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The origin of the anomalous expansion of the first peak in the radial distribution function during the rapid solidification of tantalum metal

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Physical chemistry chemical physics : PCCP 2025年 2025 May 27页

作者： Yuanqi Jiang Dadong Wen Qiang Xu Jian Lv Rui Zhao Ping Peng College of Physics & Electronic Information Key Laboratory of Atomic and Molecular Physics Nanchang Normal University Nanchang 330032 China. yuanqi325@***. School of Computational Science and Electronics Hunan Institute of Engineering Xiangtan 411104 China. Key Laboratory of Material Simulation Methods and Software of Ministry of Education College of Physics Jilin University Changchun 130012 China. School of Mechanical and Electrical Engineering Xinyu University Xinyu 338004 China. School of Material Science & Engineering Hunan University Changsha 410082 China.

The cause of the anomalous shift in the first maximum peak of radial distribution functions (RDFs) with decreasing temperature in metallic melts and glasses remains highly controversial. In this study, we show that the first RDF peak exhibits anomalous expansion as the temperature decreases during the non-equilibrium solidification ( = 1 × 10 K s and = 1 × 10 K s) of liquid tantalum. This behavior is primarily due to alterations in both the geometric and electronic structures of the system. In terms of geometric structure, for example, at the cooling rate of , the system forms a significant number of cage-like icositetrahedral Voronoi polyhedra (0,0,12,2) and standard icosahedral Voronoi polyhedra (0,0,12,0) at low temperatures. These Voronoi polyhedra have longer bond lengths and lower binding energies compared to their high-temperature counterparts. Furthermore, these Voronoi polyhedra nest together, forming a stable Ta- atomic configuration with minimal changes in bond lengths. This unique geometric arrangement contributes fundamentally to the anomalous expansion of the first peak of the RDF. Regarding the electronic structure, the temperature influences the interactions between Ta atoms. At higher temperatures, the electronic localization functions (ELFs) and the Mulliken bond overlap populations () are significantly increased, leading to stronger electronic interactions and a denser arrangement of nearest-neighbor atoms with shorter bond lengths. Consequently, the combined effects of geometric and electronic structural changes during non-equilibrium solidification could explain the anomalous expansion of the first peak of the RDF.

关键词： Rapid solidification

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Predicting Nonlinear Seismic Response of Structural Braces Using Machine Learning

arXiv

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arXiv 2020年

作者： Bas, Elif Ecem Aslangil, Denis Moustafa, Mohamed A. Department of Civil Engineering University of Nevada – Reno Reno NV89557 United States Computational Physics and Methods CCS-2 Los Alamos National Laboratory Los AlamosNM87545 United States

Numerical modeling of different structural materials that have highly nonlinear behaviors has always been a challenging problem in engineering disciplines. Experimental data is commonly used to characterize this behavior. This study aims to improve the modeling capabilities by using state of the art Machine Learning techniques, and attempts to answer several scientific questions: (i) Which ML algorithm is capable and is more efficient to learn such a complex and nonlinear problem? (ii) Is it possible to artificially reproduce structural brace seismic behavior that can represent real physics? (iii) How can our findings be extended to the different engineering problems that are driven by similar nonlinear dynamics? To answer these questions, the presented methods are validated by using experimental brace data. The paper shows that after proper data preparation, the long-short term memory (LSTM) method is highly capable of capturing the nonlinear behavior of braces. Additionally, the effects of tuning the hyperparameters on the models, such as layer numbers, neuron numbers, and the activation functions, are presented. Finally, the ability to learn nonlinear dynamics by using deep neural network algorithms and their advantages are briefly discussed. Copyright © 2020, The Authors. All rights reserved.

关键词： Long short-term memory

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DPA-2: a large atomic model as a multi-task learner

arXiv

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arXiv 2023年

作者： Zhang, Duo Liu, Xinzijian Zhang, Xiangyu Zhang, Chengqian Cai, Chun Bi, Hangrui Du, Yiming Qin, Xuejian Peng, Anyang Huang, Jiameng Li, Bowen Shan, Yifan Zeng, Jinzhe Zhang, Yuzhi Liu, Siyuan Li, Yifan Chang, Junhan Wang, Xinyan Zhou, Shuo Liu, Jianchuan Luo, Xiaoshan Wang, Zhenyu Jiang, Wanrun Wu, Jing Yang, Yudi Yang, Jiyuan Yang, Manyi Gong, Fu-Qiang Zhang, Linshuang Shi, Mengchao Dai, Fu-Zhi York, Darrin M. Liu, Shi Zhu, Tong Zhong, Zhicheng Lv, Jian Cheng, Jun Jia, Weile Chen, Mohan Ke, Guolin Weinan, E. Zhang, Linfeng Wang, Han AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China CAS Key Laboratory of Magnetic Materials and Devices Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of Sciences Ningbo315201 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development School of Chemistry and Molecular Engineering East China Normal University Shanghai200062 China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States Department of Chemistry Princeton University PrincetonNJ08540 United States College of Chemistry and Molecular Engineering Peking University Beijing100871 China Yuanpei College Peking University Beijing100871 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China State Key Laboratory of Superhard Materials College of Physics Jilin University Changchun130012 China Key Laboratory of Material Simulation Methods & Software of Ministry of Education College of Physics Jilin University Changchun130012 China International Center of Future Science Jilin University Changchun130012 China Key Laboratory for Quantum Materials of Zhejiang Province Department of Physics School of Science Westlake University Zhejiang Hangzhou310030 China Atomistic Simulations Italia

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi-task learning

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Quantum Inspired Optimization for Industrial Scale Problems

arXiv

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arXiv 2023年

作者： Banner, William P. Hadiashar, Shima Bab Mazur, Grzegorz Menke, Tim Ziolkowski, Marcin Kennedy, Ken Romero, Jhonathan Cao, Yudong Grover, Jeffrey A. Oliver, William D. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Zapata Computing Inc. 100 Federal St 20th Floor BostonMA02110 United States Department of Computational Methods in Chemistry Jagiellonian University Gronostajowa 2 Kraków30-387 Poland Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Harvard University CambridgeMA02138 United States BMW Group Information Technology Research Center 2 Research Dr. GreenvilleSC29607 United States

Model-based optimization, in concert with conventional black-box methods, can quickly solve large-scale combinatorial problems. Recently, quantum-inspired modeling schemes based on tensor networks have been developed which have the potential to better identify and represent correlations in datasets. Here, we use a quantum-inspired model-based optimization method TN-GEO to assess the efficacy of these quantum-inspired methods when applied to realistic problems. In this case, the problem of interest is the optimization of a realistic assembly line based on BMW's currently utilized manufacturing schedule. Through a comparison of optimization techniques, we found that quantum-inspired model-based optimization, when combined with conventional black-box methods, can find lower-cost solutions in certain contexts. Copyright © 2023, The Authors. All rights reserved.

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Physics-based modeling and predictive simulation of powder bed fusion additive manufacturing across length scales

arXiv

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arXiv 2021年

作者： Meier, Christoph Fuchs, Sebastian L. Much, Nils Nitzler, Jonas Penny, Ryan W. Praegla, Patrick M. Pröll, Sebastian D. Sun, Yushen Weissbach, Reimar Schreter, Magdalena Hodge, Neil E. Hart, A. John Wall, Wolfgang A. Institute for Computational Mechanics Technical University of Munich Boltzmannstrasse 15 Garching Munich85748 Germany Institute for Continuum and Material Mechanics Hamburg University of Technology Hamburg Germany Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge United States Unit of Strength of Materials and Structural Analysis University of Innsbruck Innsbruck Austria Methods Development Group Lawrence Livermore National Laboratory Livermore United States

Powder bed fusion additive manufacturing (PBFAM) of metals has the potential to enable new paradigms of product design, manufacturing and supply chains while accelerating the realization of new technologies in the medical, aerospace, and other industries. Currently, wider adoption of PBFAM is held back by difficulty in part qualification, high production costs and low production rates, as extensive process tuning, post-processing, and inspection are required before a final part can be produced and deployed. Physics-based modeling and predictive simulation of PBFAM offers the potential to advance fundamental understanding of physical mechanisms that initiate process instabilities and cause defects. In turn, these insights can help link process and feedstock parameters with resulting part and material properties, thereby predicting optimal processing conditions and inspiring the development of improved processing hardware, strategies and materials. This work presents recent developments of our research team in the modeling of metal PBFAM processes spanning length scales, namely mesoscale powder modeling, mesoscale melt pool modeling, macroscale thermo-solid-mechanical modeling and microstructure modeling. Ongoing work in experimental validation of these models is also summarized. In conclusion, we discuss the interplay of these individual submodels within an integrated overall modeling approach, along with future research directions. Copyright © 2021, The Authors. All rights reserved.

关键词： 3D printers

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Excess pressure and electric fields in nonideal plasma hydrodynamics

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Physical Review E 2019年第6期99卷 063207-063207页

作者： A. Diaw Michael S. Murillo Computational Physics and Methods Group Los Alamos National Laboratory Los Alamos New Mexico 87544 USA Department of Computational Mathematics Science and Engineering Michigan State University East Lansing Michigan 48824 USA

Nonideal plasmas have nontrivial space and time correlations, which simultaneously impact both the excess thermodynamic quantities as well as the collision processes. However, hydrodynamics models for designing and interpreting nonideal plasma experiments, such as inertial-confinement fusion experiments, typically neglect electrodynamics, although some models include electric fields indirectly through a generalized Fick's law. However, because most transport models are not computed self-consistently with the equation of state, there is double counting of the forces in the excess thermodynamic quantities and the collision terms. Here we employ the statistical mechanical hydrodynamic theory of Irving and Kirkwood [J. Chem. Phys. 18, 817 (1950)] to examine inhomogeneous, nonideal plasmas that contain electric fields. We show that it is not possible to simultaneously separate terms that correspond to electric fields and excess pressure; rather, these quantities arise from the same interparticle Coulomb forces. Moreover, new terms associated with nonlocality appear in the presence of strong inhomogeneities.

关键词： Aerodynamics Astrophysical fluid dynamics Hydrodynamic waves Inertial confinement fusion Hot dense plasma Hydrodynamic models

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Heterogeneous multiscale method for high energy-density matter: Connecting kinetic theory and molecular dynamics

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Journal of computational Physics: X 2020年 8卷

作者： Shohet, Gil Price, Jacob Haack, Jeffrey Marciante, Mathieu Murillo, Michael S. Department of Aeronautics and Astronautics Stanford University StanfordCA94305 United States Department of Applied Mathematics University of Washington SeattleWA98195 United States Computational Physics and Methods Group Los Alamos National Laboratory Los AlamosNM87545 United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States

We have developed a concurrent heterogeneous multiscale method (HMM) framework with a microscale molecular dynamics (MD) model and a macroscale kinetic Vlasov-BGK model. The kinetic model is formulated such that BGK collision times are the closure data obtained from MD. Using the H-theorem, we develop the mathematical link between the MD and the kinetic model. We examine three relaxation processes, energy, momentum, and bump-on-tail, using full microscale MD simulations as a reference solution. We find that solutions computed with the HMM framework offer a significant computational reduction (14×−100×) compared with computing a full MD solution, with significant improvements in accuracy compared with a kinetic model using analytical collision times. © 2020 The Authors

关键词： Molecular dynamics

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Linear-multifrequency-grey acceleration for thermal radiation transport in the presence of Compton scattering

Linear-multifrequency-grey acceleration for thermal radiatio...

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2019 International Conference on Mathematics and computational methods Applied to Nuclear Science and engineering, M and C 2019

作者： Till, A.T. Morel, J.E. Los Alamos National Laboratory CCS-2: Computational Physics and Methods Group P.O. Box 1663 Los AlamosNM United States Texas A and M University Nuclear Engineering Department 3133 TAMU College StationTX United States

ISBN: (纸本)9780894487699

Linear-multifrequency grey (LMFG) acceleration is commonly used in thermal radiation transport (TRT) to accelerate convergence of the radiation intensity. LMFG was developed assuming either no scattering or converged Thomson (within-group only) scattering. We derive and test variations of LMFG that support the more general Compton scattering, which has group-to-group coupling. We test combinations of LMFG and within-group DSA to approximately converge the Compton scattering before LMFG is applied. Comparisons of spectral radii between an analytic Fourier analysis and a numerical implementation in the Capsaicin code show good agreement. Effectively combining DSA and LMFG were seen to reduce spectral radii from above 0.95 to below 0.61, with more reduction at lower temperatures. © 2019 American Nuclear Society. All rights reserved.

关键词： Compton scattering

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Using a low-fidelity potential flow model as a surrogate for a high-fidelity viscous flow model 48th

Using a low-fidelity potential flow model as a surrogate for...

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48th AIAA Fluid Dynamics Conference, 2018

作者： Rossetti, Jack S. Dannenhoffer, John F. Aerospace Computational Methods Laboratory Syracuse University Mechanical and Aerospace Engineering SyracuseNY13244 United States

ISBN: (数字)9781624105531

ISBN: (纸本)9781624105531

In current engineering fluid flow systems, space is restricted and turning a fluid while trying to minimize pressure loss and maintain flow uniformity can be a challenge. Attempts to solve this problem have mainly been through the use of a trail and error methodology both experimentally and numerically, which invokes some experiential knowledge or intuition. With recent developments in design optimization research, certain methods can now be used to remove the qualitative and imprecise nature of intuition and experience. Since this problem involves finding the shape of the vanes as well as their number and distribution, it seems appropriate to investigate it using a topology optimization technique. Topology optimization presents a general design optimization approach that can produce non-conventional designs. This technique has been used in the structural dynamics field for the design of bridges and aerodynamic structures, among others. Recently, the fluid dynamics community has adopted topology optimization for low to moderate Reynolds number flows. These applications mainly consider the design of channel walls and not the design of the internal structures with fixed boundaries, like turning vanes for a fluid flow system. Design of turning vanes is an important issue for engineering applications due to size and space constraints. Developing tools to optimize these designs can reduce costs and produce more efficient fluid flow systems for heating and cooling or fuel injection. In this study, a topology optimization technique using a low-fidelity potential flow model as a surrogate for a high-fidelity viscous flow model is proposed with the goal of finding the optimal design and layout of turning vanes in moderate to high Reynolds number flow. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Topology

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Ion friction at small values of the Coulomb logarithm

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Physical Review E 2019年第5期99卷 053206-053206页

作者： Tucker Sprenkle Adam Dodson Quinton McKnight Ross Spencer Scott Bergeson Abdourahmane Diaw Michael S. Murillo Department of Physics and Astronomy Brigham Young University Provo Utah 84602 USA Computational Physics and Methods Group Los Alamos National Laboratory Los Alamos New Mexico 87544 USA Department of Computational Mathematics Science and Engineering Michigan State University East Lansing Michigan 48824 USA

Transport properties of high-energy-density plasmas are influenced by the ion collision rate. Traditionally, this rate involves the Coulomb logarithm, lnΛ. Typical values of lnΛ are ≈10–20 in kinetic theories where transport properties are dominated by weak-scattering events caused by long-range forces. The validity of these theories breaks down for strongly coupled plasmas, when lnΛ is of order one. We present measurements and simulations of collision data in strongly coupled plasmas when lnΛ is small. Experiments are carried out in the first dual-species ultracold neutral plasma (UNP), using Ca+ and Yb+ ions. We find strong collisional coupling between the different ion species in the bulk of the plasma. We simulate the plasma using a two-species fluid code that includes Coulomb logarithms derived from either a screened Coulomb potential or a the potential of mean force. We find generally good agreement between the experimental measurements and the simulations. With some improvements, the mixed Ca+ and Yb+ dual-species UNP will be a promising platform for testing theoretical expressions for lnΛ and collision cross-sections from kinetic theories through measurements of energy relaxation, stopping power, two-stream instabilities, and the evolution of sculpted distribution functions in an idealized environment in which the initial temperatures, densities, and charge states are accurately known.

关键词： Hot dense plasma Ion-inertial confinement Low-temperature plasma Random & disordered media Strongly-coupled plasmas Warm-dense matter Atom & ion cooling Optical plasma measurements Particle-in-cell methods Time-resolved light scattering spectroscopy Two-fluid & multi-fluid model

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