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ASAS-SN follow-up of IceCube high-energy neutrino alerts
No full textWe report on the search for optical counterparts to IceCube neutrino alerts released between 2016 April and 2021 August with the All-Sky Automated Survey for SuperNovae (ASAS-SN). Despite the discovery of a diffuse astrophysical high-energy neutrino flux in 2013, the source of those neutrinos remains largely unknown. Since 2016, IceCube has published likely astrophysical neutrinos as public real-time alerts. Through a combination of normal survey and triggered target-of-opportunity observations, ASAS-SN obtained images within 1 h of the neutrino detection for 20 per cent (11) of all observable IceCube alerts and within one day for another 57 per cent (32). For all observable alerts, we obtained images within at least two weeks from the neutrino alert. ASAS-SN provides the only optical follow-up for about 17 per cent of IceCube’s neutrino alerts. We recover the two previously claimed counterparts to neutrino alerts, the flaring-blazar TXS 0506 + 056 and the tidal disruption event AT2019dsg. We investigate the light curves of previously detected transients in the alert footprints, but do not identify any further candidate neutrino sources. We also analysed the optical light curves of Fermi 4FGL sources coincident with high-energy neutrino alerts, but do not identify any contemporaneous flaring activity. Finally, we derive constraints on the luminosity functions of neutrino sources for a range of assumed evolution models
Fossil Biomarkers and Biosignatures Preserved in Coprolites Reveal Carnivorous Diets in the Carboniferous Mazon Creek Ecosystem
No full textThe reconstruction of ancient trophic networks is pivotal to our understanding of ecosystem function and change through time. However, inferring dietary relationships in enigmatic ecosystems dominated by organisms without modern analogues, such as the Carboniferous Mazon Creek fauna, has previously been considered challenging: preserved coprolites often do not retain sufficient morphology to identify the dietary composition. Here, we analysed n = 3 Mazon Creek coprolites in concretions for dietary signals in preserved biomarkers, stable carbon isotope data, and macromolecular composition. Cholesteroids, metazoan markers of cholesterol, show an increased abundance in the sampled coprolites (86 to 99% of the total steranes) compared to the surrounding sediment, indicating an endogenous nature of preserved organics. Presence of unaltered 5α-cholestan-3β-ol and coprostanol underline the exceptional molecular preservation of the coprolites, and reveal a carnivorous diet for the coprolite producer. Statistical analyses of in situ Raman spectra targeting coprolite carbonaceous remains support a metazoan affinity of the digested fossil remains, and suggest a high trophic level for the coprolite producer. These currently oldest, intact dietary stanols, combined with exquisitely preserved macromolecular biosignatures in Carboniferous fossils offer a novel source of trophic information. Molecular and biosignature preservation is facilitated by rapid sedimentary encapsulation of the coprolites within days to months after egestion
Layered feedback control overcomes performance trade-off in synthetic biomolecular networks
No full textAbstractLayered feedback is an optimization strategy in feedback control designs widely used in engineering. Control theory suggests that layering multiple feedbacks could overcome the robustness-speed performance trade-off limit. In natural biological networks, genes are often regulated in layers to adapt to environmental perturbations. It is hypothesized layering architecture could also overcome the robustness-speed performance trade-off in genetic networks. In this work, we validate this hypothesis with a synthetic biomolecular network in living E. coli cells. We start with system dynamics analysis using models of various complexities to guide the design of a layered control architecture in living cells. Experimentally, we interrogate system dynamics under three groups of perturbations. We consistently observe that the layered control improves system performance in the robustness-speed domain. This work confirms that layered control could be adopted in synthetic biomolecular networks for performance optimization. It also provides insights into understanding genetic feedback control architectures in nature
Stereochemically Active Lone Pairs and Nonlinear Optical Properties of Two-Dimensional Multilayered Tin and Germanium Iodide Perovskites
No full textTwo-dimensional (2D) metal halide perovskites are promising tunable semiconductors. Previous studies have focused on Pb-based structures, whereas the multilayered Sn- and Ge-based analogues are largely unexplored, even though they potentially exhibit more diverse structural chemistry and properties associated with the more polarizable ns2 lone-pair electrons. Herein, we report the synthesis and structures of 2D tin iodide perovskites (BA)₂(A)Sn₂I₇, where BA = n-butylammonium and A = methylammonium, formamidinium, dimethylammonium, guanidinium, or acetamidinium, and those of 2D germanium iodide perovskites (BA)₂(A)Ge₂I₇, where A = methylammonium or formamidinium. By comparing these structures along with their Pb counterparts, we establish correlations between the effect of group IV-cation’s lone-pair stereochemical activity on the perovskite crystal structures and the resulting semiconducting properties such as bandgaps and carrier–phonon interactions and nonlinear optical properties. We find that the strength of carrier–phonon interaction increases with increasing lone-pair activity, leading to a more prominent photoluminescence tail on the low-energy side. Moreover, (BA)₂(A)Ge₂I₇ exhibit strong second harmonic generation with second-order nonlinear coefficients of ∼10 pm V⁻¹ that are at least 10 times those of Sn counterparts and 100 times those of Pb counterparts. We also report the third-order two-photon absorption coefficients of (BA)₂(A)Sn₂I₇ to be ∼10 cm MW⁻¹, which are one order of magnitude larger than those of the Pb counterparts and traditional inorganic semiconductors. These results not only highlight the role of lone-pair activity in linking the compositions and physical properties of 2D halide perovskites but also demonstrate 2D tin and germanium iodide perovskites as promising lead-free alternatives for nonlinear optoelectronic devices
Reports from the Frontier
No full textECS Interface is proud to introduce a new feature page that focuses on the award-winning research of ECS graduate students
Distinguishing 6D (1, 0) SCFTs: An extension to the geometric construction
No full textWe provide a new extension to the geometric construction of six-dimensional (6D) (1,0) superconformal field theories (SCFTs) that encapsulates Higgs branch structures with identical global symmetry but different spectra. In particular, we find that there exist distinct 6D (1,0) SCFTs that may appear to share their tensor branch description, flavor symmetry algebras, and central charges. For example, such subtleties arise for the very even nilpotent Higgsing of (so_(4k), so_(4k)) conformal matter; we propose a method to predict at which conformal dimension the Higgs branch operators of the two theories differ via augmenting the tensor branch description with the Higgs branch chiral ring generators of the building block theories. Torus compactifications of these 6D (1,0) SCFTs give rise to four-dimensional (4D) N = 2 SCFTs of class-S, and the Higgs branch of such 4D theories are captured via the Hall-Littlewood index. We confirm that the resulting 4D theories indeed differ in their spectra in the predicted conformal dimension from their Hall-Littlewood indices. We highlight how this ambiguity in the tensor branch description arises beyond the very even nilpotent Higgsing of (so_(4k), so_(4k)) conformal matter and hence should be understood for more general classes of 6D (1,0) SCFTs
Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning
No full textThis study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree–Fock computations. A MOB pairwise decomposition of the correlation part of the dipole moment is applied, and these pair dipole moments could be further regressed as a universal function of MOs. The dipole MOB features consist of the energy MOB features and their responses to electric fields. An interpretable and rotationally equivariant derivative kernel for Gaussian process regression (GPR) is introduced to learn the dipole moment more efficiently. The proposed problem setup, feature design, and ML algorithm are shown to provide highly accurate models for both dipole moments and energies on water and 14 small molecules. To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test the molecules from the QM9 dataset. The application of local scalable GPR with Gaussian mixture model unsupervised clustering GPR scales up MOB-ML to a large-data regime while retaining the prediction accuracy. In addition, compared with the literature results, MOB-ML provides the best test mean absolute errors of 4.21 mD and 0.045 kcal/mol for dipole moment and energy models, respectively, when training on 110 000 QM9 molecules. The excellent transferability of the resulting QM9 models is also illustrated by the accurate predictions for four different series of peptides
A Clear View of a Cloudy Brown Dwarf Companion from High-resolution Spectroscopy
No full textDirect imaging studies have mainly used low-resolution spectroscopy (R ∼ 20–100) to study the atmospheres of giant exoplanets and brown dwarf companions, but the presence of clouds has often led to degeneracies in the retrieved atmospheric abundances (e.g., carbon-to-oxygen ratio, metallicity). This precludes clear insights into the formation mechanisms of these companions. The Keck Planet Imager and Characterizer (KPIC) uses adaptive optics and single-mode fibers to transport light into NIRSPEC (R ∼ 35,000 in the K band), and aims to address these challenges with high-resolution spectroscopy. Using an atmospheric retrieval framework based on petitRADTRANS, we analyze the KPIC high-resolution spectrum (2.29–2.49 μm) and the archival low-resolution spectrum (1–2.2 μm) of the benchmark brown dwarf HD 4747 B (m = 67.2 ± 1.8 M_(Jup), a = 10.0 ± 0.2 au, T_(eff) ≈ 1400 K). We find that our measured C/O and metallicity for the companion from the KPIC high-resolution spectrum agree with those of its host star within 1σ–2σ. The retrieved parameters from the K-band high-resolution spectrum are also independent of our choice of cloud model. In contrast, the retrieved parameters from the low-resolution spectrum are highly sensitive to our chosen cloud model. Finally, we detect CO, H₂O, and CH₄ (volume-mixing ratio of log(CH₄) = −4.82 ± 0.23) in this L/T transition companion with the KPIC data. The relative molecular abundances allow us to constrain the degree of chemical disequilibrium in the atmosphere of HD 4747 B, and infer a vertical diffusion coefficient that is at the upper limit predicted from mixing length theory
Magnussonite, Mn²⁺₁₈ (As³⁺O₃)₆Mn¹⁺ₓ(H₂O, Clₓ, ☐): Re-Examination of the Structure and the [Mn¹⁺(As³⁺O₃)₆] Cluster
No full textThe crystal structure of magnussonite, ideally Mn²⁺₁₈[As³⁺₆(Mn¹⁺ₓ)O1₁₈]₂[(H₂O, Clₓ, ☐) (H₂O, ☐)]₂, from Långban, Sweden, was refined to an R₁-index of 1.19% and the structure proposed by Moore and Araki (1979) is confirmed. Magnussonite has a densely packed structure of (Mnφₙ) polyhedra, φ = (O²⁻, H₂O, Cl⁻), and (As³⁺O₃) triangular pyramids that is best envisaged as layers of polyhedra in the same way as many of the other manganese-arsenite-arsenate structures from Långban. There are two distinct layers in magnussonite; the two layers may be combined into a slab that stacks along the a-direction with rotations between adjacent slabs. A surprising feature of the dense-packed magnussonite atomic arrangement is an array of structural channels along [111] that contain much of the disorder that occurs in the magnussonite structure. The channels contain the partly occupied MX site on the central axis of the channel, and the CLW2 site (with extremely low occupancy), also on the central axis of the channel. The CLW2 site, previously unrecognized in the magnussonite structure, contains H₂O, whereas the minor Cl in the structure resides in the CLW1 channel site, balancing the charge of the MX-site occupant. The MX site on the central axis of the channels displays a coordination known only in Långban minerals. In the local arrangement around the unoccupied MX site, the neighboring (As³⁺O₃) groups project their associated stereoactive lone-pairs of electrons into the channel. Where the MX site is occupied by Mn, there are six lone-pairs of electrons pointing toward Mn; the 18-electron rule predicts/rationalizes formulae for this stable transition-metal cluster. The (As³⁺O₃) groups and MX occupant form a [Mn⁺(As³⁺O₃)₆] arrangement in accord with the 18-electron rule where Mn+ contributes 6 3d electrons and the six lone-pairs of the [(As³⁺O₃)₆] arrangement contribute 12 electrons for a total of 18 electrons that form nine molecular orbitals that are metal-ligand bonds or non-bonding. Magnussonite and dixenite, another basic manganese-iron arsenate-arsenite-silicate mineral of the Långban-type deposits in Bergslagen, Sweden, are the only two minerals known with such local [M⁺(As³⁺O₃)ₙ] transition-metal clusters. The presence of these exotic clusters in structures containing densely packed Mn²⁺ octahedra is not understood at present
Tutorial: Dynamic organic growth modeling with a volatility basis set
No full textOrganic aerosols are ubiquitous in the atmosphere and oxygenated organics are a major driver of aerosol growth. The volatility basis set (VBS) as introduced by Donahue et al. (2006, 2011) is often used to simplify the partitioning behavior of the huge variety of atmospheric organics. Recently, the VBS was used to dynamically model aerosol growth from the smallest sizes onwards. This tutorial is intended to equip the reader with the necessary tools to facilitate organic growth modelling based on gas-phase measurements of oxygenated organics using a 2-dimensional VBS. We start with a contextualization of the VBS in partitioning theory and point out the need for dynamic modeling. We provide an overview on the most common methods to estimate the volatility of oxygenated organics and give detailed instruction on how to construct the binned VBS. We then explain the dynamic condensation model including solution and curvature effects. Furthermore, we provide a python package for VBS growth calculations and show with two examples from ambient and chamber measurements how growth rates can be calculated. Last, we summarize the limitation of this approach and outline necessary future developments