Microscopic theory of the proximity effect in superconductor-graphene nanostructures

We present a theoretical analysis of the proximity effect at a graphene-superconductor interface. We use a tight-binding model for the electronic states in this system which allows to describe the interface at the microscopic level. Two different interface models are proposed: one in which the superconductor induces a finite pairing in the graphene regions underneath, thus maintaining the honeycomb structure at the interface and one that assumes that the graphene layer is directly coupled to a bulk superconducting electrode. We show that properties like the Andreev reflection probability and its channel decomposition depend critically on the model used to describe the interface. We also study the proximity effect on the local density of states on the graphene. For finite layers we analyze the induced minigap and how it is reduced when the length of the layer increases. Results for the local density of states profiles for finite and semi-infinite layers are presented.Comment: 9 pages, 7 figures, submitted to Phys. Rev.

Microscopic theory of Cooper pair beam splitters based on carbon nanotubes

We analyze microscopically a Cooper pair splitting device in which a central superconducting lead is connected to two weakly coupled normal leads through a carbon nanotube. We determine the splitting efficiency at resonance in terms of geometrical and material parameters, including the effect of spin-orbit scattering. While the efficiency in the linear regime is limited to 50% and decay exponentially as a function of the width of the superconducting region we show that it can rise up to $\sim 100$ in the non-linear regime for certain regions of the stability diagram.Comment: 5 pages, 5 figure

Transport in superlattices on single layer graphene

We study transport in undoped graphene in the presence of a superlattice potential both within a simple continuum model and using numerical tight-binding calculations. The continuum model demonstrates that the conductivity of the system is primarily impacted by the velocity anisotropy that the Dirac points of graphene develop due to the potential. For one-dimensional superlattice potentials, new Dirac points may be generated, and the resulting conductivities can be approximately described by the anisotropic conductivities associated with each Dirac point. Tight-binding calculations demonstrate that this simple model is quantitatively correct for a single Dirac point, and that it works qualitatively when there are multiple Dirac points. Remarkably, for a two dimensional potential which may be very strong but introduces no anisotropy in the Dirac point, the conductivity of the system remains essentially the same as when no external potential is present.Comment: 8 pages, 7 figures, submitted to Phys. Rev.

Selective focusing of electrons and holes in a graphene-based superconducting lens

We show that a graphene pnp junction with a central superconducting electrode acts as a Veselago lens for incoming electrons by focusing them and their phase-conjugated counterpart (holes) into di erent points of the optical axis. This selective focusing suggested by a simple trajectory analysis is con rmed by fully microscopic calculations. Although the focusing pattern is degraded by deviations from the ideal conditions we show that it remains visible for a wide range of parameters. We discuss how this property can be useful for the detection of entangled electron pairs.This work was supported by COLCIENCIAS, project 110152128235 (S.G. and W.J.H.), and MICINN-Spain via Grant No. FIS2008-04209 and EU project SE2N

Analysis of computational approaches for motif discovery

Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature

Emergence of Superlattice Dirac Points in Graphene on Hexagonal Boron Nitride

The Schr\"odinger equation dictates that the propagation of nearly free electrons through a weak periodic potential results in the opening of band gaps near points of the reciprocal lattice known as Brillouin zone boundaries. However, in the case of massless Dirac fermions, it has been predicted that the chirality of the charge carriers prevents the opening of a band gap and instead new Dirac points appear in the electronic structure of the material. Graphene on hexagonal boron nitride (hBN) exhibits a rotation dependent Moir\'e pattern. In this letter, we show experimentally and theoretically that this Moir\'e pattern acts as a weak periodic potential and thereby leads to the emergence of a new set of Dirac points at an energy determined by its wavelength. The new massless Dirac fermions generated at these superlattice Dirac points are characterized by a significantly reduced Fermi velocity. The local density of states near these Dirac cones exhibits hexagonal modulations indicating an anisotropic Fermi velocity.Comment: 16 pages, 6 figure

The genome of the protozoan parasite Cystoisospora suis and a reverse vaccinology approach to identify vaccine candidates

Vaccine development targeting protozoan parasites remains challenging, partly due to the complex interactions between these eukaryotes and the host immune system. Reverse vaccinology is a promising approach for direct screening of genome sequence assemblies for new vaccine candidate proteins. Here, we applied this paradigm to Cystoisospora suis, an apicomplexan parasite that causes enteritis and diarrhea in suckling piglets and economic losses in pig production worldwide. Using Next Generation Sequencing we produced an ∼84 Mb sequence assembly for the C. suis genome, making it the first available reference for the genus Cystoisospora. Then, we derived a manually curated annotation of more than 11,000 protein-coding genes and applied the tool Vacceed to identify 1,168 vaccine candidates by screening the predicted C. suis proteome. To refine the set of candidates, we looked at proteins that are highly expressed in merozoites and specific to apicomplexans. The stringent set of candidates included 220 proteins, among which were 152 proteins with unknown function, 17 surface antigens of the SAG and SRS gene families, 12 proteins of the apicomplexan-specific secretory organelles including AMA1, MIC6, MIC13, ROP6, ROP12, ROP27, ROP32 and three proteins related to cell adhesion. Finally, we demonstrated in vitro the immunogenic potential of a C. suis-specific 42 kDa transmembrane protein, which might constitute an attractive candidate for further testing