20,774 research outputs found
Growth of Epitaxial Oxide Thin Films on Graphene
The transfer process of graphene onto the surface of oxide substrates is well known. However, for many devices, we require high quality oxide thin films on the surface of graphene. This step is not understood. It is not clear why the oxide should adopt the epitaxy of the underlying oxide layer when it is deposited on graphene where there is no lattice match. To date there has been no explanation or suggestion of mechanisms which clarify this step. Here we show a mechanism, supported by first principles simulation and structural characterisation results, for the growth of oxide thin films on graphene. We describe the growth of epitaxial SrTiO3 (STO) thin films on a graphene and show that local defects in the graphene layer (e.g. grain boundaries) act as bridgepillar spots that enable the epitaxial growth of STO thin films on the surface of the graphene layer. This study, and in particular the suggestion of a mechanism for epitaxial growth of oxides on graphene, offers new directions to exploit the development of oxide/graphene multilayer structures and devices
Bosonic resonating valence bond wave function for doped Mott insulators
We propose a new class of ground states for doped Mott insulators in the
electron second-quantization representation. They are obtained from a bosonic
resonating valence bond (RVB) theory of the t-J model. At half filling, the
ground state describes spin correlations of the S=1/2 Heisenberg model very
accurately. Its spin degrees of freedom are characterized by RVB pairing of
spins, the size of which decreases continuously as holes are doped into the
system. Charge degrees of freedom emerge upon doping and are described by
twisted holes in the RVB background. We show that the twisted holes exhibit an
off diagonal long range order (ODLRO) in the pseudogap ground state, which has
a finite pairing amplitude, but is short of phase coherence. Unpaired spins in
such a pseudogap ground state behave as free vortices, preventing
superconducting phase coherence. The existence of nodal quasiparticles is also
ensured by such a hidden ODLRO in the ground state, which is
non-Fermi-liquid-like in the absence of superconducting phase coherence. Two
distinct types of spin excitations can also be constructed. The superconducting
instability of the pseudogap ground state is discussed and a d-wave
superconducting ground state is obtained. This class of pseudogap and
superconducting ground states unifies antiferromagnetism, pseudogap,
superconductivity, and Mott physics into a new state of matter.Comment: 28 pages, 5 figures, final version to appear in Phys. Rev.
Charmless decays and new physics effects in the mSUGRA model
By employing the QCD factorization approach, we calculate the new physics
contributions to the branching radios of the two-body charmless and
decays in the framework of the minimal supergravity (mSUGRA) model.
we choose three typical sets of the mSUGRA input parameters in which the Wilson
coefficient can be either SM-like (the case A and C) or has
a flipped-sign (the case B). We found numerically that (a) the SUSY
contributions are always very small for both case A and C; (b) for those
tree-dominated decays, the SUSY contributions in case B are also very small;
(c) for those QCD penguin-dominated decay modes, the SUSY contributions in case
B can be significant, and can provide an enhancement about to
the branching ratios of and decays, but a
reduction about to decays; and (d) the
large SUSY contributions in the case B may be masked by the large theoretical
errors dominated by the uncertainty from our ignorance of calculating the
annihilation contributions in the QCD factorization approach.Comment: 34 pages, 8 PS figures, this is the correct version
Reversible Fluorination of Graphene: towards a Two-Dimensional Wide Bandgap Semiconductor
We report the synthesis and evidence of graphene fluoride, a two-dimensional
wide bandgap semiconductor derived from graphene. Graphene fluoride exhibits
hexagonal crystalline order and strongly insulating behavior with resistance
exceeding 10 G at room temperature. Electron transport in graphene
fluoride is well described by variable-range hopping in two dimensions due to
the presence of localized states in the band gap. Graphene obtained through the
reduction of graphene fluoride is highly conductive, exhibiting a resistivity
of less than 100 k at room temperature. Our approach provides a new
path to reversibly engineer the band structure and conductivity of graphene for
electronic and optical applications.Comment: 7 pages, 5 figures, revtex, to appear in PR
On the structure of the scalar mesons and
We investigate the structure of the scalar mesons and
within realistic meson-exchange models of the and
interactions. Starting from a modified version of the J\"ulich model for
scattering we perform an analysis of the pole structure of the
resulting scattering amplitude and find, in contrast to existing models, a
somewhat large mass for the ( MeV,
MeV). It is shown that our model provides a description of
data comparable in quality with those of
alternative models. Furthermore, the formalism developed for the
system is consistently extended to the interaction leading to a
description of the as a dynamically generated threshold effect
(which is therefore neither a conventional state nor a
bound state). Exploring the corresponding pole position the
is found to be rather broad ( MeV,
MeV). The experimentally observed smaller width results from the influence of
the nearby threshold on this pole.Comment: 25 pages, 15 Postscript figure
Evolution of InAs branches in InAs/GaAs nanowire heterostructures
Branched nanowireheterostructures of InAs∕GaAs were observed during Au-assisted growth of InAs on GaAsnanowires. The evolution of these branches has been determined through detailed electron microscopy characterization with the following sequence: (1) in the initial stage of InAsgrowth, the Au droplet is observed to slide down the side of the GaAsnanowire, (2) the downward movement of Aunanoparticle later terminates when the nanoparticle encounters InAsgrowing radially on the GaAsnanowire sidewalls, and (3) with further supply of In and As vapor reactants, the Aunanoparticles assist the formation of InAs branches with a well-defined orientation relationship with GaAs∕InAs core/shell stems. We anticipate that these observations advance the understanding of the kink formation in axial nanowireheterostructures.The Australian Research Council is acknowledged for
the financial support of this project. One of the authors
M.P. acknowledges the support of an International Postgraduate
Research Scholarship
Equation-Free Dynamic Renormalization: Self-Similarity in Multidimensional Particle System Dynamics
We present an equation-free dynamic renormalization approach to the
computational study of coarse-grained, self-similar dynamic behavior in
multidimensional particle systems. The approach is aimed at problems for which
evolution equations for coarse-scale observables (e.g. particle density) are
not explicitly available. Our illustrative example involves Brownian particles
in a 2D Couette flow; marginal and conditional Inverse Cumulative Distribution
Functions (ICDFs) constitute the macroscopic observables of the evolving
particle distributions.Comment: 7 pages, 5 figure
Microseismic signal denoising and separation based on fully convolutional encoder–decoder network
Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method simultaneously learns the sparse features in the time–frequency domain, and the mask-related mapping function for signal separation. The results show that the proposed method has an impressive performance on denoising microseismic signals containing various types and intensities of noise. Furthermore, the method works well even when a similar frequency band is shared between the microseismic signals and the noises. The proposed method, compared to the existing methods, significantly improves the signal–noise ratio thanks to minor changes of the microseismic signal (less distortion in the waveform). Additionally, the proposed methods preserve the shape and amplitude characteristics so that it allows better recovery of the real waveform. This method is exceedingly useful for the automatic processing of the microseismic signal. Further, it has excellent potential to be extended to the study of exploration seismology and earthquakes
Microseismic signal denoising and separation based on fully convolutional encoder–decoder network
Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method simultaneously learns the sparse features in the time–frequency domain, and the mask-related mapping function for signal separation. The results show that the proposed method has an impressive performance on denoising microseismic signals containing various types and intensities of noise. Furthermore, the method works well even when a similar frequency band is shared between the microseismic signals and the noises. The proposed method, compared to the existing methods, significantly improves the signal–noise ratio thanks to minor changes of the microseismic signal (less distortion in the waveform). Additionally, the proposed methods preserve the shape and amplitude characteristics so that it allows better recovery of the real waveform. This method is exceedingly useful for the automatic processing of the microseismic signal. Further, it has excellent potential to be extended to the study of exploration seismology and earthquakes
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