arXiv subjects

Geraldo Magela e Silva

Publications and source records attributed to Geraldo Magela e Silva.

5 recordsLinked to original sources

arXiv2020

Charge Localization and Hopping in a Topologically Engineered GNR

Graphene nanoribbons (GNRs) are promising two-dimensional materials with various technological applications, in particular for the armchair GNR families that have a semiconductor character. Recently, methods that allowed for the control of GNR's topology have been developed, resulting in the production of nanoribbons composed of alternating segments of two distinct armchair GNR families (7 and 9-AGNRs) connected in heterojunctions. This GNR displays two topological bands that lie between the valence and conduction bands that effectively modulates the nanoribbon bandgap. Here, we employ a two-dimensional extension of the Su-Schrieffer-Heeger model to study morphological and electronic properties of this new material in both neutral and charged states. Results demonstrate that charge injection in this system results in the formation of polarons that localize strictly in the 9-AGNRs segments of the system and whose mobility is highly impaired by the system's topology. We further show polaron displacement by means of hopping between 9-AGNR portions of the system, suggesting this mechanism for charge transport in this material.

cond-mat.mtrl-sci↗

arXiv2020

Charge Transport Mechanism in Chevron--Graphene Nanoribbons

From the moment atomic precision control of the growth process of graphene was achieved, more elaborated carbon allotropes were proposed opening new channels for flat optoelectronics at the nanoscale. A special type of this material presenting a V-shape (or "kinked" pattern) was recently synthesized and named Chevron-graphene nanoribbons (C-GNRs). To realize the reach of C--GNRs in developing new applications, the formation, and transport of charge carriers in their lattices should be primarily understood. Here, we investigate the static and dynamical properties of quasiparticles in C-GNRs. We study the effects of electron-phonon coupling and doping on the system. We also determine the kind of charge carriers present in C--GNR. It is observed that a phase transition occurs between a delocalized regime of conduction and regimes mediated by charge carriers. Such a phase transition is highly dependent on the doping concentration. Remarkably, crucial differences from the transport in standard graphene nanoribbons are identified. These factors are noted to have a profound impact on the mobility on the system which, in turn, should decisively impact the performance of electronic devices based on C-GNRs.

cond-mat.mtrl-sci↗

arXiv2006

Vibrational spectrum of the H5+ molecule using quantum Monte Carlo

In this article we present a caracterization of the vibrational spectrum of the H5+ molecule using the correlation function quantum Monte Carlo (CFQMC) method and a genetic algorithm study of the topology of the potential energy surface used in this work. The vibrational modes associated with the H3+ - H2 torsion and stretching posses very flat minima. As a consequence the fundamental frequencies corresponding to these modes are poorly described in the harmonic approximation. The vibrational frequencies obtained in this work are in good agreement with the available experimental data as well as other computational methods found in literature. In our genetic algorithm study of the potential energy surface using cartesian coordinates we have found some unexpected minima. A careful analysis shows that some of these minima are described by the same curviliniar coordinates in which the potential is described. However, they represent nonequivalent molecular geometries.

physics.chem-ph↗

arXiv2005

A genetic algorithm to build diatomic potentials

Several types of numerical and combinatorial optimization algorithms have been used as useful tools to minimize functional forms. Generally, when those forms are non-linear or occur in problems without a specific optimization method, stochastic methods based on search algorithms have shown good results due to its smaller susceptibility to be trapped in a local minimum. Besides that, they can be easily implemented to work with other techniques In this algorithms class, the genetic ones have received special attention because they are a robust optimization tool. An algorithm can be named genetic when it uses some kind of codification to transform a set of possible solutions of a given problem in a population that will evolve subject to operators inspired, or not, by mechanisms of natural selection. In other words, they work with a population of solutions to obtain better solutions in the next generation. To do this, they use only information of cost and prize. In this work, we propose a genetic algorithm optimization technique (GAOT) to fit diatomic potential energy curves.In order to show this method, we obtain the analytical functions of the H2+ and Li2 systems using the ab initio energy calculations as well as Rydberg trial function. These studies show that the quality of the GAOT fitting is comparable to the best optimization techniques recommended to fit diatomic systems. The introduction of this new technique is important because it arises as a new option to fit PES for reactive scattering dynamics.

physics.chem-ph↗

arXiv2005

Fitting potential energy surface of reactive system via genetic algorithm

In this work, we present a new fitting of the Na+HF potential energy surface (PES) utilizing a new optmization method based in Genetic Algorithm. Topology studies, such as isoenergetic contours and Minimum Energy Path(MEP), show that the quality of this new PES is comparable to the best PES of literature. These facts, suggests that this new approach can be utilized as new tool to fit PES of reactive systems.

physics.comp-ph↗