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Solid polymer electrolyte-based high areal capacity all-solid-state batteries enabled with ceramic interlayers

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Nano research 2024年第10期17卷 8803-8808页

作者： Chenji Hu daiqian Chen Yage Huang Guoyong Xue Xi Liu Jingshu Wang Jun Ma Bowen Chen Qi Chen Linsen Li Yanbin Shen Liwei Chen School of Chemistry and Chemical Engineering in-situ Center for Physical SciencesShanghai Electrochemical Energy Device Research Center(SEED)and Frontiers Science Center for Transformative MoleculesShanghai Jiao Tong UniversityShanghai 200240China i-Lab CAS Center for Excellence in NanoscienceSuzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of SciencesSuzhou 215123China IdONANO Co Ltd Shanghai 201614China Future Battery research center Global Institute of Future TechnologyShanghai Jiao Tong UniversityShanghai 200240China

Solid polymer electrolytes(SPEs)based all-solid-state batteries(ASSBs)have attracted extensive attention as a promising candidate for next-generation energy storage *** ASSBs require high fabrication pressure to achieve high areal capacity,under which,however,SPEs struggle and risk damage or failure due to their low mechanical *** is also a lack of study on complex stress and strain SPEs experience during ASSB cell assembly ***,ceramic solid electrolytes are selected as interlayers to address the stress-strain conditions during *** a result,high areal capacity ASSBs with a LiCoO2 loading of 12 mg·cm^(-2) were assembled with SPE-based composite *** 200 cycles were carried out for these cells at a current density of 1 mA·cm^(-2) under room *** capacity decay of the battery at 200 cycles is observed to be as low as 0.06% per *** work identifies a critical issue for application of SPEs in ASSBs and provides a potential strategy for the design of SPE-based ASSBs with high specific energy and long cycle life.

关键词： all-solid-state batteries ceramic interlayer solid polymer electrolyte high areal capacity

reconstruction of particle distribution for tomographic particle image velocimetry based on unsupervised learning method

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PArTICUOLOGY 2024年第10期93卷 349-363页

作者： Zhang, duanyu Huang, Haoqin Zhou, Wu Feng, Mingjun Zhang, dapeng Gao, Limin Univ shanghai Sci & Technol Sch Energy & Power Engn Shanghai 200093 Peoples R China Univ shanghai Sci & Technol Shanghai Key Lab Multiphase Flow & Heat Transfer P Shanghai 200093 Peoples R China Northwestern Polytech Univ Natl Key Lab Aerodynam Design & Res Xian 710072 Peoples R China

The development of deep learning has inspired some new methods to solve the 3d reconstruction problem for Tomographic Particle Image Velocimetry (Tomo-PIV). However, the supervised learning method requires a large number of data with ground truth as training information, which is very difficult to gather from experiments. Although synthetic datasets can be used as alternatives, they are still not exactly the same with the real-world experimental data. In this paper, an Unsupervised reconstruction Technique based on U-net (UnrTU) is proposed to reconstruct volume particle distribution explicitly. Instead of using ground truth data, a projection function is used as an unsupervised loss function for network training to reconstruct particle distribution. The UnrTU was compared with some traditional algebraic reconstruction algorithms and supervised learning method using synthetic data under different particle density and noise level. The results indicate that UnrTU outperforms these traditional approaches in both reconstruction quality and noise robustness, and is comparable to the supervised learning methods AI-Pr. For experimental tests, particles dispersed in cured epoxy resin are moved by an electric rail with a certain speed to obtain the ground truth data of particle velocity. Compared with other algorithms, the reconstructed particle distribution by UnrTU has the best reconstruction fidelity. And the accuracy of the 3d velocity field estimated by UnrTU is 12.9% higher than that from the traditional MLOS-MArT algorithm. It demonstrates significant potential and advantages for UnrTU in 3d reconstruction of particle distribution. Finally, UnrTU was successfully applied to the high-speed planar cascade airflow field, demonstrating its applicability for measuring complex fluid flow fields at higher particle density. (c) 2024 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open acc

关键词： Tomographic particle image velocimetry 3d reconstruction Unsupervised learning Convolutional neural network FLOWS

Electro-optic 3d snapshot of a laser wakefield accelerated kilo-ampere electron bunch

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Light(Science & Applications) 2024年第5期13卷 823-834页

作者： Kai Huang Zhan Jin Nobuhiko Nakanii Tomonao Hosokai Masaki Kando Kansai Institute for Photon Science(KPSI) National Institutes for Quantum Science and Technology(QST)KyotoJapan. Laser Accelerator r&d Innovative Light Sources DivisionRIKEN SPring-8 CenterHyogoJapan. SANKEN Osaka UniversityOsakaJapan

Laser wakefield acceleration,as an advanced accelerator concept,has attracted great attentions for its ultrahigh acceleration gradient and the capability to produce high brightness electron *** three-dimensional(3d)density serves as an evaluation metric for the particle bunch quality and is intrinsically related to the applications of an *** its significance,this parameter has not been experimentally measured in the investigation of laser wakefield *** report on an electro-optic 3d snapshot of a laser wakefield electron bunch at a position outside the *** 3d shape of the electron bunch was detected by simultaneously performing optical transition radiation imaging and electro-optic *** 3d structures to a few micrometer levels were reconstructed using a genetic *** electron bunch possessed a transverse size of less than 30 *** current profile shows a multi-peak *** main peak had a duration ofd a peak current>1 *** maximum electron 3d number density was~9×10^(21)m^(-3).This research demonstrates a feasible way of 3d density monitoring on femtosecond kilo-ampere electron bunches,at any position of a beam transport line for relevant applications.

关键词： laser acceleration field

divergence angle consideration in energy spread measurement for high-quality relativistic electron beam in laser wakefield acceleration

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Chinese Physics B 2024年第6期33卷 363-368页

作者：卢光伟李曜均胡曦辰陈思宇徐豪祝铭阳闫文超陈黎明 Key Laboratory for Laser Plasmas of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China IFSA Collaborative Innovation center Shanghai Jiao Tong UniversityShanghai 200240China

The thorough exploration of the transverse quality represented by divergence angle has been lacking yet in the energy spread measurement of the relativistic electron beam for laser wakefield acceleration(LWFA). In this work, we fill this gap by numerical simulations based on the experimental data, which indicate that in a C-shape magnet, magnetic field possesses the beam focusing effect, considering that the divergence angle will result in an increase in the full width at half maxima(FWHM) of the electron density distribution in a uniformly isotropic manner, while the length-to-width ratio decreases. This indicates that the energy spread obtained from the electron deflection distance is smaller than the actual value, regardless of the divergence angle. A promising and efficient way to accurately correct the value is presented by considering the divergence angle(for instance, for an electron beam with a length-to-width ratio of 1.12, the energy spread correct from 1.2% to 1.5%), providing a reference for developing the high-quality electron beam source.

关键词： relativistic electron beams acceleration by laser–plasma interactions finite element analysis

In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning

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Theoretical & Applied Mechanics Letters 2024年第1期14卷 48-56页

作者： Jiaxuan Ma Sheng Sun Materials Genome Institute Shanghai UniversityShanghai 200444China Zhejiang Laboratory Hangzhou 311100China shanghai Frontier Science center of Mechanoinformatics Shanghai UniversityShanghai 200444China

dielectric elastomers(dEs)require balanced electric actuation performance and mechanical integrity under applied *** high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material *** study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of dE *** first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same *** framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance dE composites.

关键词： dielectric elastomer composites Multi-objective optimization Finite element modeling Convolutional neural network

3d nano-printed geometric phase metasurfaces for generating accelerating beams with complex amplitude manipulation

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 86-95页

作者： Tianchen Tang Saima Kanwal Yongzheng Lu Yuelong Li Shuangbao Wu Lei Chen Ziheng Qian Zhouyu Xie Jing Wen dawei Zhang research center of Optical Instrument and System Ministry of Education and Shanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and TechnologyShanghai 200093China

Metasurface,a forefront in emerging optical devices,has demonstrated remarkable potential for complex amplitude manipulation of light ***,prevailing approaches face challenges in spatial resolution and complexities associated with integrating dynamic phases,impeding the simplified design and reproducible fabrication of ***,we introduce an innovative approach for complex amplitude modulation within 3d nano-printed geometric phase *** approach enables the generation of self-accelerating beams by encoding amplitude through phase-only manipulation,achieving high spatial ***,this method circumvents the conventional need to adjust the geometric parameters of metasurface unit structures for amplitude manipulation,offering a streamlined and efficient route for design and fabrication *** novel methodology holds promise for expedited and low-cost manufacturing of complex amplitude manipulation metasurfaces.

关键词： metasurface complex amplitude manipulation geometric phase 3d nano-printing Airy beam accelerating parabolic beam

Sequential Propagation of Chaos for Mean-Field BSdE Systems

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Chinese Annals of Mathematics,Series B 2024年第1期45卷 11-40页

作者： Xiaochen LI Kai dU shanghai center for Mathematical Sciences Fudan UniversityShanghai 200433China. shanghai Artificial Intelligence Laboratory 701 Yunjin RoadShanghai 200433China

A new class of backward particle systems with sequential interaction is proposed to approximate the mean-field backward stochastic differential *** is proven that the weighted empirical measure of this particle system converges to the law of the McKean-Vlasov system as the number of particles *** on the Wasserstein met-ric,quantitative propagation of chaos results are obtained for both linear and quadratic growth ***,numerical experiments are conducted to validate our theoretical results.

关键词： Backward propagation of chaos Particle system Sequential interaction McKean-Vlasov BSdE Convergence rate

Physical neural networks with self-learning capabilities

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 23-42页

作者： Weichao Yu Hangwen Guo Jiang Xiao Jian Shen State Key Laboratory of Surface Physics and Institute for Nanoelectronic devices and Quantum Computing Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation center Fudan UniversityShanghai 201210China department of Physics Fudan UniversityShanghai 200433China shanghai research center for Quantum Sciences Shanghai 201315China Collaborative Innovation center of Advanced Microstructures Nanjing 210093China

Physical neural networks are artificial neural networks that mimic synapses and neurons using physical systems or *** networks harness the distinctive characteristics of physical systems to carry out computations effectively,potentially surpassing the constraints of conventional digital neural networks.A recent advancement known as“physical self-learning”aims to achieve learning through intrinsic physical processes rather than relying on external *** article offers a comprehensive review of the progress made in implementing physical self-learning across various physical *** learning strategies that contribute to the realization of physical self-learning are *** challenges in understanding the fundamental mechanism of learning,this work highlights the progress towards constructing intelligent hardware from the ground up,incorporating embedded self-organizing and self-adaptive dynamics in physical systems.

关键词： self-learning physical neural networks neuromorphic computing physical learning

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Operando investigation of particle re-entrainment mechanism in electrostatic capture process on the lab-on-a-chip

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Journal of Environmental Sciences 2024年第2期136卷 337-347页

作者： Yong Zhu Yikun Zhang Xiaoyong Yang Shanlong Tao Mingxia Chen Wenfeng Shangguan research center for Combustion and Environmental Technology School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Inhalable particle is a harmful air pollutant that causes a significant threat to people's health and ecological environments,which should be removed to purify air,but there exists limited removal efficiency due to particle ***,Operando observation system based on microscopic visualization method is developed to make in situ test of particle migration,deposition and re-entrainment characteristics on a lab-on-a-chip to achieve the investigation in micro-level *** deposition evolution of charged particles is recorded in electric field region intuitively,which confirms the fracture of particle chain occurs during the growth process of deposited *** captures the instantaneous process that a larger particle with micron size due to the coagulation of submicron particles fractures from main body of the particle chain for the first *** analysis of migration behavior of a single submicron particle near electrode surface demonstrates the direct influence of drag force on the fracture of particle *** work is the first-time visualization of dynamic process and mechanism elucidation of particle re-entrainment at the micron level,and the findings will provide the theory support for the particle re-entrainment mechanism and bring inspires of enhancing capture efficiency of inhalable particle.

关键词： Inhalable particle re-entrainment mechanism Operando observation Lab-on-a-chip Capture efficiency