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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The contributions from the progenitor genomes of the mesopolyploid Brassiceae are evolutionarily distinct but functionally compatible

The members of the tribe Brassiceae share a whole-genome triplication (WGT), and one proposed model for its formation is a two-step pair of hybridizations producing hexaploid descendants. However, evidence for this model is incomplete, and the evolutionary and functional constraints that drove evolution after the hexaploidy are even less understood. Here, we report a new genome sequence of Crambe hispanica , a species sister to most sequenced Brassiceae. Using this new genome and three others that share the hexaploidy, we traced the history of gene loss after the WGT using the Polyploidy Orthology Inference Tool (POInT). We confirm the two-step formation model and infer that there was a significant temporal gap between those two allopolyploidizations, with about a third of the gene losses from the first two subgenomes occurring before the arrival of the third. We also, for the 90,000 individual genes in our study, make parental subgenome assignments, inferring, with measured uncertainty, from which of the progenitor genomes of the allohexaploidy each gene derives. We further show that each subgenome has a statistically distinguishable rate of homoeolog losses. There is little indication of functional distinction between the three subgenomes: the individual subgenomes show no patterns of functional enrichment, no excess of shared protein-protein or metabolic interactions between their members, and no biases in their likelihood of having experienced a recent selective sweep. We propose a "mix and match" model of allopolyploidy, in which subgenome origin drives homoeolog loss propensities but where genes from different subgenomes function together without difficulty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

There is a need to characterize complex materials and their dynamics under reaction conditions to accelerate materials design. Adsorbate vibrational excitations are selective to adsorbate/surface interactions and infrared (IR) spectra associated with activating adsorbate vibrational modes are accurate, capture details of most modes, and can be obtained operando. Current interpretation depends on heuristic peak assignments for simple spectra, precluding the possibility of obtaining detailed structural information. Here, we combine data-based approaches with chemistry-dependent problem formulation to develop physics-driven surrogate models that generate synthetic IR spectra from first-principles calculations. Using synthetic IR spectra of carbon monoxide on platinum, we implement multinomial regression via neural network ensembles to learn probability distributions functions (pdfs) that describe adsorption sites and quantify uncertainty. We use these pdfs to infer detailed surface microstructure from experimental spectra and extend this methodology to other systems as a first step towards characterizing complex interfaces and closing the materials gap.

Science & Technology - Other Topics↗
DOE OSTI2020

Performance of the reconstruction and identification of high-momentum muons in proton-proton collisions at $\sqrt{s} =$ 13 TeV

The CMS detector at the LHC has recorded events from proton-proton collisions, with muon momenta reaching up to 1.8 TeV in the collected dimuon samples. These high-momentum muons allow direct access to new regimes in physics beyond the standard model. Because the physics and reconstruction of these muons are different from those of their lower-momentum counterparts, this paper presents for the first time dedicated studies of efficiencies, momentum assignment, resolution, scale, and showering of very high momentum muons produced at the LHC. These studies are performed using the 2016 and 2017 data sets of proton-proton collisions at &surd;s = 13 TeV with integrated luminosities of 36.3 and 42.1 fb−1, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Land‐based climate solutions for the United States

Abstract Meeting end‐of‐century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature‐based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature‐based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the United States that illustrates the benefits of combining approaches. We assign a portion of non‐forested former cropland to bioenergy sufficient to meet projected mid‐century transportation needs, with the remainder assigned to nature‐based solutions such as reforestation. Bottom‐up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost‐effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of forest management. Results show a conservative end‐of‐century mitigation capacity of 110 (57–178) Gt CO 2 e for the U.S., ~50% higher than existing estimates that prioritize nature‐based or bioenergy solutions separately. Further research is needed to shrink uncertainties, but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis

We present an in-depth analysis of the fiber assignment incompleteness in the Dark EnergySpectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by therestricted mobility of the robotic fiber positioner in the DESI focal plane, which limits thenumber of galaxies that can be observed at the same time, especially at small angular separations.As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which,if not addressed, can severely impact the inference of cosmological parameters. We discuss themethods adopted for simulating fiber assignment on mocks and data. In particular, we introducethe fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrumcovariance adopted for the DR1 full-shape analysis. We present the mitigation techniques,organised in two classes: measurement stage and model stage. We then use high fidelity mocks as areference to quantify both the accuracy of the FFA emulator and the effectiveness of the differentmeasurement-stage mitigation techniques. This complements the studies conducted in a parallelpaper for the model-stage techniques, namely the θ-cut approach. We find that pairwiseinverse probability (PIP) weights with angular upweighting recover the “true” clustering in allthe cases considered, in both Fourier and configuration space. Notably, we present the first everpower spectrum measurement with PIP weights from real data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

In-beam 𝛾-ray spectroscopy toward the proton dripline: The curious case of 32 Ar

High-resolution in-beam 𝛾-ray spectroscopy was used to study excited states of the neutron-deficient nucleus 32 Ar populated in fast-beam induced four- and six-nucleon removal reactions from 36,38 Ca. One new 𝛾-ray transition and indications for an additional two were found, allowing for a glimpse at the level scheme beyond the 2$^{+}_{1}$ state. The nature of the new 1900⁢(4)-keV transition is discussed in the context of the known energy spectrum of the mirror nucleus 32 Si and shell-model calculations using the FSU and SDPF-M cross-shell effective interactions. Its resulting parent state at 3767⁢(5)⁢keV, more than 1.3 MeV above the proton separation energy, is tentatively assigned to have mixed 𝑠⁢𝑑-shell and 2p-2h character. It might either be the mirror of the 𝐽 𝜋 = 2$^{+}_{2}$ state of 32 Si at 4230.8⁢(8)⁢keV, but with a decay branch favoring a transition to the 2$^{+}_{2}$ over the ground state, or the mirror of the 4983.9⁢(11)-keV state with quantum numbers 0 + . Furthermore, the resulting mirror-energy differences of −473⁢(5) and −1218⁢(5)⁢keV are both sizable when compared to systematics; in the latter case the result would, in fact, be among the largest reported to date in the nuclear chart or suggest the potential existence of an additional, hitherto unidentified, low-lying 0 + state of 32 Si.

20 ≤ A ≤ 38↗
DOE OSTI2022

Crucible Melter Simulation in Nek5000

Nuclear tank waste at the Hanford site is slated for vitrification in large scale refractory-lined melters to transform it into a stable borosilicate waste form suitable for long-term storage or disposal. Molten glass corrodes the refractory lining over time at a rate correlated to the velocity of molten glass against the refractory-lined wall. To properly design a melter and plan for maintenance, it is necessary to accurately model the glass flow and find the correlation between flow velocity and corrosion rate. This modeling was started in STAR-CCM+ CFD software and is being continued in Nek5000 for its fast-running and quick turnaround code. This poster explains the basic process of reconstructing the geometry, fluid properties, and heating of test melters in Nek5000. The geometry is imported from a mesh file and boundary conditions assigned based on surface IDs. The fluid properties are set in the .par and .usr case files. The heating of the actual crucibles in joule heating with electrodes but simulated in Nek5000 with a volumetric heat source term. This volumetric heat source is fit to the actual heating profile with piecewise polynomials and exponentials. Basic results and verification methods are explained in the poster, as well as further work that must be done to complete modeling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis

We present an in-depth analysis of the fiber assignment incompleteness in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by the restricted mobility of the robotic fiber positioner in the DESI focal plane, which limits the number of galaxies that can be observed at the same time, especially at small angular separations. As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which, if not addressed, can severely impact the inference of cosmological parameters. We discuss the methods adopted for simulating fiber assignment on mocks and data. In particular, we introduce the fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrum covariance adopted for the DR1 full-shape analysis. We present the mitigation techniques, organised in two classes: measurement stage and model stage. We then use high fidelity mocks as a reference to quantify both the accuracy of the FFA emulator and the effectiveness of the different measurement-stage mitigation techniques. This complements the studies conducted in a parallel paper for the model-stage techniques, namely the θ-cut approach. We find that pairwise inverse probability (PIP) weights with angular upweighting recover the “true” clustering in all the cases considered, in both Fourier and configuration space. Notably, we present the first ever power spectrum measurement with PIP weights from real data.

cosmological simulations↗
DOE OSTI2023

Dynamics of resonant low-energy electron attachment to ethanol-producing hydroxide anions

Here, the dynamics of dissociative electron attachment to ethanol is experimentally investigated at the Feshbach resonance formed with incident electron energies near 9.5 eV. Highly differential laboratory-frame momentum distributions of OH – fragments are measured for a series of energies spanning the resonance width, using the velocity-map-imaging technique. The OH – kinetic-energy distribution indicates that the C-O breaking dissociation process could either be a three-body dissociation or a two-body dissociation with significant rovibrational excited fragments. The small, but significant, anisotropy in the OH – angular distribution provides signatures of the molecular symmetry of the associated resonant state under the axial recoil approximation, which assumes the dissociation is much faster than any rotation of the dissociation axis. Within these assumptions, the 9.5-eV Feshbach resonance can be assigned to the electronic transition from the ($10a'$) orbital with its ground-state C s symmetry to the empty ($4a''$) level, involving the simultaneous electron attachment. This dynamics could be a model for C-O dissociation in larger alcohols and ethers.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

A Southern Photometric Quasar Catalog from the Dark Energy Survey Data Release 2

We present a catalog of 1.4 million photometrically selected quasar candidates in the southern hemisphere over the ~5000 deg 2 Dark Energy Survey (DES) wide survey area. We combine optical photometry from the DES second data release (DR2) with available near-infrared (NIR) and the all-sky unWISE mid-infrared photometry in the selection. We build models of quasars, galaxies, and stars with multivariate skew-t distributions in the multidimensional space of relative fluxes as functions of redshift (or color for stars) and magnitude. Our selection algorithm assigns probabilities for quasars, galaxies, and stars and simultaneously calculates photometric redshifts (photo-z) for quasar and galaxy candidates. Benchmarking on spectroscopically confirmed objects, we successfully classify (with photometry) 94.7% of quasars, 99.3% of galaxies, and 96.3% of stars when all IR bands (NIR YJHK and WISE W1W2) are available. The classification and photo-z regression success rates decrease when fewer bands are available. Our quasar (galaxy) photo-z quality, defined as the fraction of objects with the difference between the photo-z z p and the spectroscopic redshift z s , |Δz| ≡ |z s - z p |/(1 + z s ) ≤ 0.1, is 92.2% (98.1%) when all IR bands are available, decreasing to 72.2% (90.0%) using optical DES data only. Our photometric quasar catalog achieves an estimated completeness of 89% and purity of 79% at r < 21.5 (0.68 million quasar candidates), with reduced completeness and purity at 21.5 < r ≲ 24. Among the 1.4 million quasar candidates, 87,857 have existing spectra, and 84,978 (96.7%) of them are spectroscopically confirmed quasars. Finally, we provide quasar, galaxy, and star probabilities for all (0.69 billion) photometric sources in the DES DR2 coadded photometric catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Collision avoidance based on traffic management data

A system for determining a travel direction that avoids objects when a vehicle travels from a current location to a target location is provided. The system determines a travel direction based on an attract-repel model. The system accesses external object information provided by an external object system. The external object information may include, for each of a plurality of objects, location, type, and constraint. The system assigns a repel value to the location of each object based on the type of and constraint on the object. The system assigns an attractive value to the target location. The system calculates a cumulative force based on the attractive and repulsive forces and sets the travel direction based on the cumulative force.

Beer, N. Reginald↗
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Improving qubit readout with hidden Markov models

We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit-state transitions and makes for a robust classification scheme with higher starting-state assignment fidelity than when compared to a multivariate Gaussian or a support vector machine scheme. Therefore, the method also eliminates the qubit-dependent readout time optimization requirement in current schemes. Using a HMM state discriminator we estimate fidelities reaching the ideal limit. Unsupervised learning gives access to transition matrix, priors, and IQ distributions, providing a toolbox for studying qubit-state dynamics during strong projective readout.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Observation of the near-threshold intruder 0 – resonance in 12 Be

A resonant state at $3.21^{+0.12}_{–0.04}$ MeV, located just above the one-neutron separation threshold, was observed for the first time in 12 Be from the 11 Be(d,p) 12 Be one-neutron transfer reaction in inverse kinematics. This state is assigned a spin-parity of 0 – according to the systematics of the level scheme of the N=8 isotones and decay-width analysis. Gamow coupled-channel and Gamow shell-model calculations show the importance of the continuum coupling, which dramatically influences the excitation energy and ordering of low-lying states. Various exotic structures associated with cross-shell intruding configurations in 12 Be and in its isotonic nucleus 11 Li are comparably discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Shell structure in 32P

The nuclear structure of 32P was investigated by detecting multi-γ coincidences along with charged light ions following the bombardment of an 18O target with a 30-MeV 16O beam from the Florida State University accelerator facility using the Clarion2-Trinity array of Clover γ spectrometers and GAGG (Gd-Al-Ga-garnet) scintillators for charged particles. A number of new states up to 12 MeV excitation and spins up to 9+ were observed by their γ decay patterns. Spins and parities were assigned by comparing measured γ angular distributions with polarizations inferred from Compton-scattering asymmetries between the Ge crystals in the Clover spectrometers. The new level scheme of 32P compares well with shell model calculations using the FSU cross-shell interaction and reasonably well with those using the sdpf-m interaction. In particular, structures with higher spin arise from promotion of more nucleons up to the f-p shell.

Allmond, James [ORNL] (ORCID:0000000165338721)↗
DOE OSTI2024

Reconstruction of the BNB and NuMI Neutrino Bunch Structure with ICARUS

ICARUS serves as the Far Detector of the Short Baseline Neutrino (SBN) program at Fermilab, sitting on-axis on the Booster Neutrino Beam (BNB) and 6$^\circ$ off-axis from the Neutrinos at the Main Injector (NuMI) beam. Neutrinos from both beams inherit the timing sub-structure of their parent proton spills, which is in turn derived from either the Booster's or the Main Injector's synchrotron acceleration. Since neutrino propagation introduces only a constant offset, their timing structure is preserved as they travel. Identifying this structure in data represents a powerful tool for selecting neutrino events and searching for physics beyond the Standard Model (BSM). This poster presents the preliminary reconstruction of the BNB and NuMI neutrino bunch structure with ICARUS data, exploiting only the precise timing of ICARUS optical readout system to both locate and assign a time to each interaction.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Data from: Land-based climate solutions for the United States

Meeting end-of-century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature-based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature-based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the U.S. that illustrates the benefits of combining approaches. We assign a portion of non-forested former cropland to bioenergy sufficient to meet projected mid-century transportation needs, with the remainder assigned to nature-based solutions such as reforestation. Bottom-up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost-effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of reforestation. Results show a conservative end-of-century mitigation capacity of 110 (57 – 178) Gt CO2e for the U.S., ~50% higher than existing estimates that prioritize nature-based or bioenergy solutions separately. Further research is needed to shrink uncertainties but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

09 BIOMASS FUELS↗