Large domain-wall currents in epitaxial Au/BiFeO3/SrRuO3 thin-film capacitors with modulated oxygen vacancy and wall densities

Large domain wall (DW) conductivity in an insulating ferroelectric plays an important role in the future nanosensors and nonvolatile memories. However, the wall current was usually too small to drive high-speed memory circuits and other agile nanodevices requiring high output-powers. Here, a large domain-wall current of 67.8 μA in a high on/off ratio of ~4460 was observed in an epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitor with the minimized oxygen vacancy concentration. The studies from read current-write voltage hysteresis loops and piezo-response force microscope images consistently showed remaining of partially unswitched domains after application of an opposite poling voltage that increased domain wall density and wall current greatly. A theoretical model was proposed to explain the large wall current. According to this model, the domain reversal occurs with the appearance of head-to-head and tail-to-tail 180° domain walls (DWs), resulting in the formation of highly conductive wall paths. As the applied voltage increased, the domain-wall number increased to enhance the on-state current, in agreement with the measurements of current-voltage curves. This work paves a way to modulate DW currents within epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitors through the optimization of both oxygen vacancy and domain wall densities to achieve large output powers of modern domain-wall nanodevices.     

Influence of domain switching process on the electrical fatigue behavior of ferroelectrics

We report an experimental approach, designed based on the recent findings that domain switching in ferroelectric ceramics can be separated into three regimes during antiparallel electric field loading, to investigate the influence of domain switching process on the electrical fatigue behavior of ferroelectrics. Uniaxial compressive stress (−2 MPã -100 MPa) and thermal loading (20 °C–150 °C) were used to tune the domain switching process. Under the same loading condition, the bipolar electrical fatigue behavior of soft lead zirconate titanate ceramics was systematically characterized. The amplitude and frequency of the applied electric field are 2 kV/mm and 10 Hz, respectively. By analyzing the evolution of the domain switching process, combined with the measured polarization and strain response, as well as the cracks observed on the surface of the specimen, it is found that the fatigue of ferroelectric ceramics was mainly related to the domain switching process near the coercive electric field: the regime 2 defined in this paper. The underlying mechanism was further discussed by considering the interplay between the domain switching process with the main factors affecting the electrical fatigue of ferroelectrics, namely defect redistribution, charge carrier injection, and crack initiation.     

两阶段领域自适应学习

针对领域自适应问题中源域和目标域的联合分布差异最小化问题,提出两阶段领域自适应学习方法.在第一阶段考虑样本标签和数据结构的判别信息,通过学习一个共享投影变换,使投影后的共享空间中边缘分布的差异最小.第二阶段利用源域标记数据和目标域非标记数据学习一个带结构风险的自适应分类器,不仅能最小化源域和目标域条件分布差异,还能进一步保持源域和目标域边缘分布的流形一致性.在3个基准数据集上的实验表明,文中方法在平均分类准确率和Kappa系数两项评价指标上均表现较优.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

An overlapping domain decomposition dual reciprocity method

We present a domain decomposition boundary integral equation method for two-dimensional partial differential equations. The overlapping Schwarz method is employed to improve the dual reciprocity boundary element method. The resulting algorithm turns out to be more accurate than a non-overlapping approach previously proposed. Some numerical results showing the improved accuracy and efficiency of the methods are given.     

椭圆型偏微分方程的加法Schwarz方法

1.引 言 古典加法Schwarz方法(ASM)对于一般问题收敛很慢,在大多数情况下, ASM只能作为预条件子.另一方面,ASM的并行性能非常好,尤其适合大规模粗粒度并行计算,近年来随着并行机系统及并行计算的兴起,ASM重新受到重视.许多学者研究了怎样提高ASM的收敛速度[1,2,4].他们发现加法Schwarz方法之所以收敛慢是由于在内边界上采用     

RS码频域纠错编码在激光对潜通信信道中的实现方法

介绍了信道编码在激光对潜通信系统中的重要作用，介绍了频域编译ＲＳ码的基本方法，并给出了脉冲位置调制信道的ＲＳ码频域编译码的计算机模拟方法和结果。     

Restricted overlapping balancing domain decomposition methods and restricted coarse problems for the Helmholtz problem

Overlapping balancing domain decomposition methods and their combination with restricted additive Schwarz methods are proposed for the Helmholtz equation. These new methods also extend previous work on non-overlapping balancing domain decomposition methods toward simplifying their coarse problems and local solvers. They also extend restricted Schwarz methods, originally designed to overlapping domain decomposition and Dirichlet local solvers, to the case of non-overlapping domain decomposition and/or Neumann and Sommerfeld local solvers. Finally, we introduce coarse spaces based on partitions of unity and planes waves, and show how oblique projection coarse problems can be designed from restricted additive Schwarz methods. Numerical tests are presented.     

Semi-supervised model adaptation for statistical machine translation

Statistical machine translation systems are usually trained on large amounts of bilingual text (used to learn a translation model), and also large amounts of monolingual text in the target language (used to train a language model). In this article we explore the use of semi-supervised model adaptation methods for the effective use of monolingual data from the source language in order to improve translation quality. We propose several algorithms with this aim, and present the strengths and weaknesses of each one. We present detailed experimental evaluations on the French–English EuroParl data set and on data from the NIST Chinese–English large-data track. We show a significant improvement in translation quality on both tasks.     

Modelling diffusion-controlled kinetics in equilibrium and driven alloys

Summary We introduce a very simple model for thermally activated atomic migration on a lattice, and several techniques to handle it. For thermodynamical systems, the model can be used for simulating decomposition paths taking into account relevant metallurgical features. Close to equilibrium, the simplest mean-field approximation of the model can be linearized with respect to the departure from equilibrium; one then gets a microscopic interpretation of classical phenomenological coefficients, such as mobility, interfacial transfer coefficient, rate constants for the coupled relaxation of concentration and order fields. Further away from the equilibrium, the nonlinearities can be taken into account in a consistent way. For driven alloys, i.e. alloys submitted to external forcing, forced atomic migration is added to the model and new features emerge: the model is supported by several experimental results some of which confirmed its predictions a posteriori.