XIPE: the X-ray Imaging Polarimetry Explorer

X-ray polarimetry, sometimes alone, and sometimes coupled to spectral and temporal variability measurements and to imaging, allows a wealth of physical phenomena in astrophysics to be studied. X-ray polarimetry investigates the acceleration process, for example, including those typical of magnetic reconnection in solar flares, but also emission in the strong magnetic fields of neutron stars and white dwarfs. It detects scattering in asymmetric structures such as accretion disks and columns, and in the so-called molecular torus and ionization cones. In addition, it allows fundamental physics in regimes of gravity and of magnetic field intensity not accessible to experiments on the Earth to be probed. Finally, models that describe fundamental interactions (e.g. quantum gravity and the extension of the Standard Model) can be tested. We describe in this paper the X-ray Imaging Polarimetry Explorer (XIPE), proposed in June 2012 to the first ESA call for a small mission with a launch in 2017 but not selected. XIPE is composed of two out of the three existing JET-X telescopes with two Gas Pixel Detectors (GPD) filled with a He-DME mixture at their focus and two additional GPDs filled with pressurized Ar-DME facing the sun. The Minimum Detectable Polarization is 14 % at 1 mCrab in 10E5 s (2-10 keV) and 0.6 % for an X10 class flare. The Half Energy Width, measured at PANTER X-ray test facility (MPE, Germany) with JET-X optics is 24 arcsec. XIPE takes advantage of a low-earth equatorial orbit with Malindi as down-link station and of a Mission Operation Center (MOC) at INPE (Brazil).Comment: 49 pages, 14 figures, 6 tables. Paper published in Experimental Astronomy http://link.springer.com/journal/1068

Optoelectronic simulations for novel light management concepts in Cu(In,Ga)Se2 solar cells

One of the trends making its way through the Photovoltaics (PV) industry, is the search for new application possibilities. Cu(In,Ga)Se2 (CIGS) thin film solar cells stand out due to their class leading power conversion efficiency of 23.35 %, flexibility, and low cost. The use of sub-μm ultrathin CIGS solar cells has been gaining prevalence, due to the reduction in material consumption and the manufacturing time. Precise CIGS finite-difference time-domain (FDTD) and 3D-drift diffusion baseline models were developed for the Lumerical suite and a 1D electrical model for SCAPS, allowing for an accurate description of the optoelectronic behavior and response of thin and ultrathin CIGS solar cells. As a result, it was possible to obtain accurate descriptions of the optoelectronic behavior of thin and ultrathin solar cells, and to perform an optical study and optimization of novel light management approaches, such as, random texturization, photonic nanostructures, plasmonic nanoparticles, among others. The developed light management architectures enabled to push the optical performance of an ultrathin solar cell and even surpass the performance of a thin film solar cell, enabling a short-circuit current enhancement of 6.15 mA/cm2 over an ultrathin reference device, without any light management integrated.publishe

Encapsulation of Nanostructures in a Dielectric Matrix Providing Optical Enhancement in Ultrathin Solar Cells

The incorporation of nanostructures in optoelectronic devices for enhancing their optical performance is widely studied. However, several problems related to the processing complexity and the low performance of the nanostructures have hindered such actions in real-life devices. Herein, a novel way of introducing gold nanoparticles in a solar cell structure is proposed in which the nanostructures are encapsulated with a dielectric layer, shielding them from high temperatures and harsh growth processing conditions of the remaining device. Through optical simulations, an enhancement of the effective optical path length of approximately four times the nominal thickness of the absorber layer is verified with the new architecture. Furthermore, the proposed concept in a Cu(In,Ga)Se2 solar cell device is demonstrated, where the short-circuit current density is increased by 17.4%. The novel structure presented in this work is achieved by combining a bottom-up chemical approach of depositing the nanostructures with a top-down photolithographic process, which allows for an electrical contact.This work was funded in part by the Fundação para a Ciência e a Tecnologia (FCT) under Grants IF/00133/2015, PD/BD/142780/2018 and SFRH/BD/ 146776/2019. The authors also want to acknowledge the European Union’s Horizon 2020 Research and Innovation Programme through the ARCIGS-M project under Grant 720887, the Special Research Fund (BOF) of Hasselt University, the FCT through the project NovaCell (PTDC/CTM-CTM/28075/ 2017), and InovSolarCells (PTDC/FISMAC/29696/2017) co-funded by FCT and the ERDF through COMPETE2020. The authors also want to acknowledge Sandra Maya for the production of images used in this work.info:eu-repo/semantics/publishedVersio

A discrete-time-evolution model to forecast progress of Covid-19 outbreak

AbstractBased on well-known infection models, we constructed a new model to forecast the propagation of the Covid-19 pandemic which yields a discrete-time evolution with one day interval. The proposed model can be easily implemented with daily updated data sets of the pandemic publicly available by many sources. It has only two adjustable parameters and is able to predict the evolution of the total number of infected people in a country for the next 14 days, if parameters do not change during this time. The model incorporates the main aspects of the disease such as the the fact that there are asymptomatic and symptomatic phases (both capable of propagating the virus), and that these phases take almost two weeks before the infected person status evolves to the next (asymptomatic becomes symptomatic or symptomatic becomes either recovered or dead). One advantage of the model is that it gives directly the number of total infected people in each day (in thousands, tens of thousands or hundred of thousands). The model was tested with data from Brazil, UK and South Korea, it predicts quite well the evolution of the disease and therefore may be a useful tool to estimate the propagation of the disease.</jats:p

A discrete-time-evolution model to forecast progress of Covid-19 outbreak.

Here we present a discrete-time-evolution model with one day interval to forecast the propagation of Covid-19. The proposed model can be easily implemented with daily updated data sets of the pandemic publicly available by distinct online sources. It has only two adjustable parameters and it predicts the evolution of the total number of infected people in a country for the next 14 days if parameters do not change during the analyzed period. The model incorporates the main aspects of the disease such as the fact that there are asymptomatic and symptomatic phases (both capable of propagating the virus), and that these phases take almost two weeks before the infected person status evolves to the next (asymptomatic becomes symptomatic or symptomatic becomes either recovered or dead). A striking advantage of the model for its implementation by the health sector is that it gives directly the number of total infected people in each day (in thousands, tens of thousands or hundred of thousands). Here, the model is tested with data from Brazil, UK and South Korea, presenting low error rates on the prediction of the evolution of the disease in all analyzed countries. We hope this model may be a useful tool to estimate the propagation of the disease