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At least 775 records · Page 43

Duality between ( 2 + 1 ) d quantum critical points

We describe the simulated data sample for the “Photometric LSST Astronomical Time Series Classi-fication Challenge” (PLAsTiCC), a publicly available challenge to classify transient and variable eventsthat will be observed by the Large Synoptic Survey Telescope (LSST), a new facility expected tostart in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to 2018December 17, and included 1,094 teams competing for prizes. Here we provide details of the 18 tran-sient and variable source models, which were not revealed until after the challenge, and release themodel libraries athttps://doi.org/10.5281/zenodo.2612896. We describe the LSST OperationsSimulator used to predict realistic observing conditions, and we describe the publicly availableSNANAsimulation code used to transform the models into observed fluxes and uncertainties in the LSSTpassbands (ugrizy). AlthoughPLAsTiCChas finished, the publicly available models and simulationtools are being used within the astronomy community to further improve classification, and to studycontamination in photometrically identified samples of type Ia supernova used to measure propertiesof dark energy. Our simulation framework will continue serving as a platform to improve thePLAsTiCCmodels, and to develop new models.

Senthil, T.↗

Bacterial Biogeography across the Amazon River-Ocean Continuum

Spatial and temporal patterns in microbial biodiversity across the Amazon river-ocean continuum were investigated along ~675 km of the lower Amazon River mainstem, in the Tapajos River tributary, and in the plume and coastal ocean during low and high river discharge using amplicon sequencing of 16S rRNA genes in whole water and size-fractionated samples (0.2-2.0 μm and >2.0 μm). River communities varied among tributaries, but mainstem communities were spatially homogeneous and tracked seasonal changes in river discharge and co-varying factors. Co-occurrence network analysis identified strongly interconnected river assemblages during high (May) and low (December) discharge periods, and weakly interconnected transitional assemblages in September, suggesting that this system supports two seasonal microbial communities linked to river discharge. In contrast, plume communities showed little seasonal differences and instead varied spatially tracking salinity. However, salinity explained only a small fraction of community variability, and plume communities in blooms of diatom-diazotroph assemblages were strikingly different than those in other high salinity plume samples. This suggests that while salinity physically structures plumes through buoyancy and mixing, the composition of plume-specific communities is controlled by other factors including nutrients, phytoplankton community composition, and dissolved organic matter chemistry. Co-occurrence networks identified interconnected assemblages associated with the highly productive low salinity nearshore region, diatom-diazotroph blooms, and the plume edge region, and weakly interconnected assemblages in high salinity regions. This suggests that the plume supports a transitional community influenced by immigration of ocean bacteria from the plume edge, and by species sorting as these communities adapt to local environmental conditions. Few studies have explored patterns of microbial diversity in tropical rivers and coastal oceans. Comparison of Amazon continuum microbial communities to those from temperate and arctic systems suggest that river discharge and salinity are master variables structuring a range of environmental conditions that control bacterial communities across the river-ocean continuum.

58 GEOSCIENCES↗

TROPOS pyranometer network (PyrNet) observational data set collected during the S2VSR field campaign

During the Small-Scale Variability of Solar Radiation field campaign (S2VSR), a unique sensor network consisting of 60 autonomous pyranometer stations was deployed for a 12-week period at the ARM Southern Great Plains observatory. Stations have been distributed across a 4x4 to 6x6 km2 domain surrounding the Central Facility. Each station has recorded global radiation together with air temperature and relative humidity with a sampling frequency of 1-Hz. The network has provided a data set with an unprecedented level of detail of the small-scale variability of global solar radiation at the surface, resolving fluctuations down to the second- and decameter-scale.

54 ENVIRONMENTAL SCIENCES↗

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design↗

Considerations for imaging thick, low contrast, and beam sensitive samples with liquid cell transmission electron microscopy

Transmission electron microscopy of whole cells is hindered by the inherently large thickness and low atomic contrast intrinsic of cellular material. Liquid cell transmission electron microscopy, allows samples to remain in their native hydrated state and may permit visualizing cellular dynamics in-situ. However, imaging biological cells with this approach remains challenging and identifying an optimal imaging regime using empirical data would help foster new advancements in the field. Recent questions about the role of the electron beam inducing morphological changes or damaging cellular structure and function necessitates further investigation of electron beam-cell interactions, but is complicated by variability in imaging techniques used across various studies currently present in literature. The necessity for using low electron fluxes for imaging biological samples requires finding an imaging strategy which produces the strongest contrast and signal to noise ratio for the electron flux used. Here, we experimentally measure and evaluate signal to noise ratios and damage mechanisms between liquid and cryogenic samples for cells using multiple electron imaging modalities all on the same instrument and with equivalent beam parameters to standardize the comparison. We also discuss considerations for optimal electron microscopy imaging conditions for future studies on whole cells within liquid environments.

Moser, Trevor H. (ORCID:0000000193990514)↗

New Clues to the Evolution of Dwarf Carbon Stars From Their Variability and X-Ray Emission

As main-sequence stars with C > O, dwarf carbon (dC) stars are never born alone but inherit carbon-enriched material from a former asymptotic giant branch (AGB) companion. In contrast to M dwarfs in post-mass-transfer binaries, C 2 and/or CN molecular bands allow dCs to be identified with modest-resolution optical spectroscopy, even after the AGB remnant has cooled beyond detectability. Accretion of substantial material from the AGB stars should spin up the dCs, potentially causing a rejuvenation of activity detectable in X-rays. Indeed, a few dozen dCs have recently been found to have photometric variability with periods under a day. However, most of those are likely post-common-envelope binaries, spin–orbit locked by tidal forces, rather than solely spun-up by accretion. Here, we study the X-ray properties of a sample of the five nearest-known dCs with Chandra. Two are detected in X-rays, the only two for which we also detected short-period photometric variability. We suggest that the coronal activity detected so far in dCs is attributable to rapid rotation due to tidal locking in short binary orbits after a common-envelope phase, late in the thermally pulsing (TP) phase of the former C-AGB primary (TP-AGB).

79 ASTRONOMY AND ASTROPHYSICS↗

Explosive Byproduct Gas Transport Through Sorptive Geomedia

Current underground nuclear explosion (UNE) detection strategies rely heavily on atmospheric noble gas sampling of radioxenon. However, discriminating nuclear weapons testing programs from civilian sources is difficult due to highly variable atmospheric radioxenon backgrounds and processes affecting subsurface transport of parent radionuclides. Here, we aim to study the transport of gases produced by subsurface explosions as novel stable signatures for underground nuclear explosion (UNE) monitoring. These gases may be produced in large quantities with distinct molecular ratios, which will be impacted by subsurface transport processes. To demonstrate how ratios of gases produced by explosions can change during transport in geomaterials, we conducted laboratory benchtop experiments on the transport of carbon dioxide (CO 2 ) and hydrogen (H 2 ) gases through variably saturated zeolitic tuff, which is abundant at the historic US testing site. We observed that zeolitic tuff sorbs substantial quantities of CO 2 while allowing H 2 to transport more freely, leading to changes in the molecular ratios of the two gases along the transport pathway. Gas uptake in the dry zeolitic tuff core was 72.3% for CO 2 , compared with 53.4% for xenon and 7.6% for H 2 . The presence of 20% water saturation disrupted the CO 2 sorption process, though to a lesser extent than observed for noble gases, with a 36.7% drop in xenon sorption compared with a 21.9% drop for CO 2 . These results represent the first observations of zeolite sorption altering explosive gas ratios during transport through geomedia relevant to nuclear proliferation monitoring.

54 ENVIRONMENTAL SCIENCES↗

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Initial assessment of second generation of large-area picosecond photodetectors with multi-channel systems-on-a-chip readout

Here, we first briefly describe the history and motivation behind Cherenkov and scintillation light detection. We then discuss the instrumentation needed to detect these photons as it applies to both photodetectors and readout electronics. One of the motivations is future large neutrino detectors that could, in principle, differentiate between Cherenkov and scintillation light if using novel water-based scintillators. In this paper, we present the first measurements utilizing the second generation of Large Area Picosecond Photodetectors (LAPPDs) in conjunction with commercial system-on-a-chip readouts from Nalu Scientific—in particular, the High Density System on Chip (HDSoC) and Advanced ASoC Rapid Digitizer, Variable Adaptive Readout Chip (AARDVARC) platforms. These state-of-the-art full-waveform digitizers feature sampling rates on the order of 1 and 10 samples per nanosecond, respectively. Using a picosecond laser, we measured the timing jitter between a pair of LAPPD channels, demonstrating the potential of this setup for precise timing applications.

Li, V. A. [Lawrence Livermore National Laboratory ↗

Evaluating the impact of anatomical and physiological variability on human equivalent doses using PBPK models

Abstract Addressing human anatomical and physiological variability is a crucial component of human health risk assessment of chemicals. Experts have recommended probabilistic chemical risk assessment paradigms in which distributional adjustment factors are used to account for various sources of uncertainty and variability, including variability in the pharmacokinetic behavior of a given substance in different humans. In practice, convenient assumptions about the distribution forms of adjustment factors and human equivalent doses (HEDs) are often used. Parameters such as tissue volumes and blood flows are likewise often assumed to be lognormally or normally distributed without evaluating empirical data for consistency with these forms. In this work, we performed dosimetric extrapolations using physiologically based pharmacokinetic (PBPK) models for dichloromethane (DCM) and chloroform that incorporate uncertainty and variability to determine if the HEDs associated with such extrapolations are approximately lognormal and how they depend on the underlying distribution shapes chosen to represent model parameters. We accounted for uncertainty and variability in PBPK model parameters by randomly drawing their values from a variety of distribution types. We then performed reverse dosimetry to calculate HEDs based on animal points of departure for each set of sampled parameters. Corresponding samples of HEDs were tested to determine the impact of input parameter distributions on their central tendencies, extreme percentiles, and degree of conformance to lognormality. This work demonstrates that the measurable attributes of human variability should be considered more carefully and that generalized assumptions about parameter distribution shapes may lead to inaccurate estimates of extreme percentiles of HEDs.

Toxicology↗

Surface Solar Irradiance in Continental Shallow Cumulus Fields: Observations and Large-Eddy Simulation

This study examines shallow cumulus cloud fields and their surface shortwave radiative effects using large-eddy simulation (LES) along with observations across multiple days at the Atmospheric Radiation Measurement Southern Great Plains atmospheric observatory. Pronounced differences are found between probability density functions (PDFs) of downwelling surface solar irradiance derived from observations and LES one-dimensional (1D) online radiation calculations. The shape of the observed PDF is bimodal, which is only reproduced by offline three-dimensional (3D) radiative transfer calculations, demonstrating PDF bimodality as a 3D radiative signature of continental shallow cumuli. Local differences between 3D and 1D radiative transfer calculations of downwelling surface solar irradiance are, on average, larger than 150 W m -2 on one afternoon. The differences are substantially reduced when spatially averaged over the LES domain and temporally averaged over the diurnal cycle, but systematic 3D biases ranging from 2 to 8 W m -2 persist across different days. Covariations between the domain-averaged surface irradiance, framed as a surface cloud radiative effect, and the simulated cloud fraction are found to follow a consistent diurnal relationship, often exhibiting hysteresis. In contrast, observations show highly variable behavior. By subsampling the LES domain, it is shown that this is due to the limited sampling density of inherently 3D observations. These findings help to define observational requirements for detecting such relationships, provide valuable insight for evaluating weather and climate models against surface observations as they push to ever higher resolutions, and have important implications for future assessments of solar renewable energy potential.

54 ENVIRONMENTAL SCIENCES↗

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗

Digital Rock Physics and 3D Printing for Fractured Porous Media

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. Here we report on our research exploring the possibilities that these technologies can bring to geosciences for coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens.

42 ENGINEERING↗

RASA Field Performance at US International Monitoring Stations

This report attempts to collate, analyze, and summarize RASA performance over time at each of 11 US operated IMS stations. The performance over time was compared to routine maintenance operations. The data, in general, were summarized into a set analyzed almost exclusively in Excel. The data set allows for further probing into RASA performance over time. The data set would permit data to be routinely added for continued analysis. In general, all RASA systems ran within the CTBTO mandated the MDA requirements over their current lifetime of operations. The largest impacts to performance appeared to arise from variabilities of Germanium gamma detectors as they were replaced. It is noted that the air volumes of samples were not provided and had to be assumed to be constant over the period analyzed.

61 RADIATION PROTECTION AND DOSIMETRY↗

Nickel Binding to the c-Src SH3 Domain Facilitates Crystallization

Introduction: Numerous X-ray crystal structures of the c-Src SH3 domain have provideda large sampling of atomic-level information for this important signaling domain. Multiple crystalforms have been reported, with variable crystal lattice contacts and chemical crystallizationconditions. Materials and Methods: We crystallized the c-Src SH3 domain in a crystallization buffercontaining NiCl2. Results: A unique crystal structure of the Src SH3 domain in the trigonal space group H32 isdetermined to 1.45 Å resolution. Crystal packing and anomalous scattering reveal that this crystalform is mediated by two ordered nickel ions provided by the crystallization buffer. Nickelcoordination occurs in a 2:2 stoichiometry, which dimerizes two SH3 domain monomers across apseudo-twofold rotation axis and involves the native N-terminal c-Src SH3 amino acid sequence, asurface-exposed histidine residue, and ordered water molecules. Discussion: This study provides an example of metal-mediated crystallization and metal binding byN-terminal protein residues, contrasting with the Amino-Terminal Copper and Nickel Binding(ATCUN) motif. Conclusion: Alternative avenues help widen the potential for future crystallography-based studiesof the c-Src SH3 domain.

Biochemistry & Molecular Biology↗

Recovering the effects of subgrid heterogeneity in simulations of radionuclide transport through fractured media

Groundwater flow and contaminant transport through fractured media can be simulated using Discrete Fracture Network (DFN) models which provide a natural description of structural heterogeneity. However, this approach is computationally expensive, with the large number of intersecting fractures necessitated by many real-world applications requiring modeling simplifications to be made for calculations to be tractable. Upscaling methods commonly used for this purpose can result in some loss of local-scale variability in the groundwater flow velocity field, resulting in underestimation of particle travel times, transport resistance and retention in transport calculations. In this paper, a transport downscaling algorithm to recover the transport effects of heterogeneity is tested on a synthetic Brittle Fault Zone model, motivated by the problem of large safety assessment calculations for geological repositories of spent nuclear fuel. We show that the variability in the local-scale velocity field which is lost by upscaling can be recovered by sampling from a library of DFN transport paths, accurately reproducing DFN transport statistic distributions and radionuclide breakthrough curves in an upscaled model.

54 ENVIRONMENTAL SCIENCES↗

A NanoSIMS 50 L Investigation into Improving the Precision and Accuracy of the 235U/238U Ratio Determination by Using the Molecular 235U16O and 238U16O Secondary Ions

A NanoSIMS 50 L was used to study the relationship between the 235U/238U atomic and 235U16O/238U16O molecular uranium isotope ratios determined from a variety of uranium compounds (UO2, UO2F2, UO3, UO2(NO3)2·6(H2O), and UF4) and silicates (NIST-610 glass and the Plesovice zircon reference materials, both containing µg/g uranium). Because there is typically a greater abundance of 235U16O+ and 238U16O+ molecular secondary ions than 235U+ and 238U+ atomic ions when uranium-bearing materials are sputtered with an oxygen primary ion beam, the goal was to understand whether use of 235U16O/238U16O has the potential for improved accuracy and precision when compared to the 235U/238U ratio. The UO2 and silicate reference materials showed the greatest potential for improved accuracy and precision through use of the 235U16O/238U16O ratio as compared to the 235U/238U ratio. For the UO2, which was investigated at a variety of primary beam currents, and the silicate reference materials, which were only investigated using a single primary beam current, this improvement was especially pronounced at low 235U+ count rates. In contrast, comparison of the 235U16O/238U16O ratio versus the 235U/238U ratio from the other uranium compounds clearly indicates that the 235U16O/238U16O ratio results in worse precision and accuracy. This behavior is based on the observation that the atomic (235U+ and 238U+) to molecular (235U16O+ and 238U16O+) secondary ion production rates remain internally consistent within the UO2 and silicate reference materials, whereas it is highly variable in the other uranium compounds. Efforts to understand the origin of this behavior suggest that irregular sample surface topography, and/or molecular interferences arising from the manner in which the UO2F2, UO3, UO2(NO3)2·6(H2O), and UF4 were prepared, may be a major contributing factor to the inconsistent relationship between the observed atomic and molecular secondary ion yields. Overall, the results suggest that for certain bulk compositions, use of the 235U16O/238U16O may be a viable approach to improving the precision and accuracy in situations where a relatively low 235U+ count rate is expected.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗