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- Barnett, R., et al.
(författare)
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Euclid preparation V. Predicted yield of redshift 7 < z < 9 quasars from the wide survey
- 2019
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 631
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Tidskriftsartikel (refereegranskat)abstract
- We provide predictions of the yield of 7 < z < 9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths; we adopt steeper rates of decline of the quasar luminosity function (QLF; Phi) with redshift, Phi proportional to 10(k(z-6)), k = 0:72, and a further steeper rate of decline, k = 0:92; we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies); and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to J(AB) similar to 23. Quasars at z > 8 may be selected from Euclid OYJH photometry alone, but selection over the redshift interval 7 < z < 8 is greatly improved by the addition of z-band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = 0.92, Euclid should nevertheless find over 100 quasars with 7.0 < z < 7.5, and similar to 25 quasars beyond the current record of z = 7.5, including similar to 8 beyond z = 8.0. The first Euclid quasars at z > 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 < z < 8, M-1450 < 25, using 8m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at J(AB) similar to 23. The precision with which k can be determined over 7 < z < 8 depends on the value of k, but assuming k = 0.72 it can be measured to a 1 sigma uncertainty of 0.07.
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| 2. |
- Edoff, Marika, 1965-, et al.
(författare)
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Ultrathin CIGS Solar Cells with Passivated and Highly Reflective Back Contacts – : Results from the ARCIGS-M Consortium
- 2019
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Ingår i: Proceedings of 36th European Photovoltaic Solar Energy Conference and Exhibition. ; , s. 597-600
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this work, we report results from the EU-funded project ARCIGS-M. The project started in 2016 and aims to reduce the use of indium and gallium by enabling the use of very thin Cu(In,Ga)Se2 (CIGS) layers while retaining high efficiency and developing innovative low-cost steel substrates as alternatives to glass. In the project, reflective layers containing TCO´s and silver have successfully been used to enhance the reflective properties of the rear contact. In addition, passivation layers based on alumina (Al2O3) deposited by atomic layer deposition (ALD) have been found to yield good passivation of the rear contact. Since the alumina layers are dielectric, perforation of these layers is necessary to provide adequate contacting. The design of the perforation patterns has been investigated by a combination of modeling and experimental verification by electron beam lithography. In parallel a nano-imprint lithography (NIL) process is further developed for scale-up and application in prototype modules. Advanced optoelectrical characterization supported by modeling is used to fill in the missing gaps in optical and electrical properties, regarding CIGS, interfaces and back contact materials.
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| 4. |
- Perdikari, A., et al.
(författare)
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BATLAS: Deconvoluting Brown Adipose Tissue
- 2018
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 25:3
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Tidskriftsartikel (refereegranskat)abstract
- Recruitment and activation of thermogenic adipocytes have received increasing attention as a strategy to improve systemic metabolic control. The analysis of brown and brite adipocytes is complicated by the complexity of adipose tissue biopsies. Here, we provide an in-depth analysis of pure brown, brite, and white adipocyte transcriptomes. By combining mouse and human transcriptome data, we identify a gene signature that can classify brown and white adipocytes in mice and men. Using a machine-learning-based cell deconvolution approach, we develop an algorithm proficient in calculating the brown adipocyte content in complex human and mouse biopsies. Applying this algorithm, we can show in a human weight loss study that brown adipose tissue (BAT) content is associated with energy expenditure and the propensity to lose weight. This online available tool can be used for in-depth characterization of complex adipose tissue samples and may support the development of therapeutic strategies to increase energy expenditure in humans.
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