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Ga intercalation in van der Waals layers for advancing p-type Bi_(2)Te_(3)-based thermoelectrics

Chinese Physics B 2023年第6期32卷 510-516页

作者：陈艺源石青钟艳李瑞恒林黎蔚任丁刘波昂然 Key Laboratory of Radiation Physics and Technology Ministry of EducationInstitute of Nuclear Science and TechnologySichuan UniversityChengdu 610064China Institute of New Energy and Low-Carbon Technology Sichuan UniversityChengdu 610065China

Tetradymite-structured chalcogenides,such as Bi_(2)Te_(3) and Sb_(2)Te_(3),are quasi-two-dimensional(2D)layered compounds,which are significant thermoelectric materials applied near room *** intercalation of guest species in van der Waals(vdW)gap implemented for tunning properties has attracted much attention in recent *** attempt to insert Ga atoms in the vdW gap between the Te layers in p-type Bi_(0.3)Sb_(1.7)Te_(3)(BST)for further improving *** vdW-related defects(including extrinsic interstitial and intrinsic defects)induced by Ga intercalation can not only modulate the carrier concentration but also enhance the texture,thereby yielding excellent electrical properties,which are reflected in the power factor PF~4.43 mW·m^(-1)·K^(-2).Furthermore,the intercalation of Ga produces multi-scale lattice imperfections such as point defects,Te precipitations,and nanopores,realizing the low lattice thermal conductivity in BST-Ga ***,a peak zT~1.1 at 373 K is achieved in the BST-1%Ga sample and greatly improved by~22%compared to the pristine *** weak bonding of vdW interlayer interaction can boost the synergistic effect for advancing BST-based or other layered thermoelectrics.

关键词： thermoelectricity p-type(Bi,Sb)_2Te_(3) van der Waals gap defects texture alignment

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Quantitative method to predict the energetics of helium-nanocavities interactions in metal systems based on electrophobic interaction

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Journal of Materiomics 2024年第3期10卷 725-737页

作者： Fengping Luo Bowen Zhang Zhiying Gao Jia Huang Hong-Bo Zhou Guang-Hong Lu Fei Gao Yugang Wang Chenxu Wang State Key Laboratory of Nuclear Physics and Technology Center for Applied Physics and TechnologyPeking UniversityBeijing100871China Department of Physics Beihang UniversityBeijing100191China Department of Nuclear Engineering and Radiological Science University of MichiganAnn ArborMI48109USA

Energetics of helium-nanocavities interactions are crucial for unveiling underlying mechanisms of nanocavity evolution in nuclear ***,it becomes intractable and even not feasible to obtain these energetics via atomic simulations with increasing nanocavity size and increasing helium content in ***,a universal scaling law of helium-induced interaction energies in nanocavities in metal systems is proposed based on electrophobic interaction of *** on this scaling law and ab-initio calculations,a predictive method for binding energies of helium and displacement defects to nanocavities of arbitrary sizes and with different helium/vacancy ratios is established for BCC iron as a representative and validated by atomic *** predictive method reveals that the critical helium/vacancy ratio for helium-enhanced vacancy binding to nanocavities in-creases with increasing nanocavity size,and the helium/vacancy ratio giving the highest stability of nanocavities is about *** Ostwald ripening of nanocavities is delayed by helium to higher temper-atures due to reduced vacancy de-trapping rates from *** proposed scaling law can be generalized to many metal systems studied in the nuclear materials *** readily coupled into mesoscale models of irradiation damages,this predictive method facilitates clarifying helium role in cavity swelling of metallic nuclear materials.

关键词： Nanocavities Helium Electrophobic interaction Predictive method

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Annealing engineering induced high thermoelectric performance in Yb-filled CoSb_(3) skutterudites

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Journal of Materials science & technology 2023年第19期150卷 168-174页

作者： Haoran Feng Qian Deng Yan Zhong Xuri Rao Yadong Wang Jianglong Zhu Fujie Zhang Ran Ang Key Laboratory of Radiation Physics and Technology Ministry of EducationInstitute of Nuclear Science and TechnologySichuan UniversityChengdu 610064China Institute of New Energy and Low-Carbon Technology Sichuan UniversityChengdu 610065China

The great pressure of energy shortage has made CoSb_(3) materials with excellent mechanical stability in the mid-temperature region favored for the integration of thermoelectric ***,their ex-cessive lattice thermal conductivity and poor Seebeck coefficient lead to low energy conversion *** Yb into the lattice void to optimize the band structure and regulate the chemical po-tential is an indispensable means for improving the thermoelectric properties of CoSb_(3)-based materials,while the phase structure and thermoelectric properties vary with the preparation *** motivates the current work to focus on the influence of annealing temperature on the microstructure and thermoelectric properties of Yb-filled CoSb_(3).Experimental analysis and theoretical model eluci-dated that an increase in annealing temperature can optimize the Yb filling fraction,which simulta-neously manipulates the band structure as well as chemical potential,resulting in an excellent electrical ***,the phase and microstructure characterization clarify that the annealing temperature can effectively affect the grain *** complex grain boundary induced by grain refinement,more filled Yb atoms and precipitates strongly scatter wide-frequency phonons,significantly suppressing the lattice thermal *** a result,a superior dimensionless figure of merit(ZT)value of~1.33 at 823 K and an average ZTave of~0.9(323-823 K)were achieved in the Ybo.4Co4Sb12 sample annealed at 923 K,and the calculated conversion efficiency could reach~13%.This work pro-vides a unique paradigm to improve thermoelectrics in the filled CoSb_(3)-based skutterudites by annealing engineering.

关键词： CoSb_(3)skutterudite Annealing engineering Grain refinement Phonon scattering Thermoelectric optimization

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A theoretical study of fragmentation dynamics of water dimer by proton impact

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Chinese Physics B 2023年第3期32卷 219-227页

作者：王志萍许雪芬张丰收王旭 Department of Fundamental Courses Wuxi Institute of TechnologyWuxi 214121China The Key Laboratory of Beam Technology and Material Modification of Ministry of Education College of Nuclear Science and TechnologyBeijing Normal UniversityBeijing 100875China

To investigate the collision processes of proton with the water dimer(H_(2)O)_(2)at 50 e V,the time-dependent density functional theory coupled with molecular dynamics nonadiabatically is *** specific collision orientations with various impact parameters are *** reaction channels,the mass distribution and the fragmentation mass spectrum are *** all launched samples,the probability of the channel of non-charge transfer scattering and charge transfer scattering is about 80%,hinting that the probability of fragmentation is about 20%.The reaction channel of proton exchange process 2 is taken as an example to exhibit the detailed microscopic dynamics of the collision process by inspecting the positions,the respective distance,the number of loss of electrons and the evolution of the electron *** study of the mass distribution and the fragmentation mass spectrum shows that among all possible fragments,the fragment with mass 36 has the highest relative abundance of 65%.The relative abundances of fragments with masses 1,35,and 34are 20%,13%,and 1.5%,*** the total electron capture cross section,the present calculations agree with the available measurements and calculations over the energy range from 50 e V to 12 ke V.

关键词： time-dependent density functional theory water dimer collision proton

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Fine-Grained Cross-Modal Fusion Based Refinement for Text-to-Image Synthesis

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Chinese Journal of Electronics 2023年第6期32卷 1329-1340页

作者： SUN Haoran WANG Yang LIU Haipeng QIAN Biao Department of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of EducationHefei University of Technology

Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite the remarkable progress, these methods are limited in fully utilizing the given texts and could generate text-mismatched images, especially when the text description is complex. We propose a novel finegrained text-image fusion based generative adversarial networks(FF-GAN), which consists of two modules: Finegrained text-image fusion block(FF-Block) and global semantic refinement(GSR). The proposed FF-Block integrates an attention block and several convolution layers to effectively fuse the fine-grained word-context features into the corresponding visual features, in which the text information is fully used to refine the initial image with more details. And the GSR is proposed to improve the global semantic consistency between linguistic and visual features during the refinement process. Extensive experiments on CUB-200 and COCO datasets demonstrate the superiority of FF-GAN over other state-of-the-art approaches in generating images with semantic consistency to the given texts.

关键词： Visualization Fuses Convolution Semantics Linguistics Benchmark testing Generative adversarial networks

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Isoscaling properties for neutron-rich fragments in highly asymmetric heavy ion collision systems

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Chinese Physics C 2024年第6期48卷 136-144页

作者：彭丹马春旺乔春源刘星泉魏慧玲 Institute of Particle and Nuclear Physics College of PhysicsHenan Normal UniversityXinxiang 453007China Institute of Nuclear Science and Technology Henan Academy of SciencesZhengzhou 450046China Key Laboratory of Radiation Physics and Technology of the Ministry of Education Sichuan UniversityChengdu 610064China

Traditionally,isoscaling has been interpreted and applied within the framework of the grand canonical ensemble,based on the assumption that fragment production occurs following the attainment of a statistical equilibrium ***,the influence of the symmetry energy can lead to differences in the neutron and density distribution in neutron-rich *** in turn may impact the iso scaling parameters(usually denoted byαandβ).We examine the isoscaling properties for neutron-rich fragments produced in highly asymmetric systems on inverse kinematics,namely^(40,48)Ca and ^(58,64)Ni+^(9)Be at 140 MeV per *** evaluate α and β values and sort them as a function of the neutron excess I≡*** significant differences in a extracted from fragments within different ranges of I emphasize the importance of understanding the dependence of isoscaling parameters on fragments generated in various collision ***,the|β(N)|/α(Z)value for a specific fragment in small size and highly iso spin asymmetry systems can serve as a probe to detect the variations in neutron density and proton density in different regions of the nucleus and indicate the limitations of theoretical models in investigating these issues.

关键词： isoscaling symmetry energy nuclear density neutron-rich fragment heavy ion collision

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A survey on graph neural network-based next POI recommendation for smart cities

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Journal of Reliable Intelligent Environments 2024年第3期10卷 299-318页

作者： Yu, Jian Guo, Lucas Zhang, Jiayu Wang, Guiling Department of Computer Science and Soft Engineering Auckland University of Technology Auckland New Zealand School of Information Science and Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there’s an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially pivotal in smart cities, these systems aim to enhance user experiences by offering location recommendations tailored to past check-ins and visited POIs. Distinguishing itself from traditional POI recommendations, the next POI approach emphasizes predicting the immediate subsequent location, factoring in both geographical attributes and temporal patterns. This approach, while promising, faces with challenges like capturing evolving user preferences and navigating data biases. The introduction of Graph Neural Networks (GNNs) brings forth a transformative solution, particularly in their ability to capture high-order dependencies between POIs, understanding deeper relationships and patterns beyond immediate connections. This survey presents a comprehensive exploration of GNN-based next POI recommendation approaches, delving into their unique characteristics, inherent challenges, and potential avenues for future research. © The Author(s) 2024.

关键词： Location based services

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Federated learning privacy incentives:Reverse auctions and negotiations

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1538-1557页

作者： Hongqin Lyu Yongxiong Zhang Chao Wang Shigong Long Shengnan Guo Guizhou Provincial Key Laboratory of Public Big Data Guizhou UniversityGuiyangChina College of Computer Science and Technology Guizhou UniversityGuiyangChina

The incentive mechanism of federated learning has been a hot topic,but little research has been done on the compensation of privacy *** this end,this study uses the Local SGD federal learning framework and gives a theoretical analysis under the use of differential privacy *** on the analysis,a multi‐attribute reverse auction model is proposed to be used for user selection as well as payment calculation for participation in federal *** model uses a mixture of economic and non‐economic attributes in making choices for users and is transformed into an optimisation equation to solve the user choice *** addition,a post‐auction negotiation model that uses the Rubinstein bargaining model as well as optimisation equations to describe the negotiation process and theoretically demonstrate the improvement of social welfare is *** the experimental part,the authors find that their algorithm improves both the model accuracy and the F1‐score values relative to the comparison algorithms to varying degrees.

关键词： artificial intelligence data privacy decision making internet of things

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PDDD-PreTrain:A Series of Commonly Used Pre-Trained Models Support Image-Based Plant Disease Diagnosis

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Plant Phenomics 2023年第2期5卷 313-332页

作者： Xinyu Dong Qi Wang Qianding Huang Qinglong Ge Kejun Zhao Xingcai Wu Xue Wu Liang Lei Gefei Hao State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China The School of Physics and Optoelectronic Engineering Guangdong University of TechnologyGuangzhou 510006China National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationGuizhou UniversityGuiyang 550025China

Plant diseases threaten global food security by reducing crop yield;thus,diagnosing plant diseases is critical to agricultural *** intelligence technologies gradually replace traditional plant disease diagnosis methods due to their time-consuming,costly,inefficient,and subjective *** a mainstream AI method,deep learning has substantially improved plant disease detection and diagnosis for precision *** the meantime,most of the existing plant disease diagnosis methods usually adopt a pre-trained deep learning model to support diagnosing diseased ***,the commonly used pre-trained models are from the computer vision dataset,not the botany dataset,which barely provides the pre-trained models sufficient domain knowledge about plant ***,this pre-trained way makes the final diagnosis model more difficult to distinguish between different plant diseases and lowers the diagnostic *** address this issue,we propose a series of commonly used pre-trained models based on plant disease images to promote the performance of disease *** addition,we have experimented with the plant disease pre-trained model on plant disease diagnosis tasks such as plant disease identification,plant disease detection,plant disease segmentation,and other *** extended experiments prove that the plant disease pre-trained model can achieve higher accuracy than the existing pre-trained model with less training time,thereby supporting the better diagnosis of plant *** addition,our pre-trained models will be open-sourced at https://***/and Zenodo platform https://***/10.5281/zenodo.7856293.

关键词： diagnosis Plant thereby

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Unveiling phonon frequency-dependent mechanism of heat transport across stacking fault in silicon carbide

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Chinese Physics B 2023年第9期32卷 373-380页

作者：王甫孙彦东邹宇徐贲付宝勤 Key Laboratory of Radiation Physics and Technology of the Ministry of Education Institute of Nuclear Science and TechnologySichuan UniversityChengdu 610064China Graduate School China Academy of Engineering PhysicsBeijing 100193China

Stacking faults(SFs)are often present in silicon carbide(SiC)and affect its thermal and heat-transport ***,it is unclear how SFs influence thermal *** non-equilibrium molecular dynamics and lattice dynamics simulations,we studied phonon transport in SiC materials with an *** to perfect SiC materials,the SF can reduce thermal *** is caused by the additional interface thermal resistance(ITR)of SF,which is difficult to capture by the previous phenomenological *** analyzing the spectral heat flux,we find that SF reduces the contribution of low-frequency(7.5 THz-12 THz)phonons to the heat flux,which can be attributed to SF reducing the phonon lifetime and group velocity,especially in the low-frequency *** SF hinders phonon transport and results in an effective interface thermal resistance around the *** results provide insight into the microscopic mechanism of the effect of defects on heat transport and have guiding significance for the regulation of the thermal conductivity of materials.

关键词： silicon carbide stacking fault thermal conductivity interface thermal resistance phonon transport spectral heat flux

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