Doping dependent charge injection and band alignment in organic field-effect transistors

We have studied metal/organic semiconductor charge injection in poly(3-hexylthiophene) (P3HT) field-effect transistors with Pt and Au electrodes as a function of annealing in vacuum. At low impurity dopant densities, Au/P3HT contact resistances increase and become nonohmic. In contrast, Pt/P3HT contacts remain ohmic even at far lower doping. Ultraviolet photoemission spectroscopy (UPS) reveals that metal/P3HT band alignment shifts dramatically as samples are dedoped, leading to an increased injection barrier for holes, with a greater shift for Au/P3HT. These results demonstrate that doping can drastically alter band alignment and the charge injection process at metal/organic interfaces.Comment: 5 pages, 4 figure

Single crystal growth and physical properties of SrFe2_{2}(As1−x_{1-x}Px_{x})2_{2}

We report a crystal growth and physical properties of SrFe$_{2}$(As$_{1-x}$P$_{x}$)$_{2}$. The single crystals for various $x$s were grown by a self flux method. For $x = 0.35$, $T_c$ reaches the maximum value of 30\,K and the electrical resistivity $\rho$($T$) shows $T$-linear dependence. As $x$ increases, $T_{c}$ decreases and $\rho$($T$) changes to $T^2$-behavior, indicating a standard Fermi liquid. These results suggest that a magnetic quantum critical point exists around $x=0.35$.Comment: 4 pages, 4 figures, accepted to Supplemental issue of the Journal of Physical Society of Japan (JPSJ

Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks

Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Localized magnetic states in biased bilayer and trilayer graphene

We study the localized magnetic states of impurity in biased bilayer and trilayer graphene. It is found that the magnetic boundary for bilayer and trilayer graphene presents the mixing features of Dirac and conventional fermion. For zero gate bias, as the impurity energy approaches the Dirac point, the impurity magnetization region diminishes for bilayer and trilayer graphene. When a gate bias is applied, the dependence of impurity magnetic states on the impurity energy exhibits a different behavior for bilayer and trilayer graphene due to the opening of a gap between the valence and the conduction band in the bilayer graphene with the gate bias applied. The magnetic moment and the corresponding magnetic transition of the impurity in bilayer graphene are also investigated.Comment: 16 pages,6 figure

Superconducting gap symmetry of Ba0.6K0.4Fe2As2 studied by angle-resolved photoemission spectroscopy

We have performed high-resolution angle-resolved photoemission spectroscopy on the optimally-doped Ba$_{0.6}$K$_{0.4}$Fe$_2$As$_2$ compound and determined the accurate momentum dependence of the superconducting (SC) gap in four Fermi-surface sheets including a newly discovered outer electron pocket at the M point. The SC gap on this pocket is nearly isotropic and its magnitude is comparable ($\Delta$ $\sim$ 11 meV) to that of the inner electron and hole pockets ($\sim$12 meV), although it is substantially larger than that of the outer hole pocket ($\sim$6 meV). The Fermi-surface dependence of the SC gap value is basically consistent with $\Delta$($k$) = $\Delta$$_0$cos$k_x$cos$k_y$ formula expected for the extended s-wave symmetry. The observed finite deviation from the simple formula suggests the importance of multi-orbital effects.Comment: 4 pages, 3 figures, 1 tabl

Angle-resolved photoemission studies of the superconducting gap symmetry in Fe-based superconductors

The superconducting gap is the fundamental parameter that characterizes the superconducting state, and its symmetry is a direct consequence of the mechanism responsible for Cooper pairing. Here we discuss about angle-resolved photoemission spectroscopy measurements of the superconducting gap in the Fe-based high-temperature superconductors. We show that the superconducting gap is Fermi surface dependent and nodeless with small anisotropy, or more precisely, a function of momentum. We show that while this observation is inconsistent with weak coupling approaches for superconductivity in these materials, it is well supported by strong coupling models and global superconducting gaps. We also suggest that the strong anisotropies measured by other probes sensitive to the residual density of states are not related to the pairing interaction itself, but rather emerge naturally from the smaller lifetime of the superconducting Cooper pairs that is a direct consequence of the momentum dependent interband scattering inherent to these materials.Comment: 7 pages, 5 figure

Bidirectional optimization of the melting spinning process

This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities