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Acta Mechanica Sinica 2023年第5期39卷 13-18页

作者：陈玉峻王鸿宇楼旭辉郭浩李晓雁王清远范海冬田晓宝 MOE Key Laboratory of Deep Earth Science and Engineering College of Architecture and EnvironmentSichuan UniversityChengdu610065China Department of Mechanics Sichuan UniversityChengdu610065China School of Urban Construction Material Simulation and Computing LaboratoryHebei Normal University of Science&TechnologyQinhuangdao066004China Center for Advanced Mechanics and Materials Applied Mechanics LaboratoryDepartment of Engineering MechanicsTsinghua UniversityBeijing100084China

铁电材料的力电耦合特性以及在纳米尺度的快速失效导致其剪切过程很难研究,而材料的脆性也限制了这些材料在铁电器件中的潜在应用.在这项工作中,我们使用分子动力学方法模拟了剪切和畴演变的动态过程,揭示了这些畴结构如何影响材料的力... 详细信息

铁电材料的力电耦合特性以及在纳米尺度的快速失效导致其剪切过程很难研究,而材料的脆性也限制了这些材料在铁电器件中的潜在应用.在这项工作中,我们使用分子动力学方法模拟了剪切和畴演变的动态过程,揭示了这些畴结构如何影响材料的力电性能.在原子尺度上,一个明显的极化旋涡状的畴结构出现在剪切带的尖端,两侧分别有180°和90°的畴壁.由应变梯度引起的挠曲电效应导致了这些复杂的畴结构.施加外部电场阻碍畴的翻转,并通过减少积累的能量减少了失配应变区域,加速了剪切过程.结果表明极化旋涡畴阻碍了剪切破坏过程,这启示我们可以通过设计畴结构来增韧铁电材料.

关键词： Ferroelectric toughening Molecular dynamics Vortex domain structure Strain gradient

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Towards quantum thermal multi-transistor systems: Energy divider formalism

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Physical Review B 2022年第23期105卷 235412-235412页

作者： Ravi T. Wijesekara Sarath D. Gunapala Malin Premaratne Advanced Computing and Simulation Laboratory(AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA

A quantum thermal transistor controls the flow of thermal energy through two of its terminals in response to an external input signal on its third terminal. In recent years, several realizations of thermal transistors combining individual quantum systems have been proposed using temperatures or optical fields as the control signals. The success of the electronic transistor in modern technology partly lies in its ability to combine and make multi-transistor systems with enhanced flow control capability or even wholly different behaviors. Hence, as the next natural step, we investigate the intricacies of building composite systems combining multiple quantum thermal transistors. We identify that the interconnects of thermal transistors play a critical role in these systems by facilitating energy exchange from one transistor to another. By isolating the exact functionality of these interconnects, we develop a simple model that still captures all its essential characteristics. This model shows that directly coupling transistors allows a substantial energy transfer between them only under highly restrictive conditions. We then develop the energy divider formalism where a single properly tuned quantum harmonic oscillator acts as an intermediary between the transistors. We demonstrate that the oscillator mediates a substantial energy exchange under a considerably relaxed set of conditions and illustrate its operating principles through detailed quantum mechanical state analysis. We compare our energy divider based interconnect against the previously developed intermediate bath method and confirm that both ways achieve similar thermal energy flow rates between the transistors over a broad range of operating temperatures. At the same time, replacing an intermediate bath made up of a large number of harmonic oscillators with a single oscillator avoids many of the theoretical and practical limitations of the earlier method. For instance, time-domain simulations show that the en

关键词： Quantum thermodynamics Thermal conductivity Harmonic oscillator Nanotechnology Transistors

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Allegro-FM: Toward an Equivariant Foundation Model for Exascale Molecular Dynamics simulations

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The journal of physical chemistry letters 2025年第25期16卷 6637-6644页

作者： Ken-Ichi Nomura Shinnosuke Hattori Satoshi Ohmura Ikumi Kanemasu Kohei Shimamura Nabankur Dasgupta Aiichiro Nakano Rajiv K Kalia Priya Vashishta Collaboratory for Advanced Computing and Simulation University of Southern California Los Angeles California 90089-0242 United States. Advanced Research Laboratory Research Platform Sony Group Corporation Atsugi Kanagawa 243-0014 Japan. Premier Institute for Advanced Studies Ehime University Matsuyama 790-8577 Japan. Department of Physics Ehime University Matsuyama 790-8577 Japan. Department of Physics Kumamoto University Kumamoto 860-8555 Japan.

We present a foundation model for exascale molecular dynamics simulations by leveraging an E(3) equivariant network architecture (Allegro) and a set of large-scale organic and inorganic materials data sets merged by the Total Energy Alignment framework. The obtained model (Allegro-FM) is versatile for various material simulations for diverse downstream tasks covering 89 elements in the training sets. Allegro-FM exhibits excellent agreement with high-level quantum chemistry theories in describing structural, mechanical, and thermodynamic properties, while exhibiting emergent capabilities for structural correlations, reaction kinetics, mechanical strengths, fracture, and solid/liquid dissolution, for which the model has not been trained. Furthermore, we demonstrate the robust predictability and generalizability of Allegro-FM for chemical reactions using Transition1x, which consists of tens of thousands of organic reactions and 9.6 million configurations including transition state data, in addition to reactive simulations using calcium silicate hydrates as a test bed. With its computationally efficient, strictly local network architecture, Allegro-FM scales up to multibillion-atom systems with a parallel efficiency of 0.975 on the exaflop/s Aurora supercomputer at Argonne Leadership computing Facility. The approach presented in this work demonstrates the potential of the foundation model for novel materials design and discovery based on large-scale atomistic simulations.

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Thermal transport in van der Waals graphene/boron-nitride structure: A molecular dynamics study

arXiv

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arXiv 2021年

作者： Alborzi, Sadegh Rajabpour, Ali Advanced Simulation and Computing Laboratory Mechanical Engineering Department Imam Khomeini International University Qazvin Iran

Among the van der Waals heterostructures, graphene/h-BN heterostructure is an appropriate candidate for 2D nanoelectronic devices. In this paper, using non-equilibrium molecular dynamics simulation approach, heat transport in bilayer graphene/h-BN and graphene/h-BN van der Waals heterostructure (i.e. h-BN flakes periodically inserted on the top and bottom of a graphene layer) are explored. The results show that by increasing the length of the system, the thermal conductivity of bilayer graphene/h-BN increases. Furthermore, it was revealed that heat transport in graphene/h-BN heterostructure enhances compared to that in monolayer graphene or monolayer h-BN. The size effect analysis shows that the heat fluxes passing through each layer in bilayer graphene/h-BN converges when the size of the system is larger than 100 nm. The results can improve the understanding heat transfer phenomena in the van der Waals heterostructures and improve designing of heterostructures for better thermal management and heat dissipation. Copyright © 2021, The Authors. All rights reserved.

关键词： Van der Waals forces

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Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2129-2147页

作者： Qiankun Zuo Junhua Hu Yudong Zhang Junren Pan Changhong Jing Xuhang Chen Xiaobo Meng Jin Hong School of Information Engineering Hubei University of EconomicsWuhan430205China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing100038China School of Computing and Mathematic Sciences University of LeicesterLeicesterLE17RHUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen518055China Faculty of Science and Technology University of MacaoMacao999078China School of Geophysics Chengdu University of TechnologyChengdu610059China Laboratory of Artificial Intelligence and 3D Technologies for Cardiovascular Diseases Guangdong Provincial Key Laboratory of South China Structural Heart DiseaseGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou519041China Medical Research Institute Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou519041China

The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia *** brain functional network is suitable to bridge the correlation between abnormal connectivities and dementia ***,it is challenging to access considerable amounts of brain functional network data,which hinders the widespread application of data-driven models in dementia *** this study,a novel distribution-regularized adversarial graph auto-Encoder(DAGAE)with transformer is proposed to generate new fake brain functional networks to augment the brain functional network dataset,improving the dementia diagnosis accuracy of data-driven ***,the label distribution is estimated to regularize the latent space learned by the graph encoder,which canmake the learning process stable and the learned representation ***,the transformer generator is devised to map the node representations into node-to-node connections by exploring the long-term dependence of highly-correlated distant brain *** typical topological properties and discriminative features can be preserved ***,the generated brain functional networks improve the prediction performance using different classifiers,which can be applied to analyze other cognitive *** on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset demonstrate that the proposed model can generate good brain functional *** classification results show adding generated data can achieve the best accuracy value of 85.33%,sensitivity value of 84.00%,specificity value of 86.67%.The proposed model also achieves superior performance compared with other related ***,the proposedmodel effectively improves cognitive disease diagnosis by generating diverse brain functional networks.

关键词： Adversarial graph encoder label distribution generative transformer functional brain connectivity graph convolutional network dementia

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Darlington pair of quantum thermal transistors

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Physical Review B 2021年第4期104卷 045405-045405页

Recent progress in manipulating individual quantum systems has led to the development of quantum thermal transistors, which control the thermal conductivity between two of its terminals according to an input signal on its third terminal. With several models for individual thermal transistors already developed, the next natural step is to investigate how multiple thermal transistors can interconnect to build useful composite devices. In electronics literature, the Darlington pair is a two-transistor configuration commonly used to construct electronic amplifiers with higher gain than is possible with a single transistor. We create the electronic Darlington pair's thermal equivalent using two individual thermal transistors in a similar configuration. Unlike previously studied models, multitransistor configurations like this contain internal transistor interconnections whose temperatures cannot be biased externally but are determined by the individual transistors' internal dynamics. We refine previous models to incorporate these transistor-transistor interactions and introduce an intermediate thermal bath to facilitate the thermal energy exchange between the Darlington pair transistors. We investigate temperature-based and optical field-based control strategies of the Darlington pair in terms of both steady-state and transient thermal flow characteristics through numerical simulations. Under both control strategies, the thermal Darlington pair's steady-state performance exhibits superior thermal amplification, sensitivity, and thermodynamic efficiency than an equivalent single thermal transistor. Our results closely mirror those expected from the corresponding electronic Darlington pair. Hence, we envision that we may readily adapt the intermediate bath formalism we developed in this work to translate a wide variety of useful electronic multitransistor configurations to their thermal equivalents.

关键词： Thermal properties Nanostructures Transistors

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DPA-2:a large atomic model as a multitask learner

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npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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Effect of graphene and carbon-nitride nanofillers on the thermal transport properties of polymer nanocomposites: A combined molecular dynamics and finite element study

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Physical Review E 2021年第1期103卷 013310-013310页

作者： Leila Razzaghi Maryam Khalkhali Ali Rajabpour Farhad Khoeini Department of Physics University of Zanjan Zanjan 45195-313 Iran Advanced Simulation and Computing Laboratory (ASCL) Mechanical Engineering Department Imam Khomeini International University Qazvin 34148-96818 Iran

Low thermal conductivity of polymers, which is one of the considerable drawbacks of commonly used composite structures, has been the focus of many researchers aiming to achieve high-performance polymer-based nanocomposites through the inclusion of highly thermally conductive fillers inside the polymer matrices. Thus, in the present study, a multiscale scheme using nonequilibrium molecular dynamics and the finite element method is developed to explore the impact of different nanosized fillers (carbon-nitride and graphene) on the effective thermal conductivity of polyethylene-based nanocomposites. We show that the thermal conductivity of amorphous polyethylene at room temperature using the reactive bond order interatomic potential is nearly 0.36±0.05W/mK. Also, the atomistic results predict that, compared to the C3N and graphene nanosheets, the C2N nanofilm presents a much stronger interfacial thermal conductance with polyethylene. Furthermore, the results indicate that the effective thermal conductivity values of C2N-polyethylene, C3N-polyethylene, and graphene-polyethylene nanocomposite, at constant volume fractions of 1%, are about 0.47, 0.56, and 0.74W/mK, respectively. In other words, the results of our models reveal that the thermal conductivity of fillers is the dominant factor that defines the effective thermal conductivity of nanocomposites.

关键词： Molecular dynamics Multiscale modeling

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CrTe2 as a two-dimensional material for topological magnetism in complex heterobilayers

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Physical Review B 2023年第9期108卷 094409-094409页

作者： Nihad Abuawwad Manuel dos Santos Dias Hazem Abusara Samir Lounis Peter Grünberg Institut and Institute for Advanced Simulation Forschungszentrum Jülich & JARA 52425 Jülich Germany Faculty of Physics University of Duisburg-Essen and CENIDE 47053 Duisburg Germany Department of Physics Birzeit University PO Box 14 Birzeit Palestine Scientific Computing Department STFC Daresbury Laboratory Warrington WA4 4AD United Kingdom

The discovery of two-dimensional (2D) van der Waals magnetic materials and their heterostructures provided an exciting platform for emerging phenomena with intriguing implications in information technology. Here, based on a multiscale modeling approach that combines first-principles calculations and a Heisenberg model, we demonstrate that interfacing a CrTe2 layer with various Te-based layers enables the control of the magnetic exchange and Dzyaloshinskii-Moriya interactions as well as the magnetic anisotropy energy of the whole heterobilayer, and thereby the emergence of topological magnetic phases such as skyrmions and antiferromagnetic Néel merons. The latter are novel particles in the world of topological magnetism since they arise in a frustrated Néel magnetic environment and manifest as multiples of intertwined hexamer textures. Our findings pave a promising road for proximity-induced engineering of both ferromagnetic and long-sought antiferromagnetic chiral objects in the very same 2D material, which is appealing for information technology devices employing quantum materials.

关键词： First-principles calculations Magnetic coupling Magnetic interactions Magnetic order Magnetic phase transitions Magnetism Spin dynamics Topological materials

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Multiorbital Nature of Doped Sr2IrO4

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Physical Review Letters 2023年第3期131卷 036504-036504页

作者： Guoren Zhang Eva Pavarini School of Sciences Nantong University Nantong 226019 People’s Republic of China Key Laboratory of Materials Physics Institute of Solid State Physics HFIPS Chinese Academy of Sciences Hefei 230031 People’s Republic of China Institute for Advanced Simulation Forschungszentrum Jülich 52425 Jülich Germany JARA High-Performance Computing Forschungszentrum Jülich 52425 Jülich Germany

The low-energy jeff=1/2 band of Sr2IrO4 bears stark resemblances with the x2−y2 band of La2CuO4, and yet no superconductivity has been found so far by doping Sr2IrO4. Behind such a behavior could be inherent failures of the jeff=1/2 picture, in particular when electrons or holes are introduced in the IrO2 planes. In view of this, here we reanalyze the jeff=1/2 scenario. By using the local-density approximation plus dynamical mean-field theory approach, we show that the form of the effective jeff=1/2 state is surprisingly stable upon doping. This supports the jeff=1/2 picture. We show that, nevertheless, Sr2IrO4 remains in essence a multiorbital system: The hybridization with the jeff=3/2 orbitals sizably reduces the Mott gap by enhancing orbital degeneracy, and part of the holes go into the jeff=3/2 channels. These effects cannot be reproduced by a simple effective screened Coulomb repulsion. In the optical conductivity spectra, multiorbital processes involving the jeff=3/2 states contribute both to the Drude peak and to relatively low-energy features.

关键词： Iridates Mott insulators Strongly correlated systems Dynamical mean field theory Quantum Monte Carlo

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