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A Deep Learning Approach to Nonconvex Energy Minimization for Martensitic Phase Transitions

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arXiv 2022年

作者： Chen, Xiaoli Rosakis, Phoebus Wu, Zhizhang Zhang, Zhiwen Institute for Functional Intelligent Materials Department of Mathematics National University of Singapore 119077 Singapore Department of Mathematics and Applied Mathematics University of Crete Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Heraklion Greece Department of Mathematics The University of Hong Kong Pokfulam Road Hong Kong

We propose a mesh-free method to solve nonconvex energy minimization problems for martensitic phase transitions and twinning in crystals, using the deep learning approach. These problems pose multiple challenges to both analysis and computation, as they involve multiwell gradient energies with large numbers of local minima, each involving a topologically complex microstructure of free boundaries with gradient jumps. We use the Deep Ritz method, whereby candidates for minimizers are represented by parameter-dependent deep neural networks, and the energy is minimized with respect to network parameters. The new essential ingredient is a novel activation function proposed here, which is a smoothened rectified linear unit we call SmReLU;this captures the structure of minimizers where usual activation functions fail. The method is mesh-free and thus can approximate free boundaries essential to this problem without any special treatment, and is extremely simple to implement. We show the results of many numerical computations demonstrating the success of our method. © 2022, CC BY.

关键词： Deep neural networks

Can Efficient Fourier-Transform Techniques Favorably Impact on Broadband computational Electromagnetism?

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arXiv 2024年

作者： Anderson, Thomas G. Lyon, Mark Yin, Tao Bruno, Oscar P. Department of Computational Applied Mathematics and Operations Research Rice University Houston77098 United States Department of Mathematics & Statistics University of New Hampshire Durham03824 United States LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Computing and Mathematical Sciences California Institute of Technology Pasadena91125 United States

In view of recently demonstrated joint use of novel Fourier-transform techniques and effective high-accuracy frequency domain solvers related to the Method of Moments, it is argued that a set of trans-formative innovations could be developed for the effective, accurate and efficient simulation of problems of wave propagation and scattering of broadband, time-dependent wavefields. This contribution aims to convey the character of these methods and to highlight their applicability in computational modeling of electromagnetic configurations across various fields of science and *** Codes 65R10, 65R20 Copyright © 2024, The Authors. All rights reserved.

关键词： Frequency domain analysis

TensorMD: Scalable Tensor-Diagram based Machine Learning Interatomic Potential on Heterogeneous Many-Core Processors

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arXiv 2023年

作者： Chen, Xin Ouyang, Yucheng Chen, Xin Chen, Zhenchuan Lin, Rongfen Gao, Xingyu Wang, Lifang Li, Fang Liu, Yin Shang, Honghui Song, Haifeng Institute of Applied Physics and Computational Mathematics Beijing China SKL of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China National Research Center of Parallel Computer Engineering and Technology Beijing China

Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extreme conditions. Ab initio accuracy is now achievable with machine learning based interatomic potentials. With recent advancements in high-performance computing, highly accurate and large-scale simulations become feasible. This study introduces TensorMD, a new machine learning interatomic potential (MLIP) model that integrates physical principles and tensor diagrams. The tensor formalism provides a more efficient computation and greater flexibility for use with other scientific codes. Additionally, we proposed several portable optimization strategies and developed a highly optimized version for the new Sunway supercomputer. Our optimized TensorMD can achieve unprecedented performance on the new Sunway, enabling simulations of up to 52 billion atoms with a time-to-solution of 31 ps/step/atom, setting new records for HPC + AI + MD. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

Initial development of the urbisphere urban hyperspectral library: Berlin, Germany

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Initial development of the urbisphere urban hyperspectral li...

Urban Remote Sensing Joint Event

作者： Giannis Lantzanakis Dimitris Tsirantonakis Nektarios Chrysoulakis Sue Grimmond Andreas Christen Joern Birkmann Institute of Applied and Computational Mathematics Remote Sensing Lab Foundation for Research and Technology Hellas Heraklion Greece Department of Meteorology University of Reading Reading UK Environmental Meteorology University of Freiburg Freiburg Germany Institute of Spatial and Regional Planning University of Stuttgart Stuttgart Germany

The future sustainability of cities is linked directly with their adaptive capacity in response to both ongoing urbanization, weather extremes and climate change. Many possible actions are related to urban materials and their thermal and radiative properties. To explore alternatives using modelling and to monitor applications the thermal and radiative properties of materials are critical. However, there is a lack of hyperspectral data for a wide range of common materials. A Spectral Evolution RS-3500 spectroradiometer is used to measure 2151 spectral (1 nm) bands between 350 to 2500 nm in four representative neighborhoods of Berlin (Charlottenburg, Neukolln, Lichtenberg and Mitte) during August 2022. The data are processed to contribute 284 hyperspectral measurements of surfaces into the urbisphere hyperspectral library.

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Actively Targeting Redox-Responsive Multifunctional Micelles for Synergistic Chemotherapy of Cancer

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ACS Omega 2024年第32期9卷 34268-34280页

作者： Darge, Haile Fentahun Addisu, Kefyalew Dagnew Tsai, Hsieh-Chih Birhan, Yihenew Simegniew Hanurry, Endris Yibru Mekonnen, Tefera Worku Gebrie, Hailemichael Tegenu Arunagiri, Vinothini Thankachan, Darieo Wu, Tsung-Yun Lai, Juin-Yih Chang, Hao-Ming Huang, Chun-Chiang Wu, Szu-Yuan Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology College of Medicine and Health Science Bahir Dar University Centre for Ocular Research & Education (CORE) School of Optometry and Vision Science University of Waterloo Institute of Technology Bahir Dar University Advanced Membrane Materials Center National Taiwan University of Science and Technology R&D Center for Membrane Technology Chung Yuan University Department of Chemistry College of Natural and Computational Sciences Debre Markos University School of Medicine Health Science College Addis Ababa University Division of General Surgery Tri-Service General Hospital National Defense Medical Center Taiwan Instrument Research Institute National Applied Research Laboratories Department of Food Nutrition and Health Biotechnology College of Medical and Health Science Asia University Big Data Center Lo-Hsu Medical Foundation Lotung Poh-Ai Hospital Division of Radiation Oncology Department of Medicine Lo-Hsu Medical Foundation Lotung Poh-Ai Hospital Department of Healthcare Administration College of Medical and Health Science Asia University Cancer Center Lo-Hsu Medical Foundation Lotung Poh-Ai Hospital Graduate Institute of Business Administration Fu Jen Catholic University Centers for Regional Anesthesia and Pain Medicine Taipei Municipal Wan Fang Hospital Taipei Medical University

Stimuli-responsive polymeric micelles decorated with cancer biomarkers represent an optimal choice for drug delivery applications due to their ability to enhance therapeutic efficacy while mitigating adverse side effects. Accordingly, we synthesized a digoxin-modified novel multifunctional redox-responsive disulfide-linked poly(ethylene glycol-b-poly(lactic-co-glycolic acid) copolymer (Bi(Dig-PEG-PLGA)-S₂) for the targeted and controlled release of doxorubicin (DOX) in cancer cells. Within the micellar aggregate, the disulfide bond confers redox responsiveness, while the presence of the digoxin moiety acts as a targeting agent and chemosensitizer for DOX. Upon self-assembly in aqueous solution, Bi(Dig-PEG-PLGA)-S₂ formed uniformly distributed spherical micelles with a hydrodynamic diameter (D_h) of 58.36 ± 0.78 nm and a zeta potential of −24.71 ± 1.01 mV. The micelles exhibited desirable serum and colloidal stability with a substantial drug loading capacity (DLC) of 6.26% and an encapsulation efficiency (EE) of 83.23%. In addition, the release of DOX demonstrated the redox-responsive behavior of the micelles, with approximately 89.41 ± 6.09 and 79.64 ± 6.68% of DOX diffusing from DOX@Bi(Dig-PEG-PLGA)-S₂ in the presence of 10 mM GSH and 0.1 mM H₂O₂, respectively, over 96 h. Therefore, in HeLa cell lines, DOX@Bi(Dig-PEG-PLGA)-S₂ showed enhanced intracellular accumulation and subsequent apoptotic effects, attributed to the targeting ability and chemosensitization potential of digoxin. Hence, these findings underscore the promising characteristics of Bi(Dig-PEG-PLGA)-S₂ as a multifunctional drug delivery vehicle for cancer treatment. © 2024 The Authors. Published by American Chemical Society

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SPECTRALITY OF A MEASURE CONSISTING OF TWO LINE SEGMENTS

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arXiv 2025年

作者： Kolountzakis, Mihail N. Wu, Sha Department of Mathematics and Applied Mathematics University of Crete Voutes Campus Heraklion70013 Greece Institute of Computer Science Foundation of Research and Technology Hellas N. Plastira 100 Vassilika Vouton Heraklion700 13 Greece School of Mathematics Hunan University Changsha410082 China

MSC Codes 42C15, 42C30Take an interval [t, t+ 1] on the x-axis together with the same interval on the y-axis and let ρ be the normalized one-dimensional Lebesgue measure on this set of two segments. Continuing the work done by Lai, Liu and Prince [LLP21] as well as Ai, Lu and Zhou [ALZ23] we examine the spectrality of this measure for all different values of t (being spectral means that there is an orthonormal basis for L2(ρ) consisting of exponentials e2πi(λ1x+λ2y)). We almost complete the study showing that for (Formula presenetd) and for all t ∉ Q the measure ρ is not spectral. The only remaining undecided case is the case (Formula presenetd) (plus space). We also observe that in all known cases of spectral instances of this measure the spectrum is contained in a line and we give an easy necessary and sufficient condition for such measures to have a line spectrum. © 2025, CC BY.

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Mechanism of nanoscale helium bubbles influencing dynamic tensile response of polycrystalline copper

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Mechanics of Materials 2023年第1期185卷

作者： Zhu, Qi Shao, Jian-Li Wang, Pei State Key Laboratory of Explosion Science and Technology Beijing Institute of Technology Beijing100081 China Explosion Protection and Emergency Disposal Technology Engineering Research Center of the Ministry of Education Beijing100039 China Institute of Applied Physics and Computational Mathematics Beijing100094 China Center for Applied Physics and Technology Peking University Beijing100871 China

This work investigates the mechanism of nanoscale helium (He) bubbles influencing the dynamic tensile response of quasi two-dimensional (2D) polycrystalline copper (Cu), based on molecular dynamics simulations. The dynamic fracture behaviors are explored under two different loading conditions (uniaxial tensile loading and shock loading). For uniaxial tensile loading, it's found the effect of He bubble on the tensile strength gets weaker with the increasing strain rate. A strain rate-dependent fracture mechanism that transforms from the growth and coalescence of He bubbles to the cleavage fracture of grain boundaries (GBs) as the strain rate increases is investigated. Under shock loading, the effect of He bubble on reducing the spall strength of polycrystalline Cu is more significant at lower impact velocities and will disappear as the impact velocity increases higher. The mechanism of spall damage is investigated by comparing the effect of He bubbles, voids and GBs under different impact velocities. Additionally, the dynamic response under the above two loading conditions is compared. The results indicate that the effect of He bubble distribution on the strength is more significant under shock loading than uniaxial tensile loading. © 2023

关键词： Grain boundaries

Equation of state for boron nitride along the principal Hugoniot to 16 Mbar

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Matter and Radiation at Extremes 2024年第5期9卷 77-86页

作者： Huan Zhang Yutong Yang Weimin Yang Zanyang Guan Xiaoxi Duan Mengsheng Yang Yonggang Liu Jingxiang Shen Katarzyna Batani Diluka Singappuli Ke Lan Yongsheng Li Wenyi Huo Hao Liu Yulong Li Dong Yang Sanwei Li Zhebin Wang Jiamin Yang Zongqing Zhao Weiyan Zhang Liang Sun Wei Kang Dimitri Batani National Key Laboratory of Plasma Physics Laser Fusion Research CenterChina Academy of Engineering PhysicsMianyang 621900China HEDPS Center for Applied Physics and Technologyand College of PhysicsPeking UniversityBeijing 100871China HEDPS Center for Applied Physics and Technologyand School of EngineeringPeking UniversityBeijing 100871China Institute of Plasma Physics and Laser Microfusion Hery 2301-497 WarszawaPoland Universitéde Bordeaux CNRSCEACELIA(Centre Lasers Intenses et Applications)UMR 5107F-33405 TalenceFrance Institute of Applied Physics and Computational Mathematics Beijing 100094China

The thermodynamic properties of boron nitride under extreme pressures and temperatures are of great interest and importance for materials science and inertial confinement fusion physics,but they are poorly understood owing to the challenges of performing experiments and realizing ab initio ***,we report the first shock Hugoniot data on hexagonal boron nitride at pressures of 5–16 Mbar,using hohlraum-driven shock waves at the SGIII-p laser facility in *** density functional theory molecular dynamics calculations closely match experimental data,validating the equations of state for modeling the shock response of boron nitride and filling a crucial gap in the knowledge of boron nitride properties in the region of multi-Mbar pressures and eV *** results presented here provide fundamental insights into boron nitride under the extreme conditions relevant to inertial confinement fusion,hydrogen–boron fusion,and high-energy-density physics.

关键词： boron Hugoniot extreme

ASYMPTOTIC-PRESERVING NEURAL NETWORKS BASED ON EVEN-ODD DECOMPOSITION FOR MULTISCALE GRAY RADIATIVE TRANSFER EQUATIONS

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arXiv 2025年

作者： Wu, Keke Xie, Xizhe Chen, Wengu Wang, Han Ma, Zheng School of Mathematical Sciences Suzhou Institute for Advanced Research University of Science and Technology of China Jiangsu215217 China Institute of Applied Physics and Computational Mathematics Beijing100088 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China

We present a novel Asymptotic-Preserving Neural Network (APNN) approach utilizing even-odd decomposition to tackle the nonlinear gray radiative transfer equations (GRTEs). Our AP loss demonstrates consistent stability concerning the small Knudsen number, ensuring the neural network solution uniformly converges to the macro solution. This APNN method alleviates the rigorous conservation requirements while simultaneously incorporating an auxiliary deep neural network, distinguishing it from the APNN method based on micro-macro decomposition for GRTE. Several numerical problems are examined to demonstrate the effectiveness of our proposed APNN technique. Copyright © 2025, The Authors. All rights reserved.

关键词： Radiative transfer