Effect of Impurity Adsorption on the Electronic and Transport Properties of Graphene Nanogaps

Graphene stands out as a versatile material with several uses in fields that range from electronics to biology. In particular, graphene has been proposed as an electrode in molecular electronics devices that are expected to be more stable and reproducible than typical ones based on metallic electrodes. In this work, we study by means of first principles, simulations and a tight-binding model the electronic and transport properties of graphene nanogaps with straight edges and different passivating atoms: Hydrogen or elements of the second row of the periodic table (boron, carbon, nitrogen, oxygen, and fluoride). We use the tight-binding model to reproduce the main ab-initio results and elucidate the physics behind the transport properties. We observe clear patterns that emerge in the conductance and the current as one moves from boron to fluoride. In particular, we find that the conductance decreases and the tunneling decaying factor increases from the former to the latter. We explain these trends in terms of the size of the atom and its onsite energy. We also find a similar pattern for the current, which is ohmic and smooth in general. However, when the size of the simulation cell is the smallest one along the direction perpendicular to the transport direction, we obtain highly non-linear behavior with negative differential resistance. This interesting and surprising behavior can be explained by taking into account the presence of Fano resonances and other interference effects, which emerge due to couplings to side atoms at the edges and other couplings across the gap. Such features enter the bias window as the bias increases and strongly affect the current, giving rise to the non-linear evolution. As a whole, these results can be used as a template to understand the transport properties of straight graphene nanogaps and similar systems and distinguish the presence of different elements in the junction.

Theoretical analysis of the inverse Edelstein effect at the LaAlO3 / SrTiO3 interface with an effective tight-binding model: Important role of the second dxy subband

The two-dimensional electron gas formed at interfaces between SrTiO3 and other materials has attracted much attention since extremely efficient spin-to-charge current conversion has been recently observed at these interfaces. This has been attributed to their complicated quantized multi-orbital structures with a topological feature. However, there are few reports quantitatively comparing the conversion efficiency values between experiments and theoretical calculations at these interfaces. In this study, we theoretically explain the experimental temperature dependence of the spin-to-charge current conversion efficiency using an 8×8 effective tight-binding model considering the second dxy subband, revealing the vital role of the quantization of the multi-band structure.

A 64 bit quantum dragon data-set for machine learning

Design and examples of a sixty-four bit quantum dragon data-set are presented. A quantum dragon is a tight-binding model for a strongly disordered nanodevice, but when connected to appropriate semi-infinite leads has complete electron transmission for a finite interval of energies. The labeled data-set contains records which are quantum dragons, which are not quantum dragons, and which are indeterminate. The quantum dragon data-set is designed to be difficult for trained humans and machines to label a nanodevice with regard to its quantum dragon property. The 64 bit record length allows the data-set to be utilized in restricted Boltzmann machines which fit well onto the D-Wave 2000Q quantum annealer architecture.