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Modelling of novel polymer materials through atomistic molecular dynamics simulations

Procedia Computer Science 2018年 136卷 341-350页

作者： Petra Bačová Anastassia N. Rissanou Vagelis Harmandaris Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas (FORTH) GR-70013 Heraklion Crete Greece Department of Mathematics and Applied Mathematics University of Crete GR-71409 Heraklion Crete Greece

Molecular simulation methodologies are nowadays very important tools for the prediction of structure-properties relations of molecular systems, and, more general, for the computational design of novel materials. Here, we demonstrate that the atomistic molecular dynamic simulations can be successfully used to design well-defined polymer systems as well as to examine their structural and dynamical properties. More specifically, we study the behaviour of graphene-based nanocomposites and nanostructured polymer materials. We provide a detailed analysis adapted to every system with a special focus on detecting the local heterogeneities in the material. Our carefully developed method allows us to shed light on the relation between the local structure and final properties of the desired material. The obtained information can be applied in the development of novel complex multi-phase polymeric materials with a broad range of possible applications, as for instance in energy storage and electronics.

关键词： computer design of polymer materials tailored analysis of properties nanocomposites

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Shock temperature and reflectivity of precompressed H2O up to 350 GPa:Approaching the interior of planets

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Chinese Physics B 2018年第12期27卷 405-412页

作者： Zhi-Yu He Hua Shu Xiu-Guang Huang Qi-Li Zhang Guo Jia Fan Zhang Yu-Chun Tu Jun-Yue Wang Jun-Jian Ye Zhi-Yong Xie Zhi-Heng Fang Wen-Bing Pei Si-Zu Fu Shanghai Institute of Laser Plasma CAER P.O.Box 800-229Shanghai201800China IFSA Collaborative Innovation Center Shanghai Jiaotong UniversityShanghai 200240China Institute of Applied Physics and Computational Mathematics Beijing 100088China Center for High Pressure Science and Technology Advance Research Beijing 100094China

Using a combination of static precompression and laser-driven shock compression, shock temperature and reflectivity of H2O have been measured up to 350 GPa and 2.1×10~4 K. Here, two calibration standards were applied to enhance temperature measurement reliability. Additionally, in temperature calculations, the discrepancy in reflectivity between active probe beam wavelength and self-emission wavelength has been taken into account to improve the data’s *** water’s temperature–pressure data are in very good agreement with our quantum molecular dynamics model,suggesting a superionic conductor of H2O in the icy planets’ deep interior. A sluggish slope gradually approaching Dulong–Petit limit at high temperature was found at a specific heat capacity. Also, high reflectivity and conductivity were observed at the same state. By analyzing the temperature–pressure diagram, reflectivity, conductivity and specific heat comprehensively at conditions simulating the interior of planets in this work, we found that as the pressure rises, a change in ionization appears; it is supposedly attributed to energetics of bond-breaking in the H2O as it transforms from a bonded molecular fluid to an ionic state. Such molecular dissociation in H2O is associated with the conducting transition because the dissociated hydrogen atoms contribute to electrical properties.

关键词： high temperature measurement equation of state of water laser-driven shock diamond anvil cell

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A demonstration of extracting the strength and wavelength of the magnetic field generated by the Weibel instability from proton radiography

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High Power Laser Science and Engineering 2019年第3期7卷 37-44页

作者： Bao Du Hong-Bo Cai Wen-Shuai Zhang Shi-Yang Zou Jing Chen Shao-Ping Zhu Institute of Applied Physics and Computational Mathematics Beijing 100094China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100871China IFSA Collaborative Innovation Center Shanghai Jiao Tong UniversityShanghai 200240China STPPL Research Center of Laser FusionChina Academy of Engineering PhysicsMianyang 621900China Graduate School China Academy of Engineering PhysicsBeijing 100088China

The Weibel instability and the induced magnetic field are of great importance for both astrophysics and inertial confinement *** of the stochasticity of this magnetic field,its main wavelength and mean strength,which are key characteristics of the Weibel instability,are still unobtainable *** this paper,a theoretical model based on the autocorrelation tensor shows that in proton radiography of the Weibel-instability-induced magnetic field,the proton flux density on the detection plane can be related to the energy spectrum of the magnetic *** allows us to extract the main wavelength and mean strength of the two-dimensionally isotropic and stochastic magnetic field directly from proton radiography for the first *** calculations are conducted to verify our theory and show good consistency between pre-set values and the results extracted from proton radiography.

关键词： magnetic field plasma diagnostics proton radiography Weibel instability

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Measurement of Two-Particle Correlations of Hadrons in e+e− Collisions at Belle

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Physical Review Letters 2022年第14期128卷 142005-142005页

作者： Y.-C. Chen Y.-J. Lee P. Chang I. Adachi H. Aihara S. Al Said D. M. Asner T. Aushev R. Ayad V. Babu P. Behera K. Belous J. Bennett M. Bessner T. Bilka D. Bodrov J. Borah M. Bračko P. Branchini T. E. Browder A. Budano M. Campajola D. Červenkov M.-C. Chang V. Chekelian B. G. Cheon K. Chilikin H. E. Cho K. Cho S.-J. Cho S.-K. Choi Y. Choi D. Cinabro S. Das G. De Nardo G. De Pietro R. Dhamija F. Di Capua J. Dingfelder T. V. Dong D. Dossett D. Epifanov T. Ferber B. G. Fulsom R. Garg V. Gaur A. Giri P. Goldenzweig T. Gu K. Gudkova C. Hadjivasiliou O. Hartbrich K. Hayasaka H. Hayashii W.-S. Hou C.-L. Hsu T. Iijima K. Inami A. Ishikawa R. Itoh M. Iwasaki Y. Iwasaki W. W. Jacobs S. Jia Y. Jin A. B. Kaliyar C. H. Kim D. Y. Kim K.-H. Kim Y.-K. Kim P. Kodyš T. Konno A. Korobov S. Korpar E. Kovalenko P. Križan R. Kroeger P. Krokovny M. Kumar R. Kumar K. Kumara A. Kuzmin Y.-J. Kwon Y.-T. Lai T. Lam J. S. Lange M. Laurenza S. C. Lee J. Li Y. Li Y. B. Li L. Li Gioi J. Libby K. Lieret C.-W. Lin D. Liventsev A. Martini M. Masuda T. Matsuda D. Matvienko F. Meier M. Merola F. Metzner K. Miyabayashi G. B. Mohanty T. J. Moon R. Mussa M. Nakao A. Natochii L. Nayak N. K. Nisar S. Nishida K. Nishimura S. Ogawa H. Ono G. Pakhlova T. Pang S. Pardi S.-H. Park S. Patra S. Paul T. K. Pedlar L. E. Piilonen T. Podobnik E. Prencipe M. T. Prim N. Rout G. Russo D. Sahoo S. Sandilya A. Sangal L. Santelj T. Sanuki V. Savinov G. Schnell C. Schwanda R. Seidl Y. Seino M. E. Sevior M. Shapkin J.-G. Shiu J. B. Singh A. Sokolov E. Solovieva M. Starič Z. S. Stottler M. Sumihama K. Sumisawa W. Sutcliffe M. Takizawa U. Tamponi K. Tanida F. Tenchini M. Uchida T. Uglov Y. Unno K. Uno S. Uno R. Van Tonder G. Varner A. Vinokurova A. Vossen E. Waheed C. H. Wang D. Wang E. Wang X. L. Wang S. Watanuki E. Won W. Yan S. B. Yang H. Ye J. Yelton Y. Zhai Z. P. Zhang V. Zhilich V. Zhukova Department of Physics National Taiwan University Taipei 10617 High Energy Accelerator Research Organization (KEK) Tsukuba 305-0801 SOKENDAI (The Graduate University for Advanced Studies) Hayama 240-0193 Department of Physics University of Tokyo Tokyo 113-0033 Department of Physics Faculty of Science University of Tabuk Tabuk 71451 Department of Physics Faculty of Science King Abdulaziz University Jeddah 21589 Brookhaven National Laboratory Upton New York 11973 National Research University Higher School of Economics Moscow 101000 Deutsches Elektronen–Synchrotron 22607 Hamburg Indian Institute of Technology Madras Chennai 600036 Institute for High Energy Physics Protvino 142281 University of Mississippi University Mississippi 38677 University of Hawaii Honolulu Hawaii 96822 Faculty of Mathematics and Physics Charles University 121 16 Prague P.N. Lebedev Physical Institute of the Russian Academy of Sciences Moscow 119991 Indian Institute of Technology Guwahati Assam 781039 Faculty of Chemistry and Chemical Engineering University of Maribor 2000 Maribor J. Stefan Institute 1000 Ljubljana INFN - Sezione di Roma Tre I-00146 Roma INFN - Sezione di Napoli I-80126 Napoli Università di Napoli Federico II I-80126 Napoli Department of Physics Fu Jen Catholic University Taipei 24205 Max-Planck-Institut für Physik 80805 München Department of Physics and Institute of Natural Sciences Hanyang University Seoul 04763 Korea Institute of Science and Technology Information Daejeon 34141 Yonsei University Seoul 03722 Chung-Ang University Seoul 06974 Sungkyunkwan University Suwon 16419 Wayne State University Detroit Michigan 48202 Malaviya National Institute of Technology Jaipur Jaipur 302017 Indian Institute of Technology Hyderabad Telangana 502285 University of Bonn 53115 Bonn Institute of Theoretical and Applied Research (ITAR) Duy Tan University Hanoi 100000 School of Physics University of Melbourne Victoria 3010 Budker Institute of Nuclear Physics SB RAS Novosibirsk 630090 Novosib

The measurement of two-particle angular correlation functions in high-multiplicity e+e− collisions at s=10.52 GeV is reported. In this study, the 89.5 fb−1 of hadronic e+e− annihilation data collected by the Belle detector at KEKB are used. Two-particle angular correlation functions are measured in the full relative azimuthal angle (Δϕ) and three units of pseudorapidity (Δη), defined by either the electron beam axis or the event-shape thrust axis, and are studied as a function of charged-particle multiplicity. The measurement in the thrust axis analysis, with mostly outgoing quark pairs determining the reference axis, is sensitive to the region of additional soft gluon emissions. No significant anisotropic collective behavior is observed with either coordinate analyses. Near-side jet correlations appear to be absent in the thrust axis analysis. The measurements are compared to predictions from various event generators and are expected to provide new constraints to the phenomenological models in the low-energy regime.

关键词： Particle & resonance production Quark & gluon jets Quark-gluon plasma

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Search for a Light Higgs Boson in Single-Photon Decays of ϒ(1S) Using ϒ(2S)→π+π−ϒ(1S) Tagging Method

引用

Physical Review Letters 2022年第8期128卷 081804-081804页

作者： S. Jia C. P. Shen I. Adachi H. Aihara S. Al Said D. M. Asner H. Atmacan T. Aushev R. Ayad V. Babu P. Behera K. Belous J. Bennett M. Bessner V. Bhardwaj B. Bhuyan T. Bilka A. Bobrov D. Bodrov G. Bonvicini J. Borah M. Bračko P. Branchini T. E. Browder A. Budano M. Campajola D. Červenkov M.-C. Chang P. Chang V. Chekelian A. Chen B. G. Cheon K. Chilikin H. E. Cho K. Cho S.-J. Cho S.-K. Choi Y. Choi S. Choudhury D. Cinabro S. Cunliffe S. Das N. Dash G. De Nardo G. De Pietro R. Dhamija F. Di Capua Z. Doležal T. V. Dong D. Epifanov T. Ferber D. Ferlewicz B. G. Fulsom R. Garg V. Gaur N. Gabyshev A. Giri P. Goldenzweig B. Golob E. Graziani Y. Guan K. Gudkova C. Hadjivasiliou T. Hara K. Hayasaka H. Hayashii M. T. Hedges W.-S. Hou K. Inami G. Inguglia A. Ishikawa R. Itoh M. Iwasaki Y. Iwasaki W. W. Jacobs E.-J. Jang Y. Jin K. K. Joo J. Kahn A. B. Kaliyar K. H. Kang T. Kawasaki C. Kiesling C. H. Kim D. Y. Kim K.-H. Kim Y.-K. Kim K. Kinoshita P. Kodyš S. Kohani T. Konno A. Korobov S. Korpar E. Kovalenko P. Križan R. Kroeger P. Krokovny M. Kumar R. Kumar K. Kumara Y.-J. Kwon T. Lam M. Laurenza S. C. Lee J. Li L. K. Li Y. Li Y. B. Li L. Li Gioi J. Libby K. Lieret D. Liventsev A. Martini M. Masuda T. Matsuda D. Matvienko S. K. Maurya F. Meier M. Merola F. Metzner K. Miyabayashi R. Mizuk G. B. Mohanty R. Mussa M. Nakao D. Narwal Z. Natkaniec A. Natochii L. Nayak N. K. Nisar S. Nishida K. Nishimura K. Ogawa S. Ogawa H. Ono P. Oskin P. Pakhlov G. Pakhlova T. Pang S. Pardi S.-H. Park S. Patra S. Paul T. K. Pedlar R. Pestotnik L. E. Piilonen T. Podobnik E. Prencipe M. T. Prim M. Röhrken A. Rostomyan N. Rout G. Russo D. Sahoo S. Sandilya A. Sangal L. Santelj T. Sanuki V. Savinov G. Schnell J. Schueler C. Schwanda Y. Seino K. Senyo M. E. Sevior M. Shapkin C. Sharma V. Shebalin J.-G. Shiu B. Shwartz J. B. Singh A. Sokolov E. Solovieva S. Stanič M. Starič Z. S. Stottler M. Sumihama K. Sumisawa T. Sumiyoshi W. Sutcliffe M. Takizawa U. Tamponi K. Tanida F. Tenchini K. Trabelsi M. Uchida S. Uehara T. Uglov Y. Unno K. Uno S. Uno P. Urquijo S Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics Fudan University Shanghai 200443 High Energy Accelerator Research Organization (KEK) Tsukuba 305-0801 SOKENDAI (The Graduate University for Advanced Studies) Hayama 240-0193 Department of Physics University of Tokyo Tokyo 113-0033 Department of Physics Faculty of Science University of Tabuk Tabuk 71451 Department of Physics Faculty of Science King Abdulaziz University Jeddah 21589 Brookhaven National Laboratory Upton New York 11973 University of Cincinnati Cincinnati Ohio 45221 National Research University Higher School of Economics Moscow 101000 Deutsches Elektronen–Synchrotron 22607 Hamburg Indian Institute of Technology Madras Chennai 600036 Institute for High Energy Physics Protvino 142281 University of Mississippi University Mississippi 38677 University of Hawaii Honolulu Hawaii 96822 Indian Institute of Science Education and Research Mohali SAS Nagar 140306 Indian Institute of Technology Guwahati Assam 781039 Faculty of Mathematics and Physics Charles University 121 16 Prague Budker Institute of Nuclear Physics SB RAS Novosibirsk 630090 Novosibirsk State University Novosibirsk 630090 P.N. Lebedev Physical Institute of the Russian Academy of Sciences Moscow 119991 Wayne State University Detroit Michigan 48202 Faculty of Chemistry and Chemical Engineering University of Maribor 2000 Maribor J. Stefan Institute 1000 Ljubljana INFN–Sezione di Roma Tre I-00146 Roma INFN–Sezione di Napoli I-80126 Napoli Università di Napoli Federico II I-80126 Napoli Department of Physics Fu Jen Catholic University Taipei 24205 Department of Physics National Taiwan University Taipei 10617 Max-Planck-Institut für Physik 80805 München National Central University Chung-li 32054 Department of Physics and Institute of Natural Sciences Hanyang University Seoul 04763 Korea Institute of Science and Technology Information Daejeon 34141 Yonsei University Seoul 03722 Chung-Ang University Seoul

We search for a light Higgs boson (A0) decaying into a τ+τ− or μ+μ− pair in the radiative decays of ϒ(1S). The production of ϒ(1S) mesons is tagged by ϒ(2S)→π+π−ϒ(1S) transitions, using 158×106 ϒ(2S) events accumulated with the Belle detector at the KEKB asymmetric energy electron-positron collider. No significant A0 signals in the mass range from the τ+τ− or μ+μ− threshold to 9.2 GeV/c2 are observed. We set the upper limits at 90% credibility level (C.L.) on the product branching fractions for ϒ(1S)→γA0 and A0→τ+τ− varying from 3.8×10−6 to 1.5×10−4. Our results represent an approximately twofold improvement on the current world best upper limits for the ϒ(1S)→γA0(→τ+τ−) production. For A0→μ+μ−, the upper limits on the product branching fractions for ϒ(1S)→γA0 and A0→μ+μ− are at the same level as the world average limits, and vary from 3.1×10−7 to 1.6×10−5. The upper limits at 90% credibility level on the Yukawa coupling fϒ(1S) and mixing angle sinθA0 are also given.

关键词： Branching fraction Extensions of Higgs sector Leptonic, semileptonic & radiative decays Hypothetical gauge bosons Lepton colliders

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AI-Driven Antimicrobial Peptide Discovery: Mining and Generation

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Accounts of chemical research 2025年第12期58卷 2025 Jun 3页

作者： Paulina Szymczak Wojciech Zarzecki Jiejing Wang Yiqian Duan Jun Wang Luis Pedro Coelho Cesar de la Fuente-Nunez Ewa Szczurek Institute of AI for Health Helmholtz Zentrum Munich Neuherberg 85764 Germany. Faculty of Mathematics Informatics and Mechanics University of Warsaw Warsaw 02-097 Poland. Faculty of Electronics and Information Technology Warsaw University of Technology Warsaw 00-661 Poland. Institute of Microbiology Chinese Academy of Sciences Beijing 100101 China. Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai 200433 China. Centre for Microbiome Research School of Biomedical Sciences Queensland University of Technology Translational Research Institute Woolloongabba Queensland 4102 Australia. Centre for Data Science Queensland University of Technology Brisbane Queensland 4001 Australia. Machine Biology Group Departments of Psychiatry and Microbiology Institute for Biomedical Informatics Institute for Translational Medicine and Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania 19104 United States of America. Departments of Bioengineering and Chemical and Biomolecular Engineering School of Engineering and Applied Science University of Pennsylvania Philadelphia Pennsylvania 19104 United States of America. Department of Chemistry School of Arts and Sciences University of Pennsylvania Philadelphia Pennsylvania 19104 United States of America. Penn Institute for Computational Science University of Pennsylvania Philadelphia Pennsylvania 19104 United States of America.

ConspectusThe escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading cause of death by 2050. Traditional antibiotic discovery methods have not kept pace with the rapidly evolving resistance mechanisms of pathogens, highlighting the urgent need for novel therapeutic strategies. In this context, antimicrobial peptides (AMPs) represent a promising class of therapeutics due to their selectivity toward bacteria and slower induction of resistance compared to classical, small molecule antibiotics. However, designing effective AMPs remains challenging because of the vast combinatorial sequence space and the need to balance efficacy with low toxicity. Addressing this issue is of paramount importance for chemists and researchers dedicated to developing next-generation antimicrobial *** intelligence (AI) presents a powerful tool to revolutionize AMP discovery. By leveraging AI, we can navigate the immense sequence space more efficiently, identifying peptides with optimal therapeutic properties. This Account explores the emerging application of AI in AMP discovery, focusing on two primary strategies: AMP mining, and AMP generation, as well as the use of discriminative methods as a valuable *** mining involves scanning biological sequences to identify potential AMPs. Discriminative models are then used to predict the activity and toxicity of these peptides. This approach has successfully identified numerous promising candidates, which were subsequently validated experimentally, demonstrating the potential of AI in AMP design and *** generation, on the other hand, creates novel peptide sequences by learning from existing data through generative modeling. This class of models optimizes for desired properties, such as increased activity and reduced toxicity, potentially producing synthetic peptides that surpass naturally occurring ones. Despite the risk of generating un

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Machine-learning approach to identification of coronal holes in solar disk images and synoptic maps

arXiv

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arXiv 2020年

作者： Illarionov, Egor Kosovichev, Alexander Tlatov, Andrey Moscow State University Moscow119991 Russia Moscow Center of Fundamental and Applied Mathematics Moscow119234 Russia Center for Computational Heliophysics New Jersey Institute of Technology NewarkNJ07102 United States Department of Physics New Jersey Institute of Technology NewarkNJ07102 United States NASA Ames Research Center Moffett FieldCA94035 United States Kislovodsk Mountain Astronomical Station of the Pulkovo Observatory Kislovodsk357700 Russia

Identification of solar coronal holes (CHs) provides information both for operational space weather forecasting and long-term investigation of solar activity. Source data for the first problem are typically most recent solar disk observations, while for the second problem it is convenient to consider solar synoptic maps. Motivated by the idea that the concept of CHs should be similar for both cases we investigate universal models that can learn a CHs segmentation in disk images and reproduce the same segmentation in synoptic maps. We demonstrate that Convolutional Neural Networks (CNN) trained on daily disk images provide an accurate CHs segmentation in synoptic maps and their pole-centric projections. Using this approach we construct a catalog of synoptic maps for the period of 2010–20 based on SDO/AIA observations in the 193 Angstrom wavelength. The obtained CHs synoptic maps are compared with magnetic synoptic maps in the time-latitude and time-longitude diagrams. The initial results demonstrate that while in some cases the CHs are associated with magnetic flux transport events there are other mechanisms contributing to the CHs formation and evolution. To stimulate further investigations the catalog of synoptic maps is published in open access. Copyright © 2020, The Authors. All rights reserved.

关键词： Solar energy

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Direct Monitoring of Li2S2Evolution and Its Influence on the Reversible Capacities of Lithium-Sulfur Batteries

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Angewandte Chemie 2023年第11期135卷

作者： Dr. Yufeng Luo Dr. Zhenhan Fang Dr. Shaorong Duan Hengcai Wu Dr. Haitao Liu Dr. Yuxing Zhao Dr. Ke Wang Prof. Qunqing Li Prof. Shoushan Fan Prof. Zijian Zheng Prof. Wenhui Duan Prof. Yuegang Zhang Prof. Jiaping Wang Tsinghua-Foxconn Nanotechnology Research Center Tsinghua University Beijing 100084 China Laboratory for Advanced Interfacial Materials and Devices School of Fashion and Textiles The Hong Kong Polytechnic University Hong Kong SAR 99077 China Department of Physics Tsinghua University Beijing 100084 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 China School of Materials Science and Technology China University of Geosciences Beijing 100083 China Frontier Science Center for Quantum Information Tsinghua University Beijing 100084 China State Key Laboratory of Low-Dimensional Quantum Physics Tsinghua University Beijing 100084 China

The polysulfide (PS) dissolution and low conductivity of lithium sulfides (Li 2 S) are generally considered the main reasons for limiting the reversible capacity of the lithium-sulfur (Li-S) system. However, as the inevitable intermediate between PSs and Li 2 S, lithium disulfide (Li 2 S 2 ) evolutions are always overlooked. Herein, Li 2 S 2 evolutions are monitored from the operando measurements on the pouch cell level. Results indicate that Li 2 S 2 undergoes slow electrochemical reduction and chemical disproportionation simultaneously during the discharging process, leading to further PS dissolution and Li 2 S generation without capacity contribution. Compared with the fully oxidized Li 2 S, Li 2 S 2 still residues at the end of the charging state. Therefore, instead of the considered Li 2 S and PSs, slow electrochemical conversions and side chemical reactions of Li 2 S 2 are the determining factors in limiting the sulfur utilization, corresponding to the poor reversible capacity of Li-S batteries.

关键词： Lithium Disulfides Chemical Reactions Conductive Interlayer Lithium Sulfur Battery Operando Measurement

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SQUARE FUNCTION INEQUALITY FOR A CLASS OF FOURIER INTEGRAL OPERATORS SATISFYING CINEMATIC CURVATURE CONDITIONS

arXiv

引用

arXiv 2019年

作者： Gao, Chuanwei Miao, Changxing Yang, Jianwei-Urbain Beijing International Center for Mathematical Research Peking University Beijing100871 China Institute of Applied Physics and Computational Mathematics P. O. Box 8009 Beijing100088 China Department of Mathematics Beijing Institute of Technology Beijing100081 China

In this paper, we establish an improved variable coefficient version of square function inequality, by which the local smoothing estimate Lp α → Lp for the Fourier integral operators satisfying cinematic curvature condition is further improved. In particular, we establish almost sharp results for 2 MSC Codes 35S30, 35L15 Copyright © 2019, The Authors. All rights reserved.

关键词： Integral equations

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Unified gas-kinetic wave-particle methods III: Multiscale photon transport

arXiv

引用

arXiv 2019年

作者： Li, Weiming Liu, Chang Zhu, Yajun Zhang, Jiwei Xu, Kun Applied and Computational Mathematics Division Beijing Computational Science Research Center Beijing100193 China National Key Laboratory of Science and Technology on Aerodynamic Design and Research Northwestern Polytechnical University Shaanxi Xi’an710072 China Department of Mathematics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong HKUST Shenzhen Research Institute Shenzhen518057 China

In this paper, we extend the unified gas-kinetic wave-particle (UGKWP) method to the multiscale photon transport. In this method, the photon free streaming and scattering processes are treated in an un-splitting way. The duality descriptions, namely the simulation particle and distribution function, are utilized to describe the photon. By accurately recovering the governing equations of the unified gas-kinetic scheme (UGKS), the UGKWP preserves the multiscale dynamics of photon transport from optically thin to optically thick regime. In the optically thin regime, the UGKWP becomes a Monte Carlo type particle tracking method, while in the optically thick regime, the UGKWP becomes a diffusion equation solver. The local photon dynamics of the UGKWP, as well as the proportion of wave-described and particle-described photons are automatically adapted according to the numerical resolution and transport regime. Compared to the Sn-type UGKS, the UGKWP requires less memory cost and does not suffer ray effect. Compared to the implicit Monte Carlo (IMC) method, the statistical noise of UGKWP is greatly reduced and computational efficiency is significantly improved in the optically thick regime. Several numerical examples covering all transport regimes from the optically thin to optically thick are computed to validate the accuracy and efficiency of the UGKWP method. In comparison to the Sn-type UGKS and IMC method, the UGKWP method may have several-order-of-magnitude reduction in computational cost and memory requirement in solving some multsicale transport problems. Copyright © 2019, The Authors. All rights reserved.

关键词： Partial differential equations

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