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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Synthetic antibacterial minerals: harnessing a natural geochemical reaction to combat antibiotic resistance

The overuse of antibiotics in clinical and livestock settings is accelerating the selection of multidrug resistant bacterial pathogens. Antibiotic resistant bacteria result in increased mortality and financial strain on the health care and livestock industry. The development of new antibiotics has stalled, and novel strategies are needed as we enter the age of antibiotic resistance. Certain naturally occurring clays have been shown to have antimicrobial properties and kill antibiotic resistant bacteria. Harnessing the activity of compounds within these clays that harbor antibiotic properties offers new therapeutic opportunities for fighting the potentially devastating effects of the post antibiotic era. However, natural samples are highly heterogenous and exhibit variable antibacterial effectiveness, therefore synthesizing minerals of high purity with reproducible antibacterial activity is needed. Here we describe for the first time synthetic smectite clay minerals and Fe-sulfide microspheres that reproduce the geochemical antibacterial properties observed in natural occurring clays. We show that these mineral formulations are effective at killing the ESKAPE pathogens ( Enterococcus sp., Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter sp., Pseudomonas aeruginosa and Enterobacter sp.) by maintaining Fe 2+ solubility and reactive oxygen species (ROS) production while buffering solution pH, unlike the application of metals alone. Our results represent the first step in utilizing a geochemical process to treat antibiotic resistant topical or gastrointestinal infections in the age of antibiotic resistance.

58 GEOSCIENCES↗
DOE OSTI2017

Sequential Designs Based on Bayesian Uncertainty Quantification in Sparse Representation Surrogate Modeling

A numerical method, called OBSM, was recently proposed which employs overcomplete basis functions to achieve sparse representations. While the method can handle non-stationary response without the need of inverting large covariance matrices, it lacks the capability to quantify uncertainty in predictions. We address this issue by proposing a Bayesian approach which first imposes a normal prior on the large space of linear coefficients, then applies the MCMC algorithm to generate posterior samples for predictions. From these samples, Bayesian credible intervals can then be obtained to assess prediction uncertainty. A key application for the proposed method is the efficient construction of sequential designs. Several sequential design procedures with different infill criteria are proposed based on the generated posterior samples. As a result, numerical studies show that the proposed schemes are capable of solving problems of positive point identification, optimization, and surrogate fitting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Measurement of event shapes in minimum-bias events from proton-proton collisions at $\sqrt{s}$ = 13

A measurement of event-shape variables is presented, using a data sample produced in a special run with approximately one inelastic proton-proton collision per bunch crossing. The data were collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 64 μ⁢b −1 . A number of observables related to the overall distribution of charged particles in the collisions are corrected for detector effects and compared with simulations. Inclusive event-shape distributions, as well as differential distributions of event shapes as functions of charged-particle multiplicity, are studied. None of the models investigated are able to satisfactorily describe the data. Moreover, there are significant features common amongst all generator setups studied, particularly showing data being more isotropic than any of the simulations. Multidimensional unfolded distributions are provided, along with their correlations.

Chekhovsky, V. [Yerevan Physics Institute]↗
DOE OSTI2016

Parameters associated with design effect of child anthropometry indicators in small-scale field surveys

Background: Cluster surveys provide rapid but representative estimates of key nutrition indicators in humanitarian crises. For these surveys, an accurate estimate of the design effect is critical to calculate a sample size that achieves adequate precision with the minimum number of sampling units. This paper describes the variability in design effect for three key nutrition indicators measured in small-scale surveys and models the association of design effect with parameters hypothesized to explain this variability. Methods: 380 small-scale surveys from 28 countries conducted between 2006 and 2013 were analyzed. We calculated prevalence and design effect of wasting, underweight, and stunting for each survey as well as standard deviations of the underlying continuous Z-score distribution. Mean cluster size, survey location and year were recorded. To describe design effects, median and interquartile ranges were examined. Generalized linear regression models were run to identify potential predictors of design effect. Results: Median design effect was under 2.00 for all three indicators; for wasting, the median was 1.35, the lowest among the indicators. Multivariable linear regression models suggest significant, positive associations of design effect and mean cluster size for all three indicators, and with prevalence of wasting and underweight, but not stunting. Standard deviation was positively associated with design effect for wasting but negatively associated for stunting. Survey region was significant in all three models. Conclusions: This study supports the current field survey guidance recommending the use of 1.5 as a benchmark for design effect of wasting, but suggests this value may not be large enough for surveys with a primary objective of measuring stunting or underweight. The strong relationship between design effect and region in the models underscores the continued need to consider country- and locality-specific estimates when designing surveys. These models also provide empirical evidence of a positive relationship between design effect and both mean cluster size and prevalence, and introduces standard deviation of the underlying continuous variable (Z-scores) as a previously unexplored factor significantly associated with design effect. The magnitude and directionality of this association differed by indicator, underscoring the need for further investigation into the relationship between standard deviation and design effect.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Organic carbon feedbacks to soil structure in Profundihumic and Haplic Ferralsols in Campinas, Sao Paulo, Brazil

Increasing soil organic matter content coincides with increasing soil porosity and decreasing bulk density, but the mechanisms that lead to changes in soil structure are unclear. We quantified and compared soil characteristics across two contrasting soils (heavily weathered ferralsols in Brazil) to clarify the effects of organic matter content on soil porosity. We found that high organic matter content fosters higher biologic activity, including root growth and animal burrowing, which in turn increase soil porosity and decreases bulk density.This dataset includes soil physical, morophological, and chemical variables from 6 soil profiles were sampled in Campinas, Sa ̃o Paulo state, southeastern Brazil to 1 m depth. Sites are regenerated mixed savanna and rainforest in the protected area of Viracopos Airport in Campinas, lightly grazed by cattle.This dataset includes soil color, bulk density, texture (percent sand, silt, clay, and coarse fragments as well as class), soil pH, cation exchange capacity, C stock, C concentration, N stock, N concentration, delta 13C, Delta 14C, and soil porosity in Excel and csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Antibacterial Minerals: A geochemical approach to combating antibiotic resistance

The rapid rise of antibiotic resistant bacteria is seriously threatening our ability to treat lifethreatening infections. As a result, our approach to medicine and agriculture will require significant changes if we are to successfully maintain current levels of healthcare and food security. Certain naturally occurring clays have been shown to harbor antimicrobial properties and kill antibiotic resistant bacteria. These clays have been proposed as a new paradigm for fighting the potentially devastating effects of the post antibiotic era. However, natural samples, by their inherent properties, exhibit variable antibacterial effectiveness and the synthesis of minerals with reproducible antibacterial activity is needed. Our project focused on 3 specific aims; 1) develop synthetic versions of naturally occurring bactericidal minerals to control the chemical purity and antibacterial potency, 2) determine how effective these mineral formulations are at killing antibiotic resistant bacteria and 3) investigate the response of human skin cell cultures to these antibacterial minerals. Utilizing hydrothermal based methods our team was able to reproduce the antibacterial activity observed in natural antibacterial minerals, while eliminating unwanted elemental impurities. Importantly, we were able to create a mineral based bactericide that has reproducible reactivity that could provide a consistent dose response. These antibacterial mineral formulations are effective at killing common hospital acquired antibiotic resistant bacteria while providing minimal toxicity to human fibroblasts. Our research has optimized the antibacterial properties of antibacterial minerals to allow greater efficacy from a public health perspective.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Intra-night Optical Variability Monitoring of Fermi Blazars: First Results from 1.3 m J. C. Bhattacharya Telescope

We report the first results obtained from our campaign to characterize the intra-night-optical variability (INOV) properties of Fermi detected blazars, using the observations from the recently commissioned 1.3 m J. C. Bhattacharya telescope (JCBT). During the first run, we were able to observe 17 blazars in the Bessel R filter for ∼137 hr. Using C- and scaled F -statistics, we quantify the extent of INOV and derive the duty cycle (DC), which is the fraction of time during which a source exhibits a substantial flux variability. We find a high DC of 40% for BL Lac objects and the flat spectrum radio quasars are relatively less variable (DC ∼ 15%). However, when estimated for blazars sub-classes, a high DC of ∼59% is found in low synchrotron peaked (LSP) blazars, whereas, intermediate and high synchrotron peaked objects have a low DC of ∼11% and 13%, respectively. We find evidence of the association of the high amplitude INOV with the γ -ray flaring state. We also notice a high polarization during the elevated INOV states (for the sources that have polarimetric data available), thus supporting the jet based origin of the observed variability. We plan to enlarge the sample and utilize the time availability from the small telescopes, such as 1.3 m JCBT, to strengthen/verify the results obtained in this work and those existing in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The BAT AGN Spectroscopic Survey. XVIII. Searching for Supermassive Black Hole Binaries in X-Rays

Theory predicts that a supermassive black hole binary (SMBHB) could be observed as a luminous active galactic nucleus (AGN) that periodically varies on the order of its orbital timescale. In X-rays, periodic variations could be caused by mechanisms including relativistic Doppler boosting and shocks. In this paper we present the first systematic search for periodic AGNs using 941 hard X-ray light curves (14–195 keV) from the first 105 months of the Swift Burst Alert Telescope (BAT) survey (2004–2013). We do not find evidence for periodic AGNs in Swift-BAT, including the previously reported SMBHB candidate MCG+11–11–032. We find that the null detection is consistent with the combination of the upper-limit binary population in AGNs in our adopted model, their expected periodic variability amplitudes, and the BAT survey characteristics. We have also investigated the detectability of SMBHBs against normal AGN X-ray variability in the context of the extended ROentgen Survey with an Imaging Telescope Array (eROSITA) survey. Under our assumptions of a binary population and the periodic signals they produce, which have long periods of hundreds of days, up to 13% true periodic binaries can be robustly distinguished from normal variable AGNs with the ideal uniform sampling. However, we demonstrate that realistic eROSITA sampling is likely to be insensitive to long-period binaries because longer observing gaps reduce their detectability. In contrast, large observing gaps do not diminish the prospect of detecting binaries of short, few-day periods, as 19% can be successfully recovered, the vast majority of which can be identified by the first half of the survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Intercomparison of biomass burning aerosol optical properties from in situ and remote-sensing instruments in ORACLES-2016

The total effect of aerosols, both directly and on cloud properties, remains the biggest source of uncertainty in anthropogenic radiative forcing on the climate. Correct characterization of intensive aerosol optical properties, particularly in conditions where absorbing aerosol is present, is a crucial factor in quantifying these effects. The southeast Atlantic Ocean (SEA), with seasonal biomass burning smoke plumes overlying and mixing with a persistent stratocumulus cloud deck, offers an excellent natural laboratory to make the observations necessary to understand the complexities of aerosol–cloud–radiation interactions. The first field deployment of the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign was conducted in September of 2016 out of Walvis Bay, Namibia. Data collected during ORACLES-2016 are used to derive aerosol properties from an unprecedented number of simultaneous measurement techniques over this region. Here, we present results from six of the eight independent instruments or instrument combinations, all applied to measure or retrieve aerosol absorption and single-scattering albedo. Most but not all of the biomass burning aerosol was located in the free troposphere, in relative humidities typically ranging up to 60%. We present the single-scattering albedo (SSA), absorbing and total aerosol optical depth (AAOD and AOD), and absorption, scattering, and extinction Ångström exponents (AAE, SAE, and EAE, respectively) for specific case studies looking at near-coincident and near-colocated measurements from multiple instruments, and SSAs for the broader campaign average over the month-long deployment. For the case studies, we find that SSA agrees within the measurement uncertainties between multiple instruments, though, over all cases, there is no strong correlation between values reported by one instrument and another. We also find that agreement between the instruments is more robust at higher aerosol loading (AOD 400 > 0.4 ).The campaign-wide average and range shows differences in the values measured by each instrument. We find the ORACLES-2016 campaign-average SSA at 500 > nm (SSA 500 ) to be between 0.85 and 0.88, depending on the instrument considered (4STAR, AirMSPI, or in situ measurements), with the interquartile ranges for all instruments between 0.83 and 0.89. This is consistent with previous September values reported over the region (between 0.84 and 0.90 for SSA at 550nm). The results suggest that the differences observed in the campaign-average values may be dominated by instrument-specific spatial sampling differences and the natural physical variability in aerosol conditions over the SEA, rather than fundamental methodological differences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Cryogenic Readout IC with 100 KSPS in-Pixel ADC for Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit (SPROCKET) is a mixed-signal front-end design for the readout of Skipper CCD-in-CMOS image sensors. SPROCKET is fabricated in a 65 nm CMOS process and each pixel occupies a 50$\mu$m $\times$ 50$\mu$m footprint. SPROCKET is intended to be heterogeneously integrated with a Skipper-in-CMOS sensor array, such that one readout pixel is connected to a multiplexed array of nine Skipper-in-CMOS pixels to enable massively parallel readout. The front-end includes a variable gain preamplifier, a correlated double sampling circuit, and a 10-bit serial successive approximation register (SAR) ADC. The circuit achieves a sample rate of 100 ksps with 0.48 $\mathrm{e^-_{rms}}$ equivalent noise at the input to the ADC. SPROCKET achieves a maximum dynamic range of 9,000 $e^-$ at the lowest gain setting (or 900 $e^-$ at the lowest noise setting). The circuit operates at 100 Kelvin with a power consumption of 40 $\mu W$ per pixel. A SPROCKET test chip was submitted in September 2022, and test results will be presented at the conference.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Synoptic NO3 in Slate River Watershed, Colorado (2022)

The synoptic nitrate (NO3) dataset in the Slate River Watershed, Colorado consists of NO3 data collected at 19 locations three times during the summer of 2022. Stream samples were collected in early summer (early July), mid summer (late August), and late summer (late September). The samples include mainstem, tributary, and point source input water samples. These data were collected to evaluate spatiotemporal variability in stream NO3 during the summer, and evaluate anthropogenic controls on stream NO3 dynamics. This data package contains: (1) a csv of all NO3 samples and (2) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATE↗
DOE OSTI2018

Assessment of Tritium Activities in Bailed versus Pumped Samples from Wells at the Nevada National Security Site

The Underground Test Area (UGTA) Activity uses a variety of methods to collect groundwater samples to identify radionuclide migration from underground nuclear tests. These include depth-discrete bailing, pumping with low-volume rod pumps, and pumping with electrical submersible pumps. The Nevada National Security Site (NNSS) Integrated Groundwater Sampling Plan specifies that when sampling with a pump, a minimum of three effective well volumes are withdrawn and then samples are collected after water-quality parameters have stabilized. In locations where pumping is not feasible, depth-discrete bailing is used and purging prior to sampling is usually not required. A recent study evaluated three sampling technologies and recommended that historical tritium results be evaluated where both pumped and bailed samples are available to identify preferred sampling protocols for the collection of tritium samples. The tritium ( 3 H) activities were obtained from the UGTA chemistry data base. Wells were identified with known 3 H activities above method detection limits, and then evaluated if both bailed and pumped samples had been collected. Twenty two wells and piezometers with bailed samples, pumped samples, and 3 H activities above background were identified for further consideration. The conclusions from this analysis are: Bailed samples collected for 3 H analysis near the water surface in a well are lower in 3 H activity than bailed samples from within screened intervals and pumped samples. Depth-discrete bailed samples from within the screened intervals are generally in good agreement with pumped samples from developed wells and piezometers. Depth-discrete bailed samples from undeveloped wells and piezometers are in good agreement with the first pumped samples. However, the next pumped samples increased in 3 H activity, resulting in a greater percent difference between the undeveloped bailed samples and later pumped samples. Continuous pumping over extended periods removing large purge volumes from wells can perturbate the surrounding groundwater system for long periods of time. These perturbations can cause large changes in 3 H activities in the aquifer near the well because of the mixing of groundwater with variable 3 H activities. Recommendations include: Bailed samples for 3 H should not be collected near the water surface in the well. Bailed samples should be collected from within the well screen. Logs of temperature, chemistry, and thermal flow should be evaluated to identify optimal depths within the well screen to collect depth-discrete bailer samples. Purging of large volumes of water from the well over extended periods of time should be avoided when collecting 3 H samples. Sufficient time should be allowed after pumping large volumes of water from the well (e.g., after well development) for the surrounding aquifer and 3 H activities to return to ambient conditions

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Genome-resolved metagenomics of eukaryotic populations during early colonization of premature infants and in hospital rooms

Background: Fungal infections are a significant cause of mortality and morbidity in hospitalized preterm infants, yet little is known about eukaryotic colonization of infants and of the neonatal intensive care unit as a possible source of colonizing strains. This is partly because microbiome studies often utilize bacterial 16S rRNA marker gene sequencing, a technique that is blind to eukaryotic organisms. Knowledge gaps exist regarding the phylogeny and microdiversity of eukaryotes that colonize hospitalized infants, as well as potential reservoirs of eukaryotes in the hospital room built environment. Results: Genome-resolved analysis of 1174 time-series fecal metagenomes from 161 premature infants revealed fungal colonization of 10 infants. Relative abundance levels reached as high as 97% and were significantly higher in the first weeks of life (p = 0.004). When fungal colonization occurred, multiple species were present more often than expected by random chance (p = 0.008). Twenty-four metagenomic samples were analyzed from hospital rooms of six different infants. Compared to floor and surface samples, hospital sinks hosted diverse and highly variable communities containing genomically novel species, including from Diptera (fly) and Rhabditida (worm) for which genomes were assembled. With the exception of Diptera and two other organisms, zygosity of the newly assembled diploid eukaryote genomes was low. Interestingly, Malassezia and Candida species were present in both room and infant gut samples. Conclusions: Increased levels of fungal co-colonization may reflect synergistic interactions or differences in infant susceptibility to fungal colonization. Discovery of eukaryotic organisms that have not been sequenced previously highlights the benefit of genome-resolved analyses, and low zygosity of assembled genomes could reflect inbreeding or strong selection imposed by room conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Synchrotron X-Ray Microdiffraction Investigation of Scaling Effects on Reliability for Through-Silicon Vias for 3-D Integration

Synchrotron x-ray microdiffraction has been applied to TSV characterization in various studies for nondestructive inspection with submicron resolution due to its high beam intensity and penetration depth. Here, the application of this technique to TSV investigations is examined and the correlation of the plastic deformation to the microstructure and extrusion behavior along with the effect of TSV dimensional scaling is examined. It is shown that the variability of the copper microstructure and resulting TSV behavior requires a larger number of samples in order to report statistically significant observations. The role of the microstructure in creating statistical scatter is demonstrated through microdiffraction measurements of grain orientation correlated with the observed peak widening, which shows that degraded TSV reliability is largely due to the high elastic anisotropy of copper. After taking the statistical variations into account, the scaling effect was clearly observed, with larger plastic deformation in 2μm diameter TSVs than in 5μm diameter TSVs consistent with microstructure variations. This is confirmed by TSV extrusion measurements, which show that the magnitude and statistical spread of the via extrusion for the 2μm diameter TSVs is higher than that of the 5μm diameter TSVs. These findings, confirmed by thermomechanical simulation, demonstrate first that large sample sizes are required in copper TSV investigations due to high variability, which is not improved with scaling.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Bright and the Slow—GRBs 100724B and 160509A with High-energy Cutoffs at ≲100 MeV

Here, we analyze the prompt emission of GRB 100724B and GRB 160509A, two of the brightest gamma-ray bursts (GRBs) observed by Fermi at ≲ MeV energies but surprisingly faint at ≳100 MeV energies. Time-resolved spectroscopy reveals a sharp high-energy cutoff at energies E c ~ 20–60 MeV for GRB 100724B and E c ~ 80–150 MeV for GRB 160509A. We first characterize phenomenologically the cutoff and its time evolution. We then fit the data to two models where the high-energy cutoff arises from intrinsic opacity to pair production within the source (τ γγ ): (i) a Band spectrum with τ γγ from the internal-shocks-motivated model of Granot et al. (2008) and (ii) the photospheric model of Gill & Thompson (2014). Alternative explanations for the cutoff, such as an intrinsic cutoff in the emitting electron energy distribution, appear to be less natural. Both models provide a good fit to the data with very reasonable physical parameters, providing an estimate of bulk Lorentz factors in the range Γ ~ 100–400, on the lower end of what is generally observed in Fermi GRBs. Surprisingly, their lower cutoff energies E c compared to other Fermi/LAT GRBs arise not only predominantly from the lower Lorentz factors, but also at a comparable level from differences in variability time, luminosity, and high-energy photon index. Lastly, particularly low E c values may prevent detection by Fermi/LAT, thus introducing a bias in the Fermi/LAT GRB sample against GRBs with low Lorentz factors or variability times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The Spectroscopic Signature of Variability in High-redshift Quasars

Using 16,421 spectra from a sample of 340 quasars (1.62 < z < 3.30) from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping Project, we present an analysis of quasar spectral variability. We confirm the intrinsic Baldwin effect (BE) and brighter-means-bluer trends in which emission line strength and color are associated with changes in luminosity. We then create a composite differential spectrum that captures the wavelength dependence of quasar variability as a function of change in luminosity. When using a bandpass around 1740 Å to describe the luminosity, the differential spectrum follows a power law at longer wavelengths that breaks blueward of 1700 Å. However, the shape of the differential spectrum, the location of the power-law break, and the slope of the intrinsic BE all vary with the choice of bandpass used to define the change in quasar luminosity. We propose that the observed behavior can be explained by inhomogeneous accretion or slim accretion disk models where delays in the reprocessing of incident light on the accretion disk cause local deviations in temperature from the thin-disk model. Finally, we quantify the effects on cosmology studies that are due to the variations in the quasar spectrum in the Lyα forest wavelength range. Using the observed spectroscopic signatures to predict the quasar continuum over the interval 1040 < λ < 1200 Å, we find that the derived spectral templates can reduce the uncertainty of the Lyα forest continuum level in individual epochs from 17.2% to 7.7%, near the level where systematic errors in SDSS flux calibration are expected to dominate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

54 ENVIRONMENTAL SCIENCES↗