55 research outputs found
Decreasing excitation gap in Andreev billiards by disorder scattering
We investigate the distribution of the lowest-lying energy states in a
disordered Andreev billiard by solving the Bogoliubov-de Gennes equation
numerically. Contrary to conventional predictions we find a decrease rather
than an increase of the excitation gap relative to its clean ballistic limit.
We relate this finding to the eigenvalue spectrum of the Wigner-Smith time
delay matrix between successive Andreev reflections. We show that the longest
rather than the mean time delay determines the size of the excitation gap. With
increasing disorder strength the values of the longest delay times increase,
thereby, in turn, reducing the excitation gap.Comment: 6 pages, 5 figures, submitted to EP
Photovoltaic effect in an electrically tunable van der Waals heterojunction
Semiconductor heterostructures form the cornerstone of many electronic and
optoelectronic devices and are traditionally fabricated using epitaxial growth
techniques. More recently, heterostructures have also been obtained by vertical
stacking of two-dimensional crystals, such as graphene and related two-
dimensional materials. These layered designer materials are held together by
van der Waals forces and contain atomically sharp interfaces. Here, we report
on a type- II van der Waals heterojunction made of molybdenum disulfide and
tungsten diselenide monolayers. The junction is electrically tunable and under
appropriate gate bias, an atomically thin diode is realized. Upon optical
illumination, charge transfer occurs across the planar interface and the device
exhibits a photovoltaic effect. Advances in large-scale production of
two-dimensional crystals could thus lead to a new photovoltaic solar
technology.Comment: 26 pages, 14 figures, Nano Letters 201
Non-retracing orbits in Andreev billiards
The validity of the retracing approximation in the semiclassical quantization
of Andreev billiards is investigated. The exact energy spectrum and the
eigenstates of normal-conducting, ballistic quantum dots in contact with a
superconductor are calculated by solving the Bogoliubov-de Gennes equation and
compared with the semiclassical Bohr-Sommerfeld quantization for periodic
orbits which result from Andreev reflections. We find deviations that are due
to the assumption of exact retracing electron-hole orbits rather than the
semiclassical approximation, as a concurrently performed
Einstein-Brillouin-Keller quantization demonstrates. We identify three
different mechanisms producing non-retracing orbits which are directly
identified through differences between electron and hole wave functions.Comment: 9 pages, 12 figures, Phys. Rev. B (in print), high resolution images
available upon reques
Graphene quantum dots: Beyond a Dirac billiard
We present realistic simulations of quantum confinement effects in ballistic
graphene quantum dots with linear dimensions of 10 to 40 nm. We determine
wavefunctions and energy level statistics in the presence of disorder resulting
from edge roughness, charge impurities, or short-ranged scatterers. Marked
deviations from a simple Dirac billiard for massless fermions are found. We
find a remarkably stable dependence of the nearest-neighbor level spacing on
edge roughness suggesting that the roughness of fabricated devices can be
potentially characterized by the distribution of measured Coulomb blockade
peaks.Comment: 5 figures, higher resolution available upon reques
Machine learning sparse tight-binding parameters for defects
We employ machine learning to derive tight-binding parametrizations for the electronic structure of defects. We test several machine learning methods that map the atomic and electronic structure of a defect onto a sparse tight-binding parameterization. Since Multi-layer perceptrons (i.e., feed-forward neural networks) perform best we adopt them for our further investigations. We demonstrate the accuracy of our parameterizations for a range of important electronic structure properties such as band structure, local density of states, transport and level spacing simulations for two common defects in single layer graphene. Our machine learning approach achieves results comparable to maximally localized Wannier functions (i.e., DFT accuracy) without prior knowledge about the electronic structure of the defects while also allowing for a reduced interaction range which substantially reduces calculation time. It is general and can be applied to a wide range of other materials, enabling accurate large-scale simulations of material properties in the presence of different defects
Electrostatically confined monolayer graphene quantum dots with orbital and valley splittings
The electrostatic confinement of massless charge carriers is hampered by
Klein tunneling. Circumventing this problem in graphene mainly relies on
carving out nanostructures or applying electric displacement fields to open a
band gap in bilayer graphene. So far, these approaches suffer from edge
disorder or insufficiently controlled localization of electrons. Here we
realize an alternative strategy in monolayer graphene, by combining a
homogeneous magnetic field and electrostatic confinement. Using the tip of a
scanning tunneling microscope, we induce a confining potential in the Landau
gaps of bulk graphene without the need for physical edges. Gating the localized
states towards the Fermi energy leads to regular charging sequences with more
than 40 Coulomb peaks exhibiting typical addition energies of 7-20 meV. Orbital
splittings of 4-10 meV and a valley splitting of about 3 meV for the first
orbital state can be deduced. These experimental observations are
quantitatively reproduced by tight binding calculations, which include the
interactions of the graphene with the aligned hexagonal boron nitride
substrate. The demonstrated confinement approach appears suitable to create
quantum dots with well-defined wave function properties beyond the reach of
traditional techniques
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