Increased cell efficiency in InGaAs thin film solar cells with dielectric and metal back reflectors

Compound single junction and multijunction solar cells enable very high photovoltaic efficiencies by virtue of employing different band gap materials in seriesconnected tandem cells to access the full solar spectrum. Researchers focused on improving the electrical properties of solar cells by optimizing the material growth conditions, however relatively little work to date has been devoted to light trapping and enhanced absorption in III-V compound solar cells using back reflectors. We studied absorption enhancement in InGaAs and InGaAsP thin film solar cells by means of numerical modeling. Flat dielectric and metal back reflectors that might be introduced into the solar cell via wafer-bonding, epitaxial lift-off or deposition techniques have been shown to increase the short circuit current and the photovoltaic efficiency of solar cells

Symmetry breaking and strong coupling in planar optical metamaterials

We demonstrate narrow transmission resonances at near-infrared wavelengths utilizing coupled asymmetric split-ring resonators (SRRs). By breaking the symmetry of the coupled SRR system, one can excite dark (subradiant) resonant modes that are not readily accessible to symmetric SRR structures. We also show that the quality factor of metamaterial resonant elements can be controlled by tailoring the degree of asymmetry. Changing the distance between asymmetric resonators changes the coupling strength and results in resonant frequency tuning due to resonance hybridization

Compliant Metamaterials for Resonantly Enhanced Infrared Absorption Spectroscopy and Refractive Index Sensing

Metamaterials can be designed to operate at frequencies from the visible to the mid-IR, making these structures useful for both refractive index sensing and surface-enhanced infrared absorption spectroscopy. Here we investigate how the mechanical deformation of compliant metamaterials can be used to create new types of tunable sensing surfaces. For split ring resonator based metamaterials on polydimethylsiloxane we demonstrate refractive index sensing with figures of merit of up to 10.1. Given the tunability of the resonance of these structures through the infrared after fabrication, they are well suited for detection of the absorption signal of many typical vibrational modes. The results highlight the promise of postfabrication tunable sensors and the potential for integration

Highly Strained Compliant Optical Metamaterials with Large Frequency Tunability

Metamaterial designs are typically limited to operation over a narrow bandwidth dictated by the resonant line width. Here we report a compliant metamaterial with tunability of Δλ ~ 400 nm, greater than the resonant line width at optical frequencies, using high-strain mechanical deformation of an elastomeric substrate to controllably modify the distance between the resonant elements. Using this compliant platform, we demonstrate dynamic surface-enhanced infrared absorption by tuning the metamaterial resonant frequency through a CH stretch vibrational mode, enhancing the reflection signal by a factor of 180. Manipulation of resonator components is also used to tune and modulate the Fano resonance of a coupled system

An Open Inflationary Model for Dimensional Reduction and its Effects on the Observable Parameters of the Universe

Assuming that higher dimensions existed in the early stages of the universe where the evolution was inflationary, we construct an open, singularity-free, spatially homogeneous and isotropic cosmological model to study the effects of dimensional reduction that may have taken place during the early stages of the universe. We consider dimensional reduction to take place in a stepwise manner and interpret each step as a phase transition. By imposing suitable boundary conditions we trace their effects on the present day parameters of the universe.Comment: 5 pages, accepted for publication in Int. J. of Mod. Phys.

Agent-Based Fault Tolerant Distributed Event System

In the last years, event-based communication style has been extensively studied and is considered a promising approach to develop large scale distributed systems. The historical development of event based systems has followed a line which has evolved from channel-based systems, to subject-based systems, next content-based systems and finally type-based systems which use objects as event messages. According to this historical development the next step should be usage of agents in event systems. In this paper, we propose a new model for Agent Based Distributed Event Systems, called ABDES, which combines the advantages of event-based communication and intelligent mobile agents into a flexible, extensible and fault tolerant distributed execution environment

SAR image classification with non-stationary multinomial logistic mixture of amplitude and texture densities

We combine both amplitude and texture statistics of the Synthetic Aperture Radar (SAR) images using Products of Experts (PoE) approach for classification purpose. We use Nakagami density to model the class amplitudes. To model the textures of the classes, we exploit a non-Gaussian Markov Random Field (MRF) texture model with t-distributed regression error. Non-stationary Multinomial Logistic (MnL) latent class label model is used as a mixture density to obtain spatially smooth class segments. We perform the Classification Expectation-Maximization (CEM) algorithm to estimate the class parameters and classify the pixels. We obtained some classification results of water, land and urban areas in both supervised and semi-supervised cases on TerraSAR-X data

Progressive Neural Networks

Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding catastrophic forgetting--remains a key obstacle to achieving human-level intelligence. The progressive networks approach represents a step forward in this direction: they are immune to forgetting and can leverage prior knowledge via lateral connections to previously learned features. We evaluate this architecture extensively on a wide variety of reinforcement learning tasks (Atari and 3D maze games), and show that it outperforms common baselines based on pretraining and finetuning. Using a novel sensitivity measure, we demonstrate that transfer occurs at both low-level sensory and high-level control layers of the learned policy

Active plasmonic devices and optical metamaterials

We studied active near-infrared metamaterials based on phase transition of vanadium oxide thin films, asymmetrically coupled split-ring resonators for narrowing resonance line-widths , field effect modulation of plasmon propagation and 3D single layer, plasmonic negative-index metamaterials