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Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks

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Friction 2024年第6期12卷 1283-1298页

作者： Junhyeon SEO Prahalada RAO Bart RAEYMAEKERS department of mechanical Engineering Virginia TechBlacksburgVA 24061USA Grado department of Industrial and Systems Engineering Virginia TechBlacksburgVA 24061USA

Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly ***,existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion(LPBF),such as partially melted metal particles,porosity,laser scan lines,and ***,we present a method to generate synthetic as-built LPBF surface topography maps using a progressively growing generative adversarial *** qualitatively and quantitatively demonstrate good agreement between synthetic and experimental as-built LPBF surface topography maps using areal and deterministic surface topography parameters,radially averaged power spectral density,and material ratio *** ability to accurately generate synthetic as-built LPBF surface topography maps reduces the experimental burden of performing a large number of surface topography ***,it facilitates combining experimental measurements with synthetic surface topography maps to create large data-sets that facilitate,*** as-built surface topography to LPBF process parameters,or implementing digital surface twins to monitor complex end-use LPBF parts,amongst other applications.

关键词： additive manufacturing surface topography synthetic surface topography generative adversarial networks

Automated and miniaturized screening of antibiotic combinations via robotic-printed combinatorial droplet platform

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1801-1813页

作者： Fangchi Shao Hui Li Kuangwen Hsieh Pengfei Zhang Sixuan Li Tza-Huei Wang department of Biomedical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA department of mechanical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA

Antimicrobial resistance(AMR)has become a global health crisis in need of novel *** this end,antibiotic combination therapies,which combine multiple antibiotics for treatment,have at-tracted significant attention as a potential approach for combating *** facilitate advances in anti-biotic combination therapies,most notably in investigating antibiotic interactions and identifying synergistic antibiotic combinations however,there remains a need for automated high-throughput plat-forms that can create and examine antibiotic combinations on-demand,at scale,and with minimal reagent *** address these challenges,we have developed a Robotic-Printed Combinatorial Droplet(RoboDrop)platform by integrating a programmable droplet microfuidic device that generates antibiotic combinations in nanoliter droplets in automation,a robotic arm that arranges the droplets in an array,and a camera that images the array of thousands of droplets in *** further implement a resazurin-based bacterial viability assay to accelerate our antibiotic combination *** a demonstration,we use RoboDrop to corroborate two pairs of antibiotics with known interactions and subsequently identify a new synergistic combination of cefsulodin,penicillin,and oxacillin against a model *** *** therefore envision RoboDrop becoming a useful tool to efficiently identify new synergistic antibiotic combinations toward combating AMR.

关键词： Droplet microfluidics Antimicrobial resistance Antibiotic combinatorial screening Contact printing Robotics Pharmaceutical analysis High-throughput Antibiotic interactions

Constructing low-dimensional perovskite network to assist efficient and stable perovskite solar cells

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Journal of Energy Chemistry 2024年第9期96卷 625-632页

作者： Jinwen Gu Xianggang Sun Pok Fung Chan Xinhui Lu Peng Zeng Jue Gong Faming Li Mingzhen Liu School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina department of Physics The Chinese University of Hong Kong Shatin999077Hong KongChina Sichuan University-Pittsburgh Institute Sichuan UniversityChengdu 610065China State Key Laboratory electronic Thin Film and Integrated Devices University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina

The use of low-dimensional(LD)perovskite materials is crucial for achieving high-performance perovskite solar cells(PSCs).However,LD perovskite films fabricated by conventional approaches give rise to full coverage of the underlying 3D perovskite films,which inevitably hinders the transport of charge carriers at the interface of ***,we designed and fabricated LD perovskite structure that forms net-like morphology on top of the underlying three-dimensional(3D)perovskite bulk *** net-like LD perovskite not only reduced the surface defects of 3D perovskite film,but also provided channels for the vertical transport of charge carriers,effectively enhancing the interfacial charge transfer at the LD/3D *** net-like morphological design comprising LD perovskite effectively resolves the contradiction between interfacial defect passivation and carrier extraction across the ***,the net-like LD perovskite morphology can enhance the stability of the underlying 3D perovskite film,which is attributed to the hydrophobic nature of LD *** a result,the net-like LD perovskite film morphology assists PSCs in achieving an excellent power conversion efficiency of up to 24.6%with over 1000 h long-term operational stability.

关键词： Low-dimensional perovskite Network Carrier transport Perovskite solar cell Stability

An artificial neural network based deep collocation method for the solution of transient linear and nonlinear partial differential equations

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1296-1310页

作者： Abhishek MISHRA Cosmin ANITESCU Pattabhi Ramaiah BUDARAPU Sundararajan NATARAJAN Pandu Rang VUNDAVILLI Timon RABCZUK School of mechanical Sciences Indian Institute of TechnologyBhubaneswar 752050India Institute of Structural Mechanics Bauhaus University of WeimarWeimar 99423Germany department of mechanical Engineering Indian Institute of Technology MadrasChennai 600036India

A combined deep machine learning(DML)and collocation based approach to solve the partial differential equations using artificial neural networks is *** developed method is applied to solve problems governed by the Sine–Gordon equation(SGE),the scalar wave equation and *** methods are studied:one is a space-time formulation and the other is a semi-discrete method based on an implicit Runge–Kutta(RK)time *** methodology is implemented using the Tensorflow framework and it is tested on several numerical *** on the results,the relative normalized error was observed to be less than 5%in all cases.

关键词： collocation method artificial neural networks deep machine learning Sine-Gordon equation transient wave equation dynamic scalar and elasto-dynamic equation Runge-Kutta method

Catecholaminergic neurons orchestrate fasting-induced immune harmony

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Biophysics Reports 2024年第1期10卷 57-59页

作者： Mengdi Guo Weiyan Wang Xiao Tu Meiling Jiang Cun-Jin Zhang department of Neurology Sichuan Provincial People's Hospital University of Electronic Science and Technology of China department of Science and Technology Sichuan Provincial People's Hospital University of Electronic Science and Technology of China

Dietary fasting is a well-established intervention for immunosuppressive therapy, but the underlying mechanism remains elusive. Host fitness to nutritional stress has been confirmed to initiate a cascade of adaptive responses mediated by the central nervous system, shedding new light on a neural link between fasting and immunity(de Cabo and Mattson 2019).

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Integrated optical frequency transfer and optical physical layer key distribution with enhanced link reciprocity detection

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Science China(Information Sciences) 2024年第7期67卷 335-336页

作者： Kunfeng XIE Liang HU Jianping CHEN Guiling WU State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic EngineeringShanghai Jiao Tong University

Optical fiber transmission has been widely used in communications and metrology, wherein optical frequency transfer (OFT) and optical physical layer secure key distribution (OKD) have become research hotspots [1, 2]. Moreover,OFT can perform a comparison between state-of-the-art optical atomic clocks and implement coherent optical phase transfer over long distances to support geodesy [1, 3].

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Magnetic and luminescent properties of bifunctional composite Fe_(3)O_(4)@Y_(2)O_(2)S:Eu^(3+)

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Journal of Rare Earths 2024年第8期42卷 1568-1576,I0006页

作者： Zhiqi Liang Zhili Zhang Liu Li Wen Xu Decai Li School of mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBejing100044China Beijing Key Laboratory of Flow and Heat Transfer of Phase Changing in Micro and Small Scale Bejing100044China State Key Laboratory of Tribology Tsinghua UniversityBejing100084China

As a kind of non-destructive testing method,magnetic particle inspection is widely used in the fields of aviation and high-speed *** properties of magnetic fluorescent bifunctional composites,such as fluorescence intensity and magnetic properties,have increasing demands in magnetic particle *** earth compounds offer potential as novel materials for fluorescent magnetic bifunctional composites due to their excellent optical properties and extremely narrow emission *** this work,the rare earth fluorescent material Y_(2)O_(2)S:Eu^(3+) was synthesized by solid-state reaction ***_(3)O_(4)nanoparticles prepared by hydrothermal method were uniformly coated on the Y_(2)O_(2)S:Eu^(3+) particles through physical adsorption of *** obtained Fe_(3)O_(4)@Y_(2)O_(2)S:Eu^(3+) exhibits dark red color under the ultraviolet *** additio n,X-ray diffractio n,morphology,photoluminescence and hyste resis loop of Fe_(3)O_(4)@Y_(2)O_(2)S:Cu^(3+) were *** luminescence mechanism of Y_(2)O_(2)S:Eu^(3+) is described in detail Fe_(3)O_(4)@Y_(2)O_(2)S:Cu^(3+) displays good paramagnetism and has a good controllability under a magnetic *** magnetic particle inspection of Fe_(3)O_(4)@Y_(2)O_(2)S:Eu^(3+) was performed using a 4-pole electromagnet and a test piece *** magnetic fluorescent bifunctional composite presented in this work can be applied for non-destructive testing.

关键词： Bifunctional material Fe_(3)O_(4) Y_(2)O_(2)S:Eu^(3+) Luminescence Solid-state reaction Rare earths

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Dynamics of a rotating ring-stiffened sandwich conical shell with an auxetic honeycomb core

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 963-982页

作者： S.JAHANGIRI A.GHORBANPOUR ARANI Z.KHODDAMI MARAGHI department of Solid Mechanics Faculty of Mechanical EngineeringUniversity of KashanKashan ***Iran Faculty of Engineering Mahallat Institute of Higher EducationMahallat ***Iran

The free vibration analysis of a rotating sandwich conical shell with a reentrant auxetic honeycomb core and homogenous isotropic face layers reinforced with a ring support is *** shell is modeled utilizing the first-order shear deformation theory(FSDT)incorporating the relative,centripetal,and Coriolis accelerations alongside the initial hoop tension created by the *** governing equations,compatibility conditions,and boundary conditions are attained using Hamilton’s *** trigonometric functions,an analytical solution is derived in the circumferential direction,and a numerical one is presented in the meridional direction via the differential quadrature method(DQM).The effects of various factors on the critical rotational speeds and forward and backward frequencies of the shell are *** present work is the first theoretical work regarding the dynamic analysis of a rotating sandwich conical shell with an auxetic honeycomb core strengthened with a ring support.

关键词： free vibration conical shell rotating shell ring support auxetic honeycomb

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Bearing Fault Diagnosis Based on Deep Discriminative Adversarial Domain Adaptation Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2619-2640页

作者： Jinxi Guo Kai Chen Jiehui Liu Yuhao Ma Jie Wu Yaochun Wu Xiaofeng Xue Jianshen Li School of mechanical and Equipment Engineering Hebei University of EngineeringHandan056000China College of mechanical Engineering Anyang Institute of TechnologyAnyang455000China department of mechanical and Electrical Engineering Yuncheng UniversityYuncheng044000China

Intelligent diagnosis driven by big data for mechanical fault is an important means to ensure the safe operation ofequipment. In these methods, deep learning-based machinery fault diagnosis approaches have received increasingattention and achieved some results. It might lead to insufficient performance for using transfer learning alone andcause misclassification of target samples for domain bias when building deep models to learn domain-invariantfeatures. To address the above problems, a deep discriminative adversarial domain adaptation neural networkfor the bearing fault diagnosis model is proposed (DDADAN). In this method, the raw vibration data are firstlyconverted into frequency domain data by Fast Fourier Transform, and an improved deep convolutional neuralnetwork with wide first-layer kernels is used as a feature extractor to extract deep fault features. Then, domaininvariant features are learned from the fault data with correlation alignment-based domain adversarial ***, to enhance the discriminative property of features, discriminative feature learning is embeddedinto this network to make the features compact, as well as separable between classes within the class. Finally, theperformance and anti-noise capability of the proposedmethod are evaluated using two sets of bearing fault *** results demonstrate that the proposed method is capable of handling domain offset caused by differentworkingconditions and maintaining more than 97.53% accuracy on various transfer tasks. Furthermore, the proposedmethod can achieve high diagnostic accuracy under varying noise levels.

关键词： Fault diagnosis transfer learning domain adaptation discriminative feature learning correlation alignment