Quantum field theory approach to the optical conductivity of strained and deformed graphene

The computation of the optical conductivity of strained and deformed graphene is discussed within the framework of quantum field theory in curved spaces. The analytical solutions of the Dirac equation in an arbitrary static background geometry for one dimensional periodic deformations are computed, together with the corresponding Dirac propagator. Analytical expressions are given for the optical conductivity of strained and deformed graphene associated with both intra and interbrand transitions. The special case of small deformations is discussed and the result compared to the prediction of the tight-binding model.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Secure multiParty computation protocols

Dissertação de Mestrado em Engenharia Informática

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Effect of polymeric matrix on morphology and photoelectric properties of polymer-quantum dots nanocomposites

Recently, CdTe semiconductor quantum dots (QDs) have attracted great interest due to their unique properties [1]. Their dispersion into polymeric matrices would be very for several optoelectronics applications. Despite its importance, there has been relatively little work done on charge transport in the QD polymeric films [2], which is mainly affected by their structural and morphological properties. In the present work, polymer-quantum dot nanocomposites films based on optically transparent polymers in the visible spectral range and CdTe QDs with controlled particle size and emission wavelength, were prepared via solvent casting. Photoluminescent (PL) measurements indicate different emission intensity of the nanocomposites. A blue shift of the emission peak compared to that of QDs in solution occurred, which is attributed to the QDs environment changes. The morphological and structural properties of the CdTe nanocomposites were evaluated. Since better QDs dispersion was achieved, PMMA seemed to be the most promising matrix. Electrical properties measurements indicate an ohmic behavior.

Design of assemblies based on polymer-coated quantum dots and organic dye

During last years, photophysical properties of complexes of semiconductor quantum dots (QDs) with organic dyes have attracted increasing interest. The development of different assemblies based on QDs and organic dyes allows to increase the range of QDs applications, which include imaging, biological sensing and electronic devices.1 Some studies demonstrate energy transfer between QDs and organic dye in assemblies.2 However, for electronic devices purposes, a polymeric matrix is required to enhance QDs photostability. Thus, in order to attach the QDs to the polymer surface it is necessary to chemically modify the polymer to induce electronic charges and stabilize the QDs in the polymer. The present work aims to investigate the design of assemblies based on polymer-coated QDs and an integrated acceptor organic dye. Polymethylmethacrylate (PMMA) and polycarbonate (PC) were used as polymeric matrices, and nile red as acceptor. Additionally, a PMMA matrix modified with 2-mercaptoethylamine is used to improve the attachment between both the donor (QDs) and the acceptor (nile red), as well as to induce a covalent bond between the modified PMMA and the QDs. An enhancement of the energy transfer efficiency by using the modified PMMA is expected and the resulting assembly can be applied for energy harvesting.

Strain induced edge magnetism at zigzag edge of a graphene quantum dot

We study the temperature dependent magnetic susceptibility of a strained graphene quantum dot by using the determinant quantum Monte Carlo method. Within the Hubbard model on a honeycomb lattice, our unbiased numerical results show that a relative small interaction $U$ may lead to a edge ferromagnetic like behavior in the strained graphene quantum dot, and a possible room temperature transition is suggested. Around half filling, the ferromagnetic fluctuations at the zigzag edge is strengthened both markedly by the on-site Coulomb interaction and the strain, especially in low temperature region. The resultant strongly enhanced ferromagnetic like behavior may be important for the development of many applications.