Optical Performance of Ag-based Back Reflectors with different Spacers in Thin Film Si Solar Cells

Abstract We have compared different Ag-based back reflectors (BRs) applied to superstrate-type microcrystalline Si devices grown on Asahi U glass. In particular, substitution of the conventional ZnO:Al layer by MgF 2 , with lower refractive index and no free-carrier absorption, has been investigated. As electrical issues can mask the optical performance of the BR when evaluated by EQE measurements, a purely optical method that compares the intensity of Raman spectra generated with long wavelength excitation light has been applied. Based on this investigation, MgF 2 /Ag is potentially superior to ZnO:Al/Ag, even when MgF 2 is used in the form of ultrathin layer (few nm, likely island-like). Nevertheless, the novel dual-function n-SiO x /Ag BR outperforms all the other BRs

TCO Optimization in Si Heterojunction Solar Cells on p-type Wafers with n-SiOx Emitter☆

Abstract Silicon heterojunction solar cells have largely demonstrated their suitability to reach high efficiencies. We have here focused on p-type c-Si wafers as absorber, considering that they share more than 90% of the solar cell market. To overcome some of the issues encountered in the conventional (n)a-Si:H/(p)c-Si configuration, we have implemented a mixed phase n-type silicon oxide (n-SiOx) emitter in order to gain from the wider bandgap and lower activation energy of this material with respect to (n)a-Si:H. The workfunction of the transparent conductive oxide layer (WTCO) plays also a key role, as it may induce an unfavourable band bending at the interface with the emitter. We have here focused on AZO, a promising alternative to ITO. Different layers with varying WTCO were prepared, by changing relevant deposition parameters, and were tested into solar cells. The experimental results have been explained with the aid of numerical simulations. Finally, for the n-SiOx/(p)c-Si heterojunction with optimized WTCO a potential conversion efficiency well over 23% has been estimated

Modification of amorphous and microcrystalline silicon film properties after irradiation with MeV and GeV protons

It is well known that the degree of crystallinity has a prominent influence on the stability of Silicon under proton irradiation. Amorphous silicon films are much more stable than mono- or polycrystalline silicon substrates or microcrystalline silicon thin films. In particular it has been shown, that in a micromorph tandem solar cell irradiated with protons in the lower MeV energy range only the microcrystalline diode showed a pronounced decrease in photocurrent after irradiation1. The proton irradiation induced damage in thick crystalline silicon samples has a maximum at beam energies between 1MeV and 4MeV and decreases for further increasing proton energies. However, irradiating an amorphous silicon/crystalline silicon heterojunction solar cell with a relatively dose of 24GeV, we observed a very strong drop in conversion efficiency with only minor recovery after sample annealing. In literature it has been reported 2, that the degradation of amorphous silicon is negligible for proton energies above 100MeV. In order to clarify to which extent also the thin film top layer of the hetero solar cell is affected by the proton irradiation, we exposed a variety of thin film silicon samples either to a 1.7MeV beam with a dose of 5.1012 protons/cm2 or to a 24GeV beam with a dose of 5 .1013 protons/cm2. The investigated intrinsic, p-type and n-type amorphous and microcrystalline silicon films have been deposited by conventional plasma deposition under variation of the silane / hydrogen gas phase ratio. Raman measurements have been done in order to determine the order of crystallinity obtained under various deposition conditions. We observed even at 24GeV a clear modification in the electrical characteristics of the films. Temperature dependent measurements of the dark current revealed in particular for all doped samples a significant increase of the activation energy, that might be explained by a decrease of the dopant efficiency, while for intrinsic a-Si:H layers the increasing activation energy is due to deep defect creation

Procedure Based on External Quantum Efficiency for Reliable Characterization of Perovskite Solar Cells

Perovskite solar cells PSCs have the potential for widespread application, but challenges remain for a reliable characterization of their performance. Standardized protocols for measuring and reporting are still debated. Focusing on the short circuit current density J SC , current voltage characteristics J V and external quantum efficiency EQE are collected to estimate the parameter. Still, they often provide a mismatch above 1 amp; 8201;mA amp; 8201;cm amp; 8722;2, resulting in a possible 5 or higher error. Combining experimental data and optical simulations, it is demonstrated that the EQE can provide a reliable estimate of the J SC that could otherwise easily be overestimated by J V. With access to the internally transmitted light through simulations, an upper limit for EQE is defined depending on the front layers. Details on the origin of the spectral shape and contributions to the optical losses are obtained with further optical simulations, providing hints for cell optimization to achieve a photocurrent gain. The authors use solution processed n i p PSCs with triple cation mixed halide absorbers as demonstrators and ultimately come to the proposal of an upgrade of the present best practices in PSC efficiency measurements. Still, the approach and conclusions are general and apply to cells with all designs and chemical formulation

A BRAIN study to tackle imaging with artificial intelligence in the ALMA2030 era

Instrumentatio

SKA Science Data Challenge 2: analysis and results

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarise the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, `reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy -- which combined predictions from two independent machine learning techniques to yield a 20 percent improvement in overall performance -- underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets.Comment: Under review by MNRAS; 28 pages, 16 figure

Euclid preparation. Measuring detailed galaxy morphologies for Euclid with Machine Learning

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images.Comment: 27 pages, 26 figures, 5 tables, submitted to A&

Laser treatment of amorphous silicon junction field effect transistor channel

A systematic study of laser treatment of the channel of an amorphous silicon junction field effect transistor (JFET) is presented, using a Nd:YLF laser at 523 rim. and power ranging from 20 to 635 mJ/cm(2). A threshold energy equal to 150 mJ/cm2 is observed, Above this value higher power gives higher channel conductivity and reverse current of the gate-drain and gate-source junctions. Furthermore, the increase of conductivity corresponds to a lack of channel modulability due to an increase of defects and/or active dopant, which hampers the depletion of the channel. (C) 2002 Elsevier Science B.V. All rights reserved