Observational Constraints on First-Star Nucleosynthesis. I. Evidence for Multiple Progenitors of CEMP-no Stars

We investigate anew the distribution of absolute carbon abundance, $A$(C) $= \log\,\epsilon$(C), for carbon-enhanced metal-poor (CEMP) stars in the halo of the Milky Way, based on high-resolution spectroscopic data for a total sample of 305 CEMP stars. The sample includes 147 CEMP-$s$ (and CEMP-r/s) stars, 127 CEMP-no stars, and 31 CEMP stars that are unclassified, based on the currently employed [Ba/Fe] criterion. We confirm previous claims that the distribution of $A$(C) for CEMP stars is (at least) bimodal, with newly determined peaks centered on $A$(C)$=7.96$ (the high-C region) and $A$(C)$=6.28$ (the low-C region). A very high fraction of CEMP-$s$ (and CEMP-r/s) stars belong to the high-C region, while the great majority of CEMP-no stars reside in the low-C region. However, there exists complexity in the morphology of the $A$(C)-[Fe/H] space for the CEMP-no stars, a first indication that more than one class of first-generation stellar progenitors may be required to account for their observed abundances. The two groups of CEMP-no stars we identify exhibit clearly different locations in the $A$(Na)-$A$(C) and $A$(Mg)-$A$(C) spaces, also suggesting multiple progenitors. The clear distinction in $A$(C) between the CEMP-$s$ (and CEMP-$r/s$) stars and the CEMP-no stars appears to be $as\ successful$, and$likely\ more\ astrophysically\ fundamental$, for the separation of these sub-classes as the previously recommended criterion based on [Ba/Fe] (and [Ba/Eu]) abundance ratios. This result opens the window for its application to present and future large-scale low- and medium-resolution spectroscopic surveys.Comment: 26pages, 7 figures, and 3 Tables ; Accepted for publication in ApJ; added more data and corrected minor inconsistencies existed in the compiled data of the previous studie

Carbon network evolution from dimers to sheets in superconducting ytrrium dicarbide under pressure

Carbon-bearing compounds display intriguing structural diversity, due to variations in hybrid bonding of carbon. Here, first-principles calculations and unbiased structure searches on yttrium dicarbide at pressure reveal four new structures with varying carbon polymerisation, in addition to the experimentally observed high-temperature low-pressure I4/mmm dimer phase. At low pressures, a metallic C2/m phase (four-member single-chain carbide) is stable, which transforms into a Pnma phase (single-chain carbide) upon increasing pressure, with further transformation to an Immm structure (double-chain carbide) at 54 GPa and then to a P6/mmm phase (sheet carbide) at 267 GPa. Yttrium dicarbide is structurally diverse, with carbon bonded as dimers (at lowest pressure), four-member single chains, infinite single chains, double chains and eventually sheet structures on compression. Electron–phonon coupling calculations indicate that the high-pressure phases are superconducting. Our results aid the understanding and design of new superconductors and illuminate pressure-induced carbon polymerisation in carbides

Body Fat Estimation from Surface Meshes using Graph Neural Networks

Body fat volume and distribution can be a strong indication for a person's overall health and the risk for developing diseases like type 2 diabetes and cardiovascular diseases. Frequently used measures for fat estimation are the body mass index (BMI), waist circumference, or the waist-hip-ratio. However, those are rather imprecise measures that do not allow for a discrimination between different types of fat or between fat and muscle tissue. The estimation of visceral (VAT) and abdominal subcutaneous (ASAT) adipose tissue volume has shown to be a more accurate measure for named risk factors. In this work, we show that triangulated body surface meshes can be used to accurately predict VAT and ASAT volumes using graph neural networks. Our methods achieve high performance while reducing training time and required resources compared to state-of-the-art convolutional neural networks in this area. We furthermore envision this method to be applicable to cheaper and easily accessible medical surface scans instead of expensive medical images

Insight into the Spatial Arrangement of the Lysine Tyrosylquinone and Cu2+ in the Active Site of Lysyl Oxidase-like 2

Lysyl oxidase-2 (LOXL2) is a Cu2+ and lysine tyrosylquinone (LTQ)-dependent amine oxidase that catalyzes the oxidative deamination of peptidyl lysine and hydroxylysine residues to promote crosslinking of extracellular matrix proteins. LTQ is post-translationally derived from Lys653 and Tyr689, but its biogenesis mechanism remains still elusive. A 2.4 Å Zn2+-bound precursor structure lacking LTQ (PDB:5ZE3) has become available, where Lys653 and Tyr689 are 16.6 Å apart, thus a substantial conformational rearrangement is expected to take place for LTQ biogenesis. However, we have recently shown that the overall structures of the precursor (no LTQ) and the mature (LTQ-containing) LOXL2s are very similar and disulfide bonds are conserved. In this study, we aim to gain insights into the spatial arrangement of LTQ and the active site Cu2+ in the mature LOXL2 using a recombinant LOXL2 that is inhibited by 2-hydrazinopyridine (2HP). Comparative UV-vis and resonance Raman spectroscopic studies of the 2HP-inhibited LOXL2 and the corresponding model compounds and an EPR study of the latter support that 2HP-modified LTQ serves as a tridentate ligand to the active site Cu2. We propose that LTQ resides within 2.9 Å of the active site of Cu2+ in the mature LOXL2, and both LTQ and Cu2+ are solvent-exposed

Contrasting Ultra-Low Frequency Raman and Infrared Modes in Emerging Metal Halides for Photovoltaics

Lattice dynamics are critical to photovoltaic material performance, governing dynamic disorder, hot-carrier cooling, charge-carrier recombination, and transport. Soft metal-halide perovskites exhibit particularly intriguing dynamics, with Raman spectra exhibiting an unusually broad low-frequency response whose origin is still much debated. Here, we utilize ultra-low frequency Raman and infrared terahertz time-domain spectroscopies to provide a systematic examination of the vibrational response for a wide range of metal-halide semiconductors: FAPbI3, MAPbI x Br3–x , CsPbBr3, PbI2, Cs2AgBiBr6, Cu2AgBiI6, and AgI. We rule out extrinsic defects, octahedral tilting, cation lone pairs, and “liquid-like” Boson peaks as causes of the debated central Raman peak. Instead, we propose that the central Raman response results from an interplay of the significant broadening of Raman-active, low-energy phonon modes that are strongly amplified by a population component from Bose–Einstein statistics toward low frequency. These findings elucidate the complexities of light interactions with low-energy lattice vibrations in soft metal-halide semiconductors emerging for photovoltaic applications

Fatigue degradation and electric recovery in Silicon solar cells embedded in photovoltaic modules

Cracking in Silicon solar cells is an important factor for the electrical power-loss of photovoltaic modules. Simple geometrical criteria identifying the amount of inactive cell areas depending on the position of cracks with respect to the main electric conductors have been proposed in the literature to predict worst case scenarios. Here we present an experimental study based on the electroluminescence (EL) technique showing that crack propagation in monocrystalline Silicon cells embedded in photovoltaic (PV) modules is a much more complex phenomenon. In spite of the very brittle nature of Silicon, due to the action of the encapsulating polymer and residual thermo-elastic stresses, cracked regions can recover the electric conductivity during mechanical unloading due to crack closure. During cyclic bending, fatigue degradation is reported. This pinpoints the importance of reducing cyclic stresses caused by vibrations due to transportation and use, in order to limit the effect of cracking in Silicon cells