Luminescent solar concentrators: Semiconductor solution

There are increasing public and private pressures for the adoption of renewable energy technologies, of which solar is anticipated to be a prime player1. As it becomes increasingly desirable to generate energy nearer the point of demand (such as within a city centre) it is also more apparent that additional features beyond electrical performance play an important role in solar power: aesthetics2 and perceived safety3 of the devices come to the fore. Because of their adaptability and attractive appearance, there is a burgeoning interest in luminescent solar concentrator (LSC) devices for use in urban areas4. LSCs are large plastic plates filled with luminescent materials that essentially redirect solar energy to small edge-attached photovoltaic (PV) cells to generate electricity (Fig. 1). The first steps have been made in integrating LSCs into public spaces5, 6. But while the silicon-based PV panel industry has experienced tremendous growth, there is still no commercial manufacturer of LSCs

Silicon quantum dots: surface matters

Silicon quantum dots (SiQDs) hold great promise for many future technologies. Silicon is already at the core of photovoltaics and microelectronics, and SiQDs are capable of efficient light emission and amplification. This is crucial for the development of the next technological frontiers—silicon photonics and optoelectronics. Unlike any other quantum dots (QDs), SiQDs are made of non-toxic and abundant material, offering one of the spectrally broadest emission tunabilities accessible with semiconductor QDs and allowing for tailored radiative rates over many orders of magnitude. This extraordinary flexibility of optical properties is achieved via a combination of the spatial confinement of carriers and the strong influence of surface chemistry. The complex physics of this material, which is still being unraveled, leads to new effects, opening up new opportunities for applications. In this review we summarize the latest progress in this fascinating research field, with special attention given to surface-induced effects, such as the emergence of direct bandgap transitions, and collective effects in densely packed QDs, such as space separated quantum cutting

Cuckoo Search Based Backcalculation Algorithm for Estimating Layer Properties of Full-Depth Flexible Pavements

This study introduces a backcalculation algorithm to estimate the material properties of the full-depth asphalt pavements. The proposed algorithm, namely CS-ANN, uses an Artificial Neural Network (ANN) based forward response engine, which is developed from the solutions of nonlinear finite element analysis to calculate the deflections mathematically. In the backward phase of the method, Cuckoo Search (CS), is utilized to search for the layer moduli values. The performance of the proposed method is investigated by analyzing the synthetically calculated deflections by a finite element based software and deflection data obtained from the field. In addition, to evaluate the searching capability of CS, optimization algorithms widely used in pavement backcalculation; Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA), are employed for comparison purposes. Obtained results indicate that the proposed backcalculation approach is able to determine stiffness-related layer properties in an accurate and rapid manner. In addition, CS presents a promising performance in reaching the optimum solutions that are better than GA, PSO, and GSA