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Neural network study of the nuclear ground-state spin distribution within a random interaction ensemble

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Nuclear science and Techniques 2024年第3期35卷 216-227页

作者： Deng Liu Alam Noor A Zhen-Zhen Qin Yang Lei School of Mathematics and Physics Southwest University of Science and TechnologyMianyang 621010China School of Nuclear science and technology Southwest University of Science and TechnologyMianyang 621010China

The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output *** quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the ***,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.

关键词： Neural network Two-body random ensemble Spin distribution of nuclear ground state

Frameworked electrolytes:Ionic transport behavior and high mobility for solid state batteries

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InfoMat 2024年第2期6卷 76-89页

作者： Jianguo Sun Hao Yuan Jing Yang Tuo Wang Yulin Gao Qi Zhao Ximeng Liu Haimei Wang Yong-Wei Zhang John Wang Department of Materials science and Engineering National University of SingaporeSingaporeSingapore Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore ST Engineering Advanced Material Engineering Pte.Ltd. SingaporeSingapore National University of Singapore(Chongqing)Research Institute Chongqing Liang Jiang New AreaChongqingthe People's Republic of China Institute of Materials Research and Engineering(IMRE) Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore

All solid-state batteries(ASSBs)are the holy grails of rechargeable batteries,where extensive searches are ongoing in the pursuit of ideal solid-state ***,there is still a long way off to the satisfactorily high(enough)ionic conductivity,long-term stability and especially being able to form compatible interfaces with the solid ***,we have explored ionic transport behavior and high mobility in the sub-nano pore networks in the framework ***,the frameworked electrolyte behaves as a solid,and however in the(sub)-nano scales,the very limited number of solvent molecules in confinement makes them completely different from that in liquid *** from a liquid-electrolyte counterpart,the interactions between the mobile ions and surrounding molecules are subject to dramatic changes,leading to a high ionic conductivity at room temperature with a low activation ***+ions in the sub-nano cages of the network structure are highly mobile and diffuse rather independently,where the rate-limiting step of ions crossing cages is driven by the local concentration gradient and the electrostatic interactions between Li^(+)*** new class of frameworked electrolytes(FEs)with both high ionic conductivity and desirable interface with solid electrodes are demonstrated to work with Li-ion batteries,where the ASSB with LiFePO_(4)shows a highly stable electrochemical performance of over 450 cycles at 2℃ at room temperature,with an almost negligible capacity fade of 0.03‰ each *** addition,the FE shows outstanding flexibility and anti-flammability,which are among the key requirements of large-scale applications.

关键词： frameworked electrolyte macroscopically solid with 3D ionic channels in sub-nano-scales solid-state battery space confinement of Li ions

Synchronous deprotonation–protonation for mechanically robust chitin/aramid nanofibers conductive aerogel with excellent pressure sensing, thermal management, and electromagnetic interference shielding

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Nano Research 2024年第3期17卷 2038-2049页

作者： Xinxin Zhang Kunpeng Qian Jianhui Fang Sineenat Thaiboonrod Miao Miao Xin Feng Department of Chemistry College of SciencesShanghai UniversityShanghai 200444China Research Center of Nano science and technology College of SciencesShanghai UniversityShanghai 200444China School of Materials sciences and Engineering Shanghai UniversityShanghai 200444China National Nanotechnology Center(NANOTEC) National Science and Technology Development Agency(NSTDA)Thailand Science ParkPathum Thani 12120Thailand

Aerogels with regularly porous structure and uniformly distributed conductive networks have received extensive attention in wearable electronic sensors,electromagnetic shielding,and so ***,the poor mechanical properties of the emerging nanofibers-based aerogels are limited in practical *** this work,we developed a synchronous deprotonation–protonation method in the KOH/dimethyl sulfoxide(DMSO)system at room temperature for achieving chitin cross-linked aramid nanofibers(CANFs)rather than chitin nanofibers(ChNFs)and aramid nanofibers(ANFs)separately by using chitin and aramid pulp as raw *** freeze-drying process,the cross-linked chitin/aramid nanofibers(CA)aerogel exhibited the synergetic properties of ChNF and ANF by the dual-nanofiber compensation *** mechanical stress of CA aerogel was 170 kPa at 80%compressive strain,increased by 750%compared with pure ChNF ***,the compressibility of CA aerogel was somewhat improved compared to ANF *** enhancement verified that the crosslinking reaction between ANF and ChNF during the synchronous deprotonation process was ***,the conductive aerogels with uniform porous structure(CA-M)were successfully obtained by vacuum impregnating CA aerogels in Ti_(3)C_(2)T_(x) MXene solution,displaying low thermal conductivity(0.01 W/(m·K)),high electromagnetic interference(EMI)shielding effectiveness(SE)(75 dB),flame retardant,and heat ***,the as-obtained CA-M aerogels were also applied as a pressure sensor with excellent compression cycle stability and superior human motion monitoring *** a result,the dual-nanofiber based conductive aerogels have great potentials in flexible/wearable electronics,EMI shielding,flame retardant,and heat insulation.

关键词： synchronous deprotonation–protonation electromagnetic interference(EMI)shielding flame retardant heat insulation pressure sensing

A new method to solve the Reynolds equation including mass-conserving cavitation by physics informed neural networks(PINNs)with both soft and hard constraints

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Friction 2024年第6期12卷 1165-1175页

作者： Yinhu XI Jinhui DENG Yiling LI School of Mechanical Engineering Anhui University of Science and TechnologyHuainan 232001China Ericsson AB Datalinjen 3Linköping 58330Sweden

In this work,a new method to solve the Reynolds equation including mass-conserving cavitation by using the physics informed neural networks(PINNs)is *** complementarity relationship between the pressure and the void fraction is *** are several difficulties in problem solving,and the solutions are ***,the difficulty for considering the pressure inequality constraint by PINNs is solved by transferring it into one equality constraint without introducing *** the void fraction inequality constraint is considered by using the hard constraint with the max-min ***,to avoid the fluctuation of the boundary value problems,the hard constraint method is also utilized to apply the boundary pressure values and the corresponding functions are ***,for avoiding the trivial solution the limitation for the mean value of the void fraction is *** results are validated against existing data,and both the incompressible and compressible lubricant are *** agreement can be found for both the domain and domain boundaries.

关键词： Reynolds equation mass-conserving cavitation physics informed neural networks hard constraints trivial solution

Vector field path following for a micro flapping-wing robot

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science China(Information sciences) 2024年第6期67卷 442-444页

作者： Haifeng HUANG Yingte LIU Tao NIU Chang WANG Yao ZOU Wei HE School of Intelligence science and technology University of Science and Technology Beijing Institute of Artificial Intelligence University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of EducationUniversity of Science and Technology Beijing

Flapping-wing robots mimic the flight patterns of natural flying creatures,granting them natural *** hold promising applications in the military reconnaissance,urban surveillance,and various other fields[1–3].However,the current limitations in size often restrict the suitability of existing bird-like flapping-wing robots,

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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 of1 *** 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

Multimodal Dependence Attention and Large-Scale Data Based Offline Handwritten Formula Recognition

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Journal of Computer science & technology 2024年第3期39卷 654-670页

作者：刘汉超董兰芳张信明 School of Computer science and technology University of Science and Technology of ChinaHefei 230022China CCF IEEE

Offline handwritten formula recognition is a challenging task due to the variety of handwritten symbols and two-dimensional formula ***,the deep neural network recognizers based on the encoder-decoder frame-work have achieved great improvements on this ***,the unsatisfactory recognition performance for formulas with long LTeX strings is one shortcoming of the existing ***,lacking sufficient training data also limits the capability of these *** this paper,we design a multimodal dependence attention(MDA)module to help the model learn visual and semantic dependencies among symbols in the same formula to improve the recognition perfor-mance of the formulas with long LTeX *** alleviate overfitting and further improve the recognition performance,we also propose a new dataset,Handwritten Formula Image Dataset(HFID),which contains 25620 handwritten formula images collected from real *** conduct extensive experiments to demonstrate the effectiveness of our proposed MDA module and HFID dataset and achieve state-of-the-art performances,63.79%and 65.24%expression accuracy on CROHME 2014 and CROHME 2016,respectively.

关键词： handwritten formula recognition multimodal dependence attention semantic dependence visual dependence Handwritten Formula Image Dataset

STDNet: A Spatio-Temporal Decomposition Neural Network for Multivariate Time Series Forecasting

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Tsinghua science and technology 2024年第4期29卷 1232-1247页

作者： Zhuolun Jiang Zefei Ning Hao Miao Li Wang College of Computer science and technology(College of Data science) Taiyuan University of TechnologyJinzhong 030600China

Long-term multivariate time series forecasting is an important task in engineering applications. It helps grasp the future development trend of data in real-time, which is of great significance for a wide variety of fields. Due to the non-linear and unstable characteristics of multivariate time series, the existing methods encounter difficulties in analyzing complex high-dimensional data and capturing latent relationships between multivariates in time series, thus affecting the performance of long-term prediction. In this paper, we propose a novel time series forecasting model based on multilayer perceptron that combines spatio-temporal decomposition and doubly residual stacking, namely Spatio-Temporal Decomposition Neural Network (STDNet). We decompose the originally complex and unstable time series into two parts, temporal term and spatial term. We design temporal module based on auto-correlation mechanism to discover temporal dependencies at the sub-series level, and spatial module based on convolutional neural network and self-attention mechanism to integrate multivariate information from two dimensions, global and local, respectively. Then we integrate the results obtained from the different modules to get the final forecast. Extensive experiments on four real-world datasets show that STDNet significantly outperforms other state-of-the-art methods, which provides an effective solution for long-term time series forecasting.

关键词： time series forecasting multivariate time series spatio-temporal decomposition

Adverse effect of niobium and boron on hot deformation behavior of sulfur-containing steel

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Journal of Iron and Steel Research International 2024年第1期31卷 252-263页

作者： Guo-ning He Shi-qi Wan Bo Jiang Chao-lei Zhang Ya-zheng Liu Chun-jing Wu School of Materials science and Engineering University of Science and Technology BeijingBeijing100083China Institute for Advanced Materials and technology University of Science and Technology BeijingBeijing100083China

The hot deformation behaviors of sulfur-containing gear steel 20MnCr5 containing three different contents of Nb and B(0,0.021%Nb,and 0.024%Nb-0.0022%B)were *** compression and tenssion tests were carried out by Gleeble3800 at the austenite region from 850 to 1150℃and the adverse effects of Nb and B were analyzed by the fracture,microstructure and precipitate *** compression tests showed that the proportions of instable area in hot processing maps of 0.021%Nb and Nb-B steels were higher and the deformability of Nb free steel was *** tensile deformation experiments showed that the reduction areas of Nb free,0.021%Nb and Nb-B steels were 92%-99%,84%-98%and 67%-97%,*** addition of Nb or Nb and B inhibited the dynamic recrystallization during hot deformation,and consequently,more deformed grains were then formed in 0.021%Nb and Nb-B steels thus to obtain the microstructure with worse uniformity and then deteriorate the *** addition,the interaction between inclusions and microalloyed elements was also *** particles of 0.021%Nb and Nb-B steels dynamically precipitated during deformation and precipitated together with MnS thus to worsen the deformability,resulting in the decrease of reduction area.

关键词： Hot deformation Gear steel Processing map Dynamic recrystallization Microalloying