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Plastic Laminate Antireflective Coatings for Millimeter-Wave Optics in BICEP Array
No full textThe BICEP/Keck series of experiments target the cosmic microwave background at degree-scale resolution from the South Pole. Over the next few years, the “Stage-3” BICEP Array (BA) telescope will improve the program’s frequency coverage and sensitivity to primordial B-mode polarization by an order of magnitude. The first receiver in the array, BA1, began observing at 30/40 GHz in early 2020. The next two receivers, BA2 and BA3, are currently being assembled and will map the southern sky at frequencies ranging from 95 to 150 GHz. Common to all BA receivers is a refractive, on-axis, cryogenic optical design that focuses microwave radiation onto a focal plane populated with antenna-coupled bolometers. High-performance antireflective coatings up to 760 mm in aperture are needed for each element in the optical chain, and must withstand repeated thermal cycles down to 4 K. Here, we present the design and fabrication of the 30/40 GHz anti-reflection coatings for the recently deployed BA1 receiver, with indices matched to its various polyethylene, nylon and alumina optical components. We describe an epoxy coating technique designed for alumina optics, which achieves better than 80% transmission at room temperature. For polyethylene optical elements, we present a new heat-compression approach that allows low-density polytetrafluoroethylene AR layers to reach sub-percent reflected power. We describe the planned use of these methods for the next BA cryostats, which may inform technological choices for future small-aperture telescopes of the CMB-S4 experiment
GABAergic role in the disruption of wild cleaner fish behaviour under high CO₂
No full textOcean acidification is considered to affect fish behaviour through the disruption of GABAergic neurotransmission in controlled laboratory conditions, but less is known of the GABAergic role on fish behavioural performance in the wild. Most coral reef fishes engage in complex cleaning interactions, where they benefit from ectoparasite removal and stress relief. Here, we tested whether potential ocean acidification impairment of wild cleaning interactions, between the cleaner fish Labroides dimidiatus and its clients, can be explained by the GABAAR model. We used, the GABAA receptor agonist (muscimol) and antagonist (gabazine) for the first time in the wild and tested their effects on cleaning behaviour in Moorea Island (French Polynesia) to address natural interactions and recovery capacity. After exposure to expected ocean acidification conditions, the proportion of time spent advertising cleaning services, a measure of motivation to interact, dropped significantly relative to controls. Furthermore, the GABAergic antagonist gabazine recovered most CO₂-induced behavioural alterations to control levels, consistent with the GABAAR model of altered Cl⁻ flux in ocean acidification-exposed fish. However, muscimol treatment only produced the same behavioural alterations found with CO₂ exposure in time spent advertising cleaning. Our results support the evidence that ocean acidification alters some components of cleaning behaviour through GABAA receptor modulation with potential cascading effects on coral reef health and structure
Damage localization and robust diagnostics in guided-wave testing using multitask complex hierarchical sparse Bayesian learning
No full textThe inversion of guided-wave data for accurate damage localization is a challenging problem when using guided waves for nondestructive testing and robust diagnostics. It is especially important to detect incorrect damage localization without knowing the original damage. In this paper, a new damage localization and robust diagnostics method is proposed. A Multi-task Complex Hierarchical Sparse Bayesian learning (MuCHSBL) algorithm is presented to solve the inverse problem for damage localization based on the data measured from a small number of sensors. The multi-task model improves the efficacy of damage localization by utilizing the consistency of damage locations for tasks with different signal frequencies. A Sparse Bayesian learning algorithm is also introduced to utilize the spatial sparsity of the damage, since structural damage typically occurs at only a few localized areas. The quantified posterior uncertainty of the model parameters gives a sense of confidence in the damage localization results. Utilizing the different levels of uncertainty in the optimal and suboptimal inversion models, diagnostic tools are proposed to detect whether the inversion for damage localization is accurate, without knowing the original damage. Numerical and experimental studies are carried out to verify the effectiveness of the proposed method. It is demonstrated that the damage localization efficacy of multi-task model is much higher than that of single-task model; moreover, the accuracy of damage localization results can be diagnosed effectively by the posterior uncertainty quantification of the model parameters
Thermomechanical Properties of Nontoxic Plasticizers for Polyvinyl Chloride Predicted from Molecular Dynamics Simulations
No full textEnvironmental and toxicity concerns dictate replacement of di(2-ethylhexyl) phthalate (DEHP) plasticizer used to impart flexibility and thermal stability to polyvinyl chloride (PVC). Potential alternatives to DEHP in PVC include diheptyl succinate (DHS), diethyl adipate (DEA), 1,4-butanediol dibenzoate (1,4-BDB), and dibutyl sebacate (DBS). To examine whether that these bio-based plasticizers can compete with DEHP, we need to compare their tensile, mechanical, and diffusional properties. This work focuses on predicting the effect these plasticizers have on Tg, Young’s modulus, shear modulus, fractional free volume, and diffusion for PVC–plasticizer systems. Where data was available, the results from this study are in good agreement with the experiment; we conclude that DBS and DHS are most promising green plasticizers for PVC, since they have properties comparable to DEHP but not the environmental and toxicity concerns
A Surrogate Machine Learning Model for the Design of Single-Atom Catalyst on Carbon and Porphyrin Supports towards Electrochemistry
No full textWe apply the machine learning (ML) tool to calculate the Gibbs free energy (ΔG) of reaction intermediates rapidly and accurately as a guide for designing porphyrin- and graphene-supported single-atom catalysts (SACs) toward electrochemical reactions. Based on the 2105 DFT calculation data from the literature, we trained a support vector machine (SVR) algorithm. The hyperparameters were optimized using Bayesian optimization along with 10-fold cross-validation to avoid overfitting. Based on the Shapley Additive exPlanation (SHAP) and permutation methods, the feature importance analysis suggests that the most important parameters are the number of pyridinic nitrogen (Npy), the number of d electrons (θᵈ), and the number of valence electrons of reaction intermediates. Inspired by this feature importance analysis and the Pearson correlation coefficient, we found a linear dependent, simple, and general descriptor (φ) to describe ΔG of reaction intermediates (e.g., ΔG_(OH*) = 0.020φ – 2.190). Using the trained SVR algorithm, ΔG_(OH*), ΔG_(O*), ΔG_(OOH*), ΔG_(OO*), ΔG_(H*), ΔG_(COOH*), ΔG_(CO*), and ΔG_(N₂*) intermediates are predicted for the oxygen reduction reaction (ORR), the oxygen evolution reaction (OER), the hydrogen evolution reaction (HER), and the CO₂ reduction reaction (CO2RR). The SVR model predicts an ORR overpotential of 0.51 V and an HER overpotential of 0.22 V for FeN4-SAC. Moreover, we used the SVR algorithm for high-throughput screening of SACs, suggesting new SACs with low ORR overpotentials. This strategy provides a data-driven catalyst design method that significantly reduces the costs of DFT calculations while providing the means for designing SACs for electrocatalysis and beyond
A stochastic search for intermittent gravitational-wave backgrounds
No full textA likely source of a gravitational-wave background (GWB) in the frequency band of the Advanced LIGO, Virgo, and KAGRA detectors is the superposition of signals from the population of unresolvable stellar-mass binary-black-hole (BBH) mergers throughout the Universe. Since the duration of a BBH merger in band (∼1 s) is much shorter than the expected separation between neighboring mergers (∼10³ s), the observed signal will be “popcornlike” or intermittent with duty cycles of order 10⁻³. However, the standard cross-correlation search for stochastic GWBs currently performed by the LIGO-Virgo-KAGRA Collaboration is based on a continuous-Gaussian signal model, which does not take into account the intermittent nature of the background. The latter is better described by a Gaussian mixture model, which includes a duty cycle parameter that quantifies the degree of intermittence. Building on an earlier paper by Drasco and Flanagan [Detection methods for non-gaussian gravitational wave stochastic backgrounds, Phys. Rev. D 67, 082003 (2003).], we propose a stochastic-signal-based search for intermittent GWBs. For such signals, this search performs better than the standard continuous cross-correlation search. We present results of our stochastic-signal-based approach for intermittent GWBs applied to simulated data for some simple models, and we compare its performance to the other search methods, in terms of both detection and signal characterization. Additional testing on more realistic simulated datasets, e.g., consisting of astrophysically motivated BBH merger signals injected into colored detector noise containing noise transients, will be needed before this method can be applied with confidence on real gravitational-wave data
A non-ergodic spectral acceleration ground motion model for California developed with random vibration theory
No full textA new approach for creating a non-ergodic pseudo-spectral acceleration (PSA) ground-motion model (GMM) is presented, which accounts for the magnitude dependence of the non-ergodic effects. In this approach, the average PSA scaling is controlled by an ergodic PSA GMM, and the non-ergodic effects are captured with non-ergodic PSA factors, which are the adjustment that needs to be applied to an ergodic PSA GMM to incorporate the non-ergodic effects. The non-ergodic PSA factors are based on the effective amplitude spectrum (EAS) non-ergodic effects and are converted to PSA through Random Vibration Theory (RVT). The advantage of this approach is that it better captures the non-ergodic source, path, and site effects through small-magnitude earthquakes. Due to the linear properties of the Fourier Transform, the EAS non-ergodic effects of the small events can be applied directly to the large magnitude events. This is not the case for PSA, as response spectra are controlled by a range of frequencies, making PSA non-ergodic effects dependent on the spectral shape, which in turn is magnitude-dependent. Two PSA non-ergodic GMMs are derived using the ASK14 (Abrahamson et al. in Earthq Spectra 30:1025–1055, 2014) and CY14 (Chiou and Youngs in Earthq Spectra 30:1117–1153, 2014) GMMs as backbone models, respectively. The non-ergodic EAS effects are estimated with the LAK21 (Lavrentiadis et al. in Bull Earthq Eng ) GMM. The RVT calculations are performed with the V75 (Vanmarcke in ASCE Mech Eng Mech Division 98:425–446, 1972) peak factor model, the D_(a0.05−0.85) estimate of AS96 (Abrahamson and Silva in Apendix A: empirical ground motion models, description and validation of the stochastic ground motion model. Tech. rep.,. Brookhaven National Laboratory, New York) for the ground-motion duration, and BT15 (Boore and Thompson in Bull Seismol Soc Am 105:1029–1041, 2015) oscillator-duration model. The California subset of the NGAWest2 database (Ancheta et al. in Earthq Spectra 30:989–1005, 2014) is used to fit both models. The total aleatory standard deviation of each of the two non-ergodic PSA GMMs is approximately 25% smaller than the total aleatory standard deviation of the corresponding ergodic PSA GMMs. This reduction has a significant impact on hazard calculations at large return periods. In remote areas, far from stations and past events, the reduction of aleatory variability is accompanied by an increase in epistemic uncertainty
Early Results from GLASS-JWST. XV. Properties of the Faintest Red Sources in the NIRCAM Deep Fields
No full textWe present a first look at the reddest 2–5 μm sources found in deep images from the GLASS Early Release Science program. We undertake a general search, i.e., not looking for any particular spectral signatures, for sources detected only in bands redder than is reachable with the Hubble Space Telescope, and which would likely not have been identified in pre-JWST surveys. We search for sources down to AB ∼27 (corresponding to >10σ detection threshold) in any of the F200W to F444W filters, with a >1 magnitude excess relative to F090W to F150W bands. Fainter than F444W >25 we find 56 such sources of which 37 have reasonably constrained spectral energy distributions to which we can fit photometric redshifts. We find the majority of this population (∼65%) as 2 2 μm boosted by a combination of the Balmer break and emission lines. The typical implied rest equivalent widths are ∼200 Å with some extreme objects up to ∼1000 Å. This is in contrast with brighter magnitudes where the red sources tend to be z 11 galaxies and a very cool brown dwarf
Copper-catalysed enantioconvergent alkylation of oxygen nucleophiles
No full textCarbon–oxygen bonds are commonplace in organic molecules, including chiral bioactive compounds; therefore, the development of methods for their construction with simultaneous control of stereoselectivity is an important objective in synthesis. The Williamson ether synthesis, first reported in 1850, is the most widely used approach to the alkylation of an oxygen nucleophile, but it has significant limitations (scope and stereochemistry) owing to its reaction mechanism (SN2 pathway). Transition-metal catalysis of the coupling of an oxygen nucleophile with an alkyl electrophile has the potential to address these limitations, but progress so far has been limited, especially with regard to controlling enantioselectivity. Here we establish that a readily available copper catalyst can achieve an array of enantioconvergent substitution reactions of α-haloamides, a useful family of electrophiles, by oxygen nucleophiles; the reaction proceeds under mild conditions in the presence of a wide variety of functional groups. The catalyst is uniquely effective in being able to achieve enantioconvergent alkylations of not only oxygen nucleophiles but also nitrogen nucleophiles, giving support for the potential of transition-metal catalysts to provide a solution to the pivotal challenge of achieving enantioselective alkylations of heteroatom nucleophiles
Earthquake Magnitude With DAS: A Transferable Data‐Based Scaling Relation
No full textDistributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Previous DAS studies mainly focus on the phase information but less on the amplitude information. In this study, we compile earthquake data from two DAS arrays in California, USA, and one submarine array in Sanriku, Japan. We develop a data-driven method to obtain the first scaling relation between DAS amplitude and earthquake magnitude. Our results reveal that the earthquake amplitudes recorded by DAS in different regions follow a similar scaling relation. The scaling relation can provide a rapid earthquake magnitude estimation and effectively avoid uncertainties caused by the conversion to ground motions. Our results show that the scaling relation appears transferable to new regions with calibrations. The scaling relation highlights the great potential of DAS in earthquake source characterization and early warning