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Understanding and exploiting interfacial interactions between phosphonic acid functional groups and co-evaporated perovskites

Abstract (Expand)

Interfacial engineering has fueled recent development of p-i-n perovskite solar cells (PSCs), with self-assembled monolayer-based hole-transport layers (SAM-HTLs) enabling almost lossless contacts for … solution-processed PSCs, resulting in the highest achieved power conversion efficiency (PCE) to date. Substrate interfaces are particularly crucial for the growth and quality of co-evaporated PSCs. However, adoption of SAM-HTLs for co-evaporated perovskite absorbers is complicated by the underexplored interaction of such perovskites with phosphonic acid functional groups. In this work, we highlight how exposed phosphonic acid functional groups impact the initial phase and final bulk crystal structures of co-evaporated perovskites and their resultant PCE. The explored surface interaction is mediated by hydrogen bonding with interfacial iodine, leading to increased formamidinium iodide adsorption, persistent changes in perovskite structure, and stabilization of bulk α-FAPbI3, hypothesized as being due to kinetic trapping. Our results highlight the potential of exploiting substrates to increase control of co-evaporated perovskite growth.

Authors: Thomas Feeney, Julian Petry, Abderrezak Torche, Dirk Hauschild, Benjamin Hacene, Constantin Wansorra, Alexander Diercks, Michelle Ernst, Lothar Weinhardt, Clemens Heske, Ganna Gryn’ova, Ulrich W. Paetzold, Paul Fassl

Date Published: 1st Mar 2024

Publication Type: Journal

Towards a self-consistent model of the convective core boundary in upper main sequence stars

Abstract (Expand)

There is strong observational evidence that the convective cores of intermediate-mass and massive main sequence stars are substantially larger than those predicted by standard stellar-evolution models. … However, it is unclear what physical processes cause this phenomenon or how to predict the extent and stratification of stellar convective boundary layers. Convective penetration is a thermal-timescale process that is likely to be particularly relevant during the slow evolution on the main sequence. We use our low-Mach-number SEVEN-LEAGUE HYDRO code to study this process in 2.5D and 3D geometries. Starting with a chemically homogeneous model of a 15  M⊙ zero-age main sequence star, we construct a series of simulations with the luminosity increased and opacity decreased by the same factor, ranging from 10^3 to 10^6. After reaching thermal equilibrium, all of our models show a clear penetration layer; its thickness becomes statistically constant in time and it is shown to converge upon grid refinement. The penetration layer becomes nearly adiabatic with a steep transition to a radiative stratification in simulations at the lower end of our luminosity range. This structure corresponds to the adiabatic ‘step overshoot’ model often employed in stellar-evolution calculations. The simulations with the highest and lowest luminosity differ by less than a factor of two in the penetration distance. The high computational cost of 3D simulations makes our current 3D data set rather sparse. Depending on how we extrapolate the 3D data to the actual luminosity of the initial stellar model, we obtain penetration distances ranging from 0.09 to 0.44 pressure scale heights, which is broadly compatible with observations.

Authors: R. Andrassy, G. Leidi, J. Higl, P. V. F. Edelmann, F. R. N. Schneider, F. K. Röpke

Date Published: 1st Mar 2024

Publication Type: Journal

Deep learning for postprocessing global probabilistic forecasts on subseasonal time scales

Abstract

Not specified

Authors: Nina Horat, Sebastian Lerch

Date Published: 1st Mar 2024

Publication Type: Journal

Non-crossing quantile regression neural network as a calibration tool for ensemble weather forecasts

Abstract

Not specified

Authors: Mengmeng Song, Dazhi Yang, Sebastian Lerch, Xiang’ao Xia, Gokhan Mert Yagli, Jamie M. Bright, Yanbo Shen, Bai Liu, Xingli Liu, Martin János Mayer

Date Published: 1st Mar 2024

Publication Type: Journal

Effect of nuclear reactions rates and core boundary mixing on the seismology of red clump stars

Abstract (Expand)

Context: Modeling of the stars in the red clump (RC), that is, core helium-burning stars that have gone through a He flash, is challenging because of the uncertainties associated with the physical … processes in their core and during the helium flash. By probing the internal stellar structure, asteroseismology allows us to constrain the core properties of RC stars and eventually, to improve our understanding of this evolutionary phase. Aims: We aim to quantify the impact on the seismic properties of the RC stars of the two main core modeling uncertainties: core boundary mixing, and helium-burning nuclear reaction rates. Methods: Using the MESA stellar evolution code, we computed models with different core boundary mixing as well as different 3α and 12C(α, γ)16O nuclear reaction rates. We investigated the impact of these parameters on the period spacing ΔΠ, which is a probe of the region around the core. Results: We find that different core boundary mixing schemes yield significantly different period spacings, with differences of 30 s between the maximum ΔΠ value computed with semiconvection and maximal overshoot. We show that an increased rate of 12C(α, γ)16O lengthens the core helium-burning phase, which extends the range of ΔΠ covered by the models during their evolution. This results in a difference of 10 s between the models computed with a nominal rate and a rate multiplied by 2, which exceeds the observational uncertainties. The effect of changing the 3α reaction rate is comparatively small. Conclusions: The core boundary mixing is the main source of uncertainty in the seismic modeling of RC stars. Moreover, the effect of the 12C(α, γ)16O is non-negligible, even though it is difficult to distinguish from the effect of the mixing. This degeneracy could be seen more frequently in the future in the new seismic data from the PLATO mission and through theoretical constraints from numerical simulations.

Authors: Anthony Noll, Sarbani Basu, Saskia Hekker

Date Published: 1st Mar 2024

Publication Type: Journal

Towards explainable evaluation metrics for machine translation

Abstract (Expand)

Unlike classical lexical overlap metrics such as BLEU, most current evaluation metrics for machine translation (for example, COMET or BERTScore) are based on black-box large language models. They often … achieve strong correlations with human judgments, but recent research indicates that the lower-quality classical metrics remain dominant, one of the potential reasons being that their decision processes are more transparent. To foster more widespread acceptance of novel high-quality metrics, explainability thus becomes crucial. In this concept paper, we identify key properties as well as key goals of explainable machine translation metrics and provide a comprehensive synthesis of recent techniques, relating them to our established goals and properties. In this context, we also discuss the latest state-of-the-art approaches to explainable metrics based on generative models such as ChatGPT and GPT4. Finally, we contribute a vision of next-generation approaches, including natural language explanations. We hope that our work can help catalyze and guide future research on explainable evaluation metrics and, mediately, also contribute to better and more transparent machine translation systems.

Authors: Christoph Leiter, Piyawat Lertvittayakumjorn, Marina Fomicheva, Wei Zhao, Yang Gao, Steffen Eger

Date Published: 1st Mar 2024

Publication Type: Journal

1100 days in the life of the supernova 2018ibb. The best pair-instability supernova candidate, to date

Abstract

Not specified

Authors: Steve Schulze, Claes Fransson, Alexandra Kozyreva, Ting-Wan Chen, Ofer Yaron, Anders Jerkstrand, Avishay Gal-Yam, Jesper Sollerman, Lin Yan, Tuomas Kangas, Giorgos Leloudas, Conor M. B. Omand, Stephen J. Smartt, Yi Yang, Matt Nicholl, Nikhil Sarin, Yuhan Yao, Thomas G. Brink, Amir Sharon, Andrea Rossi, Ping Chen, Zhihao Chen, Aleksandar Cikota, Kishalay De, Andrew J. Drake, Alexei V. Filippenko, Christoffer Fremling, Laurane Fréour, Johan P. U. Fynbo, Anna Y. Q. Ho, Cosimo Inserra, Ido Irani, Hanindyo Kuncarayakti, Ragnhild Lunnan, Paolo Mazzali, Eran O. Ofek, Eliana Palazzi, Daniel A. Perley, Miika Pursiainen, Barry Rothberg, Luke J. Shingles, Ken Smith, Kirsty Taggart, Leonardo Tartaglia, WeiKang Zheng, Joseph P. Anderson, Letizia Cassara, Eric Christensen, S. George Djorgovski, Lluı́s Galbany, Anamaria Gkini, Matthew J. Graham, Mariusz Gromadzki, Steven L. Groom, Daichi Hiramatsu, D. Andrew Howell, Mansi M. Kasliwal, Curtis McCully, Tomás E. Müller-Bravo, Simona Paiano, Emmanouela Paraskeva, Priscila J. Pessi, David Polishook, Arne Rau, Mickael Rigault, Ben Rusholme

Date Published: 1st Mar 2024

Publication Type: Journal

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