Interaction Effects on the Magneto-optical Response of Magnetoplasmonic Dimers

The effect that dipole-dipole interactions have on the magneto-optical (MO) properties of magnetoplasmonic dimers is theoretically studied. The specific plasmonic versus magnetoplasmonic nature of the dimer's metallic components and their specific location within the dimer plays a crucial role on the determination of these properties. We find that it is possible to generate an induced MO activity in a purely plasmonic component, even larger than that of the MO one, therefore dominating the overall MO spectral dependence of the system. Adequate stacking of these components may allow obtaining, for specific spectral regions, larger MO activities in systems with reduced amount of MO metal and therefore with lower optical losses. Theoretical results are contrasted and confirmed with experiments for selected structures

Electron Scattering in 2D Semiconductors: Contrasting Dirac and Schr\"odinger Behavior

Electronic transport through a material depends on the response to local perturbations induced by defects or impurities in the material. The scattering processes can be described in terms of phase shifts and corresponding cross sections. The multiorbital nature of the spinor states in transition metal dichalcogenides would naturally suggest the consideration of a massive Dirac equation to describe the problem, while the parabolic dispersion of its conduction and valence bands would invite a simpler Schr\"odinger equation description. Here, we contrast the scattering of massive Dirac particles and Schr\"odinger electrons, in order to assess different asymptotic regimes (low and high Fermi energy) for each one of the electronic models and describe their regime of validity or transition. At low energies, where the dispersion is approximately parabolic, the scattering processes are dominated by low angular momentum channels, which results in nearly isotropic scattering amplitudes. On the other hand, the differential cross section at high Fermi energies exhibits clear signatures of the linear band dispersion, as the partial phase shifts approach a non-zero value. We analyze the electronic dynamics by presenting differential cross sections for both attractive and repulsive scattering centers. The dissimilar behavior between Dirac and Schr\"odinger carriers points to the limits and conditions over which different descriptions are required for the reliable treatment of scattering processes in these materials

Electron Scattering in 2D Semiconductors: Contrasting Dirac and Schr\"odinger Behavior

Electronic transport through a material depends on the response to local perturbations induced by defects or impurities in the material. The scattering processes can be described in terms of phase shifts and corresponding cross sections. The multiorbital nature of the spinor states in transition metal dichalcogenides would naturally suggest the consideration of a massive Dirac equation to describe the problem, while the parabolic dispersion of its conduction and valence bands would invite a simpler Schr\"odinger equation description. Here, we contrast the scattering of massive Dirac particles and Schr\"odinger electrons, in order to assess different asymptotic regimes (low and high Fermi energy) for each one of the electronic models and describe their regime of validity or transition. At low energies, where the dispersion is approximately parabolic, the scattering processes are dominated by low angular momentum channels, which results in nearly isotropic scattering amplitudes. On the other hand, the differential cross section at high Fermi energies exhibits clear signatures of the linear band dispersion, as the partial phase shifts approach a non-zero value. We analyze the electronic dynamics by presenting differential cross sections for both attractive and repulsive scattering centers. The dissimilar behavior between Dirac and Schr\"odinger carriers points to the limits and conditions over which different descriptions are required for the reliable treatment of scattering processes in these materials

Life Cycle Assessment of a Small Hydropower Plant in the Brazilian Amazon

Brazil as well as the rest of the world, faces a major challenge related to the electricity sector, to meet the growing demand with energy production from renewable sources. Many hydroelectric plants are being implemented, especially in the northern region of Brazil, but its environmental impacts are yet unknown. Energy produced by hydropower plants has been considered totally renewable and clean, but more recent studies describe analysis pointing to the existence of emissions by hydroelectric plants, especially if a lifecycle approach is considered. Thus, the objective of this study is the investigation of environmental impacts of the construction, operation and decommissioning of a hydroelectric power station based on life cycle assessment. The main focus is the Curuá-Una hydropower plant that is located in the Amazon forest in northern Brazil, in Santarém municipality (Pará state)

Direct Hydroxylation of Phenol to Dihydroxybenzenes by H2O2 and Fe-based Metal-Organic Framework Catalyst at Room Temperature

A semi-crystalline iron-based metal-organic framework (MOF), in particular Fe-BTC, that contained 20 wt.% Fe, was sustainably synthesized at room temperature and extensively characterized. Fe-BTC nanopowders could be used as an efficient heterogeneous catalyst for the synthesis of dihydroxybenzenes (DHBZ), from phenol with hydrogen peroxide (H2O2), as oxidant under organic solvent-free conditions. The influence of the reaction temperature, H2O2 concentration and catalyst dose were studied in the hydroxylation performance of phenol and MOF stability. Fe-BTC was active and stable (with negligible Fe leaching) at room conditions. By using intermittent dosing of H2O2, the catalytic performance resulted in a high DHBZ selectivity (65%) and yield (35%), higher than those obtained for other Fe-based MOFs that typically require reaction temperatures above 70◦C. The long-term experiments in a fixed-bed flow reactor demonstrated good Fe-BTC durability at the above conditionsThe authors thank the financial support by Consejo Nacional de Ciencia y Tecnología (CONACYT) for the grant number 764635 and the project 256296; and to TNM for the supporting project 5627.19.P. Also, to the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN) and FEDER program (EU) through the projects: CTM2016-76454-R (MICINN) and RTI2018-095052-B-I00 ((MCIU/AEI/FEDER, UE

Rapid detection of cardiac pathologies by neural networks using ECG signals (1D) and sECG images (3D)

Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health services or the time the public health system takes to refer the patient to a cardiologist. In addition, the variety of cardiac pathologies (more than 20 types) is a problem in diagnosing the disease. On the other hand, surface electrocardiography (sECG) is a little-explored technique for this diagnosis. sECGs are three-dimensional images (two dimensions in space and one in time). In this way, the signals were taken in one-dimensional format and analyzed using neural networks. Following the transformation of the one-dimensional signals to three-dimensional signals, they were analyzed in the same sense. For this research, two models based on LSTM and ResNet34 neural networks were developed, which showed high accuracy, 98.71% and 93.64%, respectively. This study aims to propose the basis for developing Decision Support Software (DSS) based on machine learning models. © 2022 by the authors. Licensee MDPI, Basel, Switzerland