Abstract:For any given technology to be successful, its ability to compete with the other existing technologies is the key. Over the last five years, perovskite solar cells have entered the research spectrum with tremendous market prospects. These cells provide easy and low cost processability and are an efficient alternative to the existing solar cell technologies in the market. In this review article, we first go over the innovation and the scientific findings that have been going on in the field of perovskite solar cells (PSCs) and then present a short case study of perovskite solar cells based on their energy payback time. Our review aims to be comprehensive, considering the cost, the efficiency, and the stability of the PSCs. Later, we suggest areas for improvement in the field, and how the future might be shaped.
Runaway stars are ejected from their place of birth in the Galactic disk, with some young B-type runaways found several tens of kiloparsecs from the plane traveling at speeds beyond the escape velocity, which calls for violent ejection processes. Young open clusters are a likely place of origin, and ejection may be either through N-body interactions or in binary supernova explosions. The most energetic events may require dynamical interaction with massive black holes. The excellent quality of Gaia astrometry opens up the path to study the kinematics of young runaway stars to such a high precision that the place of origin in open stellar clusters can be identified uniquely even when the star is a few kiloparsecs away. We developed an efficient minimization method to calculate whether two or more objects may come from the same place, which we tested against samples of Orion runaways. Our fitting procedure was then used to calculate trajectories for known runaway stars, which have previously been studied from Hipparcos astrometry as well as known open clusters. For runaways in our sample we used Gaia data and updated radial velocities, and found that only half of the sample could be classified as runaways. The other half of the sample moves so slowly (<30 km s −1 ) that they have to be considered as walkaway stars. Most of the latter stars turned out to be binaries. We identified parent clusters for runaways based on their trajectories. We then used cluster age and flight time of the stars to investigate whether the ejection was likely due to a binary supernova or due to a dynamical ejection. In particular we show that the classical runaways AE Aurigae and µ Columbae might not have originated together, with µ Columbae having an earlier ejection from Collinder 69, a cluster near the ONC. The second sample investigated comprises a set of distant runaway B stars in the halo which have been studied carefully by quantitative spectral analyses. We are able to identify candidate parent clusters for at least four stars including the hyper-runaway candidate HIP 60350. The ejection events had to be very violent, ejecting stars at velocities as large as 150 to 400 km s −1 .
Context. Classification of sources is one of the most important tasks in astronomy. Sources detected in one wavelength band, for example using gamma rays, may have several possible associations in other wavebands, or there may be no plausible association candidates. Aims. In this work we aim to determine the probabilistic classification of unassociated sources in the third Fermi Large Area Telescope (LAT) point source catalog (3FGL) and the fourth Fermi LAT data release 2 point source catalog (4FGL-DR2) using two classes – pulsars and active galactic nuclei (AGNs) – or three classes – pulsars, AGNs, and “OTHER” sources. Methods. We use several machine learning (ML) methods to determine a probabilistic classification of Fermi-LAT sources. We evaluate the dependence of results on the meta-parameters of the ML methods, such as the maximal depth of the trees in tree-based classification methods and the number of neurons in neural networks. Results. We determine a probabilistic classification of both associated and unassociated sources in the 3FGL and 4FGL-DR2 catalogs. We cross-check the accuracy by comparing the predicted classes of unassociated sources in 3FGL with their associations in 4FGL-DR2 for cases where such associations exist. We find that in the two-class case it is important to correct for the presence of OTHER sources among the unassociated ones in order to realistically estimate the number of pulsars and AGNs. We find that the three-class classification, despite different types of sources in the OTHER class, has a similar performance as the two-class classification in terms of reliability diagrams and, at the same time, it does not require adjustment due to presence of the OTHER sources among the unassociated sources. We show an example of the use of the probabilistic catalogs for population studies, which include associated and unassociated sources.
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