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arXiv 2018年

作者： Peng, Jie Wang, Junxian Shu, Shi School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan411105 China

Balancing domain decomposition by constraints (BDDC) algorithms with adaptive primal constraints are developed in a concise variational framework for the weighted plane wave least-squares (PWLS) discritization of Helmholtz equations with high and various wave numbers. The unknowns to be solved in this preconditioned system are defined on elements rather than vertices or edges, which are different from the well-known discritizations such as the classical finite element method. Through choosing suitable "interface" and appropriate primal constraints with complex coefficients and introducing some local techniques, we developed a two-level adaptive BDDC algorithm for the PWLS discretization, and the condition number of the preconditioned system is proved to be bounded above by a user-defined tolerance and a constant which is only dependent on the maximum number of interfaces per subdomain. A multilevel algorithm is also attempted to resolve the bottleneck in large scale coarse problem. Numerical results are carried out to confirm the theoretical results and illustrate the efficiency of the proposed *** Codes 65N30, 65F10, 65N55 Copyright © 2018, The Authors. All rights reserved.

关键词： Helmholtz equation

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Corrigendum to “Curl recovery for the lowest order rectangular edge element” [Applied Mathematics and computation 371 (2020) 124897]

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Applied Mathematics and computation 2020年 372卷

作者： Peizhen Wang Yanping Chen Wei Yang School of Mathematics and Statistics North China University of Water Resources and Electric Power Zhengzhou Henan 450000 PR China School of Mathematical Sciences South China Normal University Guangzhou Guangdong 510631 PR China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 PR China

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Design lithium storage materials by lithium adatoms adsorption at the edges of zigzag silicene nanoribbon: A first principle study

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Applied Surface science 2017年 406卷 161-169页

作者： Guo, Gang Mao, Yuliang Zhong, Jianxin Yuan, Jianmei Zhao, Hongquan Hunan Key Laboratory for Micro–Nano Energy Materials and Devices School of Physics and Optoelectronic Engineering Xiangtan University Hunan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan411105 China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing401120 China

First-principles spin-polarized calculations are performed to design lithium storage materials using the active edges of zigzag silicene nanoribbon (ZSiNR). We predict that edge-adsorption of Li adatoms on zigzag silicene nanoribbon is preferred in energy to form new type lithium storage materials. Significant charge transfer from Li adatoms to Si atoms at the edges of ZSiNR is found, indicating the main ionic interactions. It is found that the band structures of ZSiNR with Li adsorptions are sensitive with the variation of sites of adatoms at the two edges. Ferro-magnetic to antiferro-magnetic change is found in ZSiNR with symmetrical adsorption of Li adatoms at its two edges. Other unsymmetrical Li adsorptions at the edges of ZSiNR prefer to stay in ferro-magnetic state as that in narrow pristine ZSiNR. © 2017 Elsevier B.V.

关键词： Adsorption

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Titelbild: Entropy-Mediated Stable Structural Evolution of Prussian White Cathodes for Long-Life Na-Ion Batteries (Angew. Chem. 7/2024)

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Angewandte Chemie 2024年第7期136卷

作者： Yueyue He Sören L. Dreyer Yin-Ying Ting Prof. Yuan Ma Dr. Yang Hu Dr. Damian Goonetilleke Dr. Yushu Tang Dr. Thomas Diemant Bei Zhou Dr. Piotr M. Kowalski Prof. Maximilian Fichtner Prof. Horst Hahn Prof. Jasmin Aghassi-Hagmann Dr. Torsten Brezesinski Dr. Ben Breitung Prof. Yanjiao Ma Institute of Nanotechnology Karlsruhe Institute of Technology (KIT) Hermann-von-Helmholtz Platz 1 76344 Eggenstein-Leopoldshafen Germany Institute of Energy and Climate Research (IEK-13) Forschungszentrum Jülich GmbH Wilhelm-Johnen-Str. 52428 Jülich Germany Chair of Theory and Computation of Energy Materials Faculty of Georesources and Materials Engineering RWTH Aachen University 52062 Aachen Germany Helmholtz Institute Ulm (HIU) for Electrochemical Energy Storage Helmholtzstr. 11 89081 Ulm Germany Current address: Corporate Research and Development Umicore Watertorenstraat 33 2250 Olen Belgium Jülich Aachen Research Alliance JARA Energy & Center for Simulation and Data Science (CSD) 52425 Jülich Germany School of Chemical Biological and Materials Engineering The University of Oklahoma Norman OK 73019 USA Current address: School of Energy and Mechanical Engineering Jiangsu Key Laboratory of New Power Batteries Nanjing Normal University Nanjing 210023 China

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Cover Picture: Entropy-Mediated Stable Structural Evolution of Prussian White Cathodes for Long-Life Na-Ion Batteries (Angew. Chem. Int. Ed. 7/2024)

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Angewandte Chemie International Edition 2024年第7期63卷

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Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network

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Scientific reports 2019年第1期9卷 2474页

作者： Dong-Ling Yu Yuan-Lin Ma Zu-Guo Yu Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. yuzuguo@***. School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Q4001 Australia. yuzuguo@***.

More and more research works have indicated that microRNAs (miRNAs) play indispensable roles in exploring the pathogenesis of diseases. Detecting miRNA-disease associations by experimental techniques in biology is expensive and time-consuming. Hence, it is important to propose reliable and accurate computational methods to exploring potential miRNAs related diseases. In our work, we develop a novel method (BRWHNHA) to uncover potential miRNAs associated with diseases based on hybrid recommendation algorithm and unbalanced bi-random walk. We first integrate the Gaussian interaction profile kernel similarity into the miRNA functional similarity network and the disease semantic similarity network. Then we calculate the transition probability matrix of bipartite network by using hybrid recommendation algorithm. Finally, we adopt unbalanced bi-random walk on the heterogeneous network to infer undiscovered miRNA-disease relationships. We tested BRWHNHA on 22 diseases based on five-fold cross-validation and achieves reliable performance with average AUC of 0.857, which an area under the ROC curve ranging from 0.807 to 0.924. As a result, BRWHNHA significantly improves the performance of inferring potential miRNA-disease association compared with previous methods. Moreover, the case studies on lung neoplasms and prostate neoplasms also illustrate that BRWHNHA is superior to previous prediction methods and is more advantageous in exploring potential miRNAs related diseases. All source codes can be downloaded from https://***/myl446/BRWHNHA .

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Parallel-in-Time with Fully Finite Element Multigrid for 2-D Space-fractional Diffusion Equations

arXiv

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arXiv 2018年

作者： Yue, X.Q. Shu, S. Xu, X.W. Bu, W.P. Pan, K.J. School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan411105 China Institute of Applied Physics and Computational Mathematics Beijing100088 China School of Mathematics and Statistics Central South University Hunan410083 China

The paper investigates a non-intrusive parallel time integration with multigrid for space-fractional diffusion equations in two spatial dimensions. We firstly obtain a fully discrete scheme via using the linear finite element method to discretize spatial and temporal derivatives to propagate solutions. Next, we present a non-intrusive time-parallelization and its two-level convergence analysis, where we algorithmically and theoretically generalize the MGRIT to time-dependent fine time-grid propagators. Finally, numerical illustrations show that the obtained numerical scheme possesses the saturation error order, theoretical results of the two-level variant deliver good predictions, and significant speedups can be achieved when compared to parareal and the sequential time-stepping approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Finite element method

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Spin-dependent electron transport along hairpin-like DNA molecules

arXiv

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arXiv 2020年

作者： Hu, Pei-Jia Wang, Si-Xian Gao, Xiao-Hui Zhang, Yan-Yang Fang, Tie-Feng Guo, Ai-Min Sun, Qing-Feng Hunan Key Laboratory for Super-microstructure and Ultrafast Process School of Physics and Electronics Central South University Changsha410083 China School of Physics and Electronic Engineering Guangzhou University Guangzhou510006 China School of Physical Science and Technology Lanzhou University Lanzhou730000 China International Center for Quantum Materials School of Physics Peking University Beijing100871 China Collaborative Innovation Center of Quantum Matter Beijing100871 China CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing100190 China

The chirality-induced spin selectivity (CISS), demonstrated in diverse chiral molecules by numerous experimental and theoretical groups, has been attracting extensive and ongoing interest in recent years. As the secondary structure of DNA, the charge transfer along DNA hairpins has been widely studied for more than two decades, finding that DNA hairpins exhibit spin-related effects as reported in recent experiments. Here, we propose a setup to demonstrate directly the CISS effect in DNA hairpins contacted by two nonmagnetic leads at both ends of the stem. Our results indicate that DNA hairpins present pronounced CISS effect and the spin polarization could be enhanced by using conducting molecules as the loop. In particular, DNA hairpins show several intriguing features, which are different from other chiral molecules. First, the local spin currents can flow circularly and assemble into a number of vortex clusters when the electron energy locates in the left/right electronic band of the stem. The chirality of vortex clusters in each band is the same and will be reversed by switching the electron energy from the left band to the right one, inducing the sign reversal of the spin polarization. Interestingly, the local spin currents can be greater than the corresponding spin component of the source-drain current. Second, both the conductance and the spin polarization can increase with molecular length as well as dephasing strength, contrary to the physical intuition that the transmission ability of molecular wires should be poorer when suffering from stronger scattering. Third, we unveil the optimal contact configuration of efficient electron transport and that of the CISS effect, which are distinct from each other and can be controlled by dephasing strength. The underlying physical mechanism is illustrated. Copyright © 2020, The Authors. All rights reserved.

关键词： Chirality

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Naive gabor networks for hyperspectral image classification

arXiv

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arXiv 2019年

作者： Liu, Chenying Li, Jun He, Lin Plaza, Antonio Li, Shutao Li, Bo Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou510275 China School of Automation Science and Engineering South China University of Technology Guangzhou510640 China College of Electrical and Information Engineering Hunan University Changsha410082 China Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politécnica University of Extremadura CáceresE-10071 Spain Beijing Key Laboratory of Digital Media School of Computer Science and Engineering State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

Recently, many convolutional neural network (CNN) methods have been designed for hyperspectral image (HSI) classification since CNNs are able to produce good representations of data, which greatly benefits from a huge number of parameters. However, solving such a high-dimensional optimization problem often requires a large amount of training samples in order to avoid overfitting. Additionally, it is a typical non-convex problem affected by many local minima and flat regions. To address these problems, in this paper, we introduce naive Gabor Networks or Gabor-Nets which, for the first time in the literature, design and learn CNN kernels strictly in the form of Gabor filters, aiming to reduce the number of involved parameters and constrain the solution space, and hence improve the performances of CNNs. Specifically, we develop an innovative phase-induced Gabor kernel, which is trickily designed to perform the Gabor feature learning via a linear combination of local low-frequency and high-frequency components of data controlled by the kernel phase. With the phase-induced Gabor kernel, the proposed Gabor-Nets gains the ability to automatically adapt to the local harmonic characteristics of the HSI data and thus yields more representative harmonic features. Also, this kernel can fulfill the traditional complex-valued Gabor filtering in a real-valued manner, hence making Gabor-Nets easily perform in a usual CNN thread. We evaluated our newly developed Gabor-Nets on three well-known HSIs, suggesting that our proposed Gabor-Nets can significantly improve the performance of CNNs, particularly with a small training set. Copyright © 2019, The Authors. All rights reserved.

关键词： Spectroscopy

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Entropy-Mediated Stable Structural Evolution of Prussian White Cathodes for Long-Life Na-Ion Batteries

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Angewandte Chemie 2023年第7期136卷

The high-entropy approach is applied to monoclinic Prussian White (PW) Na-ion cathodes to address the issue of unfavorable multilevel phase transitions upon electrochemical cycling, leading to poor stability and capacity decay. A series of Mn-based samples with up to six metal species sharing the N-coordinated positions was synthesized. The material of composition Na 1.65 Mn 0.4 Fe 0.12 Ni 0.12 Cu 0.12 Co 0.12 Cd 0.12 [Fe(CN) 6 ] 0.92 □ 0.08 ⋅ 1.09H 2 O was found to exhibit superior cyclability over medium/low-entropy and conventional single-metal PWs. We also report, to our knowledge for the first time, that a high-symmetry crystal structure may be advantageous for high-entropy PWs during battery operation. computational comparisons of the formation enthalpy demonstrate that the compositionally less complex materials are prone to phase transitions, which negatively affect cycling performance. Based on data from complementary characterization techniques, an intrinsic mechanism for the stability improvement of the disordered PW structure upon Na + insertion/extraction is proposed, namely the dual effect of suppression of phase transitions and mitigation of gas evolution.

关键词： High-Entropy Materials Outgassing Phase Transitions Prussian White Sodium-Ion Cathode

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