient suppression of chain transfer in ethylene *** this contribution,we demonstrated thatα-diimine catalysts based on naphthylamine with only one bulky ortho-aryl substituent also demonstrated excellent capabilities to suppress the chain ***,a class ofα-diimine nickel and palladium complexes with only one o-aryl-dibenzhydryl or o-aryl-dibenzosuberyl substituent were synthesized and ***,the as-prepared naphthylamine-based nickel catalysts demonstrated outstanding activities(up to 13.02×106 g·mol–1·h–1)and yielded lightly branched(16-40/1000C)polyethylenes with very high molecular weights(445.8-854.3 kg/mol)in ethylene *** comparison,the corresponding palladium catalysts showed moderate activities(level of 104-105 g·mol–1·h–1),generating moderately branched(47-78/1000C)polyethylenes with moderate molecular weights(21.6-82.0 kg/mol).Moreover,the palladium catalysts could also copolymerize ethylene and methyl acrylate(MA),albeit in low activities(level of 103 g·mol–1·h–1),providing E-MA copolymers with low to moderate molecular weights(1.4-16.3 kg/mol)and a moderate level of incorporation ratio(2.4-7.4 mol%)and branching density(53-84/1000C).As compared with aniline-based nickel and palladium catalysts,the naphthylamine-based catalysts displayed a superior ability to suppress the chain transfer reactions and could give access to(co)polymers with orders of magnitude higher molecular weight in ethylene(co)polymerization.

关键词： α-Dimine catalysts Chain transfer High molecular weight Naphthylamine-based catalysts Ethylene(co)polymerization Copolymers Homogeneouscatalysis Conformation

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