Related papers: Computation of electron quantum transport in graph…
In graphene nanoribbons (GNRs), the lateral confinement of charge carriers opens a band gap, the key feature to enable novel graphene-based electronics. Successful synthesis of GNRs has triggered efforts to realize field-effect transistors…
We derive an improved version of the recursive Green's function formalism (RGF), which is a standard tool in the quantum transport theory. We consider the case of disordered quasi one-dimensional materials where the disorder is applied in…
We present some computational simulations of graphene-based nanoribbons with a number of half-twists varying from 0 to 4 and two types of defects obtained by removing a single carbon atom from two different sites. Optimized geometries are…
The article introduces a new method for applying Quantum Clustering to graph structures. Quantum Clustering (QC) is a novel density-based unsupervised learning method that determines cluster centers by constructing a potential function. In…
Graphene nanoribbons with sub-nanometer widths are extremely interesting for nanoscale electronics and devices as they combine the unusual transport properties of graphene with the opening of a band gap due to quantum confinement in the…
The coupling of geometrical and electronic properties is a promising venue to engineer conduction properties in graphene. Confinement added to strain allows for interplay of different transport mechanisms with potential device applications.…
An efficient computational methodology is used to explore charge transport properties in chemically-modified (and randomly disordered) graphene-based materials. The Hamiltonians of various complex forms of graphene are constructed using…
One of the main challenges in Heavy Energy Physics is to make fast analysis of high amount of experimental and simulated data. At LHC-CERN one p-p event is approximate 1 Mb in size. The time taken to analyze the data and obtain fast results…
Recent studies have shown that Binary Graph Neural Networks (GNNs) are promising for saving computations of GNNs through binarized tensors. Prior work, however, mainly focused on algorithm designs or training techniques, leaving it open to…
We present an efficient numerical approach for treating ballistic quantum transport across devices described by tight binding (TB) Hamiltonians designated to systems with localized potential defects. The method is based on the wave function…
Within the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations (ODE) for the computation of chemical kinetics stands as the primary demand on computational resources. Meanwhile,…
We investigate the electronic transport properties of copper-graphene composites using a density-functional framework. Conduction in composites by varying the interface distance of a copper/graphene/copper (Cu/G/Cu) interface models was…
We present calculations of electronic quantum transport in graphene nanoribbons with adsorbed H, F, OH and O, based on a tight binding model derived from extended Huckel theory. The relaxed atomic geometries of the adsorbates and graphene…
Graphene nanoribbon (GNR) field-effect transistors (FETs) with widths down to 12 nm have been fabricated by electron beam lithography using a wafer-scale chemical vapor deposition (CVD) process to form the graphene. The GNR FETs show…
We present a systematic study of electron backscattering phenomena during conduction for graphene nanoribbons with single-vacancy scatterers and dimensions within the capabilities of modern lithographic techniques. Our analysis builds upon…
Most relatively modern desktop or even laptop computers contain a graphics card useful for more than showing colors on a screen. In this paper, we make a case for why you should learn enough about GPU (graphics processing unit) computing to…
We study the transport of charge carriers through finite graphene structures. The use of numerical exact kernel polynomial and Green function techniques allows us to treat actual sized samples beyond the Dirac-cone approximation.…
Grain boundaries (GBs) are ubiquitous in polycrystalline graphene materials obtained by various growth methods. It has been shown previously that considerable electrical transport gap can be opened by grain boundaries. On the other hand,…
As high energy physics experiments reach higher luminosities and intensities, the computing burden for real time data processing and reduction grows. Following the developments in the computing landscape, multi-core processors such as…
We propose an algorithm for determining the zeros of the electric conductivity in large molecular nanonstructures such as graphene sheets. To this end, we employ the inverse graph method, whereby non-zeros of the Green's functions are…