Antireflective nanotextures for monolithic perovskite silicon tandem solar cells

Recently, we studied the effect of hexagonal sinusoidal textures on the reflective properties of perovskite silicon tandem solar cells using the finite element method FEM . We saw that such nanotextures, applied to the perovskite top cell, can strongly increase the current density utilization from 91 for the optimized planar reference to 98 for the best nanotextured device period 500 nm and peak to valley height 500 nm , where 100 refers to the Tiedje Yablonovitch limit. [D. Chen et al., J. Photonics Energy 8, 022601, 2018 , doi 10.1117 1.JPE.8.022601] In this manuscript we elaborate on some numerical details of that work we validate an assumption based on the Tiedje Yablonovitch limit, we present a convergence study for simulations with the finite element method, and we compare different configurations for sinusoidal nanotexture

Control of fine-structure splitting and excitonic binding energies in selected individual InAs/GaAs quantum dots

A systematic study of the impact of annealing on the electronic properties of single InAs/GaAs quantum dots (QDs) is presented. Single QD cathodoluminescence spectra are recorded to trace the evolution of one and the same QD over several steps of annealing. A substantial reduction of the excitonic fine-structure splitting upon annealing is observed. In addition, the binding energies of different excitonic complexes change dramatically. The results are compared to model calculations within eight-band k.p theory and the configuration interaction method, suggesting a change of electron and hole wave function shape and relative position.Comment: 4 pages, 4 figure

Increased fluorescence of PbS quantum dots in photonic crystals by excitation enhancement

We report on the enhanced fluorescence of lead sulfide quantum dots interacting with leaky modes of slab type silicon photonic crystals. The photonic crystal slabs were fabricated, supporting leaky modes in the near infrared wavelength range. Lead sulfite quantum dots which are resonant in the same spectral range were prepared in a thin layer above the slab. We selectively excited the leaky modes by tuning the wavelength and angle of incidence of the laser source and measured distinct resonances of enhanced fluorescence. By an appropriate experiment design, we ruled out directional light extraction effects and determined the impact of enhanced excitation. Three dimensional numerical simulations consistently explain the experimental findings by strong near field enhancements in the vicinity of the photonic crystal surface. Our study provides a basis for systematic tailoring of photonic crystals used in biological applications such as biosensing and single molecule detection, as well as quantum dot solar cells and spectral conversion application

Converting sporting capacity to entrepreneurial capacity: A process perspective

Managing a personal sporting career and conducting an entrepreneurial initiative are two vitally connected processes. Most athletes require a second career and many engage in entrepreneurship. Research on the similarities and differences of the sports career management process and entrepreneurial process with a special emphasis on the necessary capacities will have a ready audience among practitioners. This study begins the task of closing a surprising gap. In entrepreneurship literature, there is (1) growing research on entrepreneurial process and entrepreneurial capacity as the key driver; (2) strong work in generic, descriptive and explanatory modelling of process as a whole and capacity as a sub-process; and (3) the presence of a generic model of entrepreneurial process based of what distinguishes entrepreneurial capacity from other human capacities. In sports management literature, these research strands are virtually absent. The study indicates how the deficiency might be remedied

Weakness evaluation on in-vehicle violence detection: an assessment of X3D, C2D and I3D against FGSM and PGD

When constructing a deep learning model for recognizing violence inside a vehicle, it is crucial to consider several aspects. One aspect is the computational limitations, and the other is the deep learning model architecture chosen. Nevertheless, to choose the best deep learning model, it is necessary to test and evaluate the model against adversarial attacks. This paper presented three different architecture models for violence recognition inside a vehicle. These model architectures were evaluated based on adversarial attacks and interpretability methods. An analysis of the model’s convergence was conducted, followed by adversarial robustness for each model and a sanity-check based on interpretability analysis. It compared a standard evaluation for training and testing data samples with the adversarial attacks techniques. These two levels of analysis are essential to verify model weakness and sensibility regarding the complete video and in a frame-by-frame way.This work is funded by “FCT—Fundação para a Ciência e Tecnologia” within the R&D Units Project Scope: UIDB/00319/2020. The employment contract of Dalila Durães is supported by CCDR-N Project: NORTE-01-0145-FEDER-00008