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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

EuAuSb: An odd-parity helical variation of altermagnetism

EuAuSb is a triangular-lattice Dirac semimetal in which a topological Hall effect has been observed to develop in association with a magnetically ordered phase. Our single-crystal neutron diffraction measurements have identified an incommensurate helical order in which individual ferromagnetic Eu 2+ layers rotate in-plane by ∼ 120° from one layer to the next. An in-plane magnetic field distorts the incommensurate order, eventually leading to a first order transition to a state that is approximately commensurate and that is continuously polarized as the bulk magnetization approaches saturation. From an analysis of the magnetic diffraction intensities versus field, we find evidence for a dip in the ordered in-plane moment at the same field where the topological Hall effect is a maximum, and we propose that this is due to field-induced quantum spin fluctuations. Our electronic structure calculations yield exchange constants compatible with the helical order and show that the bands near the Fermi level lose their spin degeneracy via a mechanism similar to that in the collinear altermagnets. In conclusion, we find that, unlike the even symmetry seen in the altermagnets, the spin splitting in EuAuSb has odd-wave symmetry similar to that recently found in a number of coplanar magnetic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Meissner-London Susceptibility of Superconducting Right Circular Cylinders in an Axial Magnetic Field

Analysis of magnetic susceptibility of nonellipsoidal samples is a long-standing problem in experimental studies of magnetism and superconductivity. Here the quantitative description of the Meissner-London response (no Abrikosov vortices) of right circular cylinders in an axial magnetic field is given. Three-dimensional adaptive finite-element modeling is used to calculate the total magnetic moment ( m ) in a wide range of London penetration depth ( λ ) to sample size ( a ) ratios, λ /a. Furthermore, by fitting numerical solutions, the closed-form empirical magnetic susceptibility is obtained involving only sample dimensions and λ, thus providing a recipe for determining the London penetration depth from the precision measurements of the magnetic susceptibility. Detailed protocols of the experimental data analysis using the developed approach are given. The results can be readily extended to the most frequently used cuboid-shaped samples.

3-dimensional systems↗
DOE OSTI2025

Constraints on f ( R ) gravity from thermal-Sunyaev-Zel’dovich-effect-selected SPT galaxy clusters and weak lensing mass calibration from DES and HST

We present constraints on the f ( R ) gravity model using a sample of 1005 galaxy clusters in the redshift range 0.25–1.78 that have been selected through the thermal Sunyaev-Zel’dovich effect from South Pole Telescope data and subjected to optical and near-infrared confirmation with the multicomponent matched filter algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey Year 3 data for 688 clusters at z < 0.95 and from the Hubble Space Telescope for 39 clusters with 0.6 < z < 1.7 . Our cluster sample is a powerful probe of f ( R ) gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semianalytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background temperature and polarization anisotropy measurements from the Planck 2018 release, we derive robust constraints on the f ( R ) parameter f R 0 . Our results, log 10 | f R 0 | < − 5.32 at the 95% credible level, are the tightest current constraints on f ( R ) gravity from cosmological scales. This upper limit rules out f ( R ) -like deviations from general relativity that result in more than a ∼ 20 % enhancement of the cluster population on mass scales M 200 c > 3 × 10 14 M ⊙ . Published by the American Physical Society 2025

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Suppression of electroconvective and morphological instabilities by an imposed cross flow of the electrolyte

Electroconvective (EC) instability and its influence on surface morphological perturbations (Morph) are important in many applications, including electrodialysis, batteries, and fuel cells. In this work, we study the effects of a two-dimensional channel flow on the EC and Morph instabilities using two approaches. In the bulk analysis, we derive the asymptotic solutions for small and large wave numbers by neglecting the space charge layer and imposing a second kind electroosmosis slip velocity boundary condition on the electroneutral bulk region. In the full analysis, the instability of the entire region of the liquid electrolyte is analyzed using the ultraspherical spectral method. Both studies show that the flow significantly affects the EC instability. The imposed flow distorts the concentration field, causing a sheltering effect which hinders the ion transport from low- to high-concentration regions, and therefore suppresses the EC instability below a certain wave number. In combination with the viscous stabilization of the high wave number modes by the space charge layer, a sufficiently strong imposed flow can fully suppress the EC instability. The increment in the critical voltage for the instability onset is roughly proportional to the square root of the product of imposed velocity and double layer thickness. The imposed flow has a smaller effect on the Morph instability, except that it may remove the morphological modes resulting from the EC instability and thereby change the wave number of the most unstable mode.

42 ENGINEERING↗
DOE OSTI2026

Computational prediction of ferromagnetic 𝐴⁢𝑇 6 ⁢𝑋 6 kagome compounds

We present a systematic high-throughput density-functional-theory investigation of the structural and magnetic stability of 312 substitutional compounds in the magnetic kagome 𝐴⁢𝑇 6⁢ 𝑋 6 family. Our screening confirms the stability of many previously reported structures and predicts several additional stable candidates. Within collinear spin configurations, we find that Fe-based systems predominantly adopt antiferromagnetic ground states, whereas Mn-based analogs exhibit a more balanced distribution between ferromagnetic and antiferromagnetic order. For compounds exhibiting several nearly degenerate collinear configurations, we analyze the nature of their magnetic ground states, assess the possible emergence of noncollinear order, and discuss the limitations and uncertainties inherent to standard density-functional approaches. Our electronic structure analysis further reveals that predicted ferromagnetic kagome systems display characteristic features of topological metals, with rich magnetic configurations that can be tuned by chemical substitution. Altogether, these ferromagnetic kagome compounds constitute a broad and still largely unexplored materials platform for the emergence of exciting magnetotransport phenomena.

Density functional calculations↗
DOE OSTI2021

Data-Driven Learning for the Mori--Zwanzig Formalism: A Generalization of the Koopman Learning Framework

A theoretical framework which unifies the conventional Mori--Zwanzig formalism and the approximate Koopman learning of deterministic dynamical systems from noiseless observation is presented. In this framework, the Mori--Zwanzig formalism, developed in statistical mechanics to tackle the hard problem of construction of reduced-order dynamics for high-dimensional dynamical systems, can be considered as a natural generalization of the Koopman description of the dynamical system. We next show that, similar to the approximate Koopman learning methods, data-driven methods can be developed for the Mori--Zwanzig formalism with Mori's linear projection operator. We have developed two algorithms to extract the key operators, the Markov and the memory kernel, using time series of a reduced set of observables in a dynamical system. We have adopted the Lorenz `96 system as a test problem and solved for the above operators. These operators exhibit complex behaviors, which are unlikely to be captured by traditional modeling approaches in Mori--Zwanzig analysis. The nontrivial generalized fluctuation-dissipation relationship, which relates the memory kernel with the two-time correlation statistics of the orthogonal dynamics, was numerically verified as a validation of the solved operators. Here we present numerical evidence that the generalized Langevin equation, a key construct in the Mori--Zwanzig formalism, is more advantageous in predicting the evolution of the reduced set of observables than the conventional approximate Koopman operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Coreii - Scout

COREII Scout employs React, Vite, TypeScript, Tailwind, and Daisy UI for its graphical user interface (GUI), offering both dark and light modes. The code is modular, with components and reusable wrappers to enhance efficiency. The primary goal of COREII Scout is to aid analysts in collecting and analyzing various sources related to cyber attacks, utilizing models to automate the report writing process. It uses Named Entity Recognition (NER), a type of Natural Language Processing (NLP), to extract key entities from each source. Analysts review and classify these entities using the COREII Attack Chain Estimator (ACE), adding their comments. Ultimately, a Large Language Model (LLM) generates a detailed report with user guidance. This setup ensures a streamlined and effective approach to cyber attack analysis and reporting.

Pluth, Adam [Idaho National Laboratory (INL), Idah↗
DOE OSTI2021

Prebiotic properties of Bacillus coagulans MA-13: production of galactoside hydrolyzing enzymes and characterization of the transglycosylation properties of a GH42 β-galactosidase

The spore-forming lactic acid bacterium Bacillus coagulans MA-13 has been isolated from canned beans manufacturing and successfully employed for the sustainable production of lactic acid from lignocellulosic biomass. Among lactic acid bacteria, B. coagulans strains are generally recognized as safe (GRAS) for human consumption. Low-cost microbial production of industrially valuable products such as lactic acid and various enzymes devoted to the hydrolysis of oligosaccharides and lactose, is of great importance to the food industry. Specifically, α- and β-galactosidases are attractive for their ability to hydrolyze not-digestible galactosides present in the food matrix as well as in the human gastrointestinal tract. In this work we have explored the potential of B. coagulans MA-13 as a source of metabolites and enzymes to improve the digestibility and the nutritional value of food. A combination of mass spectrometry analysis with conventional biochemical approaches has been employed to unveil the intra- and extra- cellular glycosyl hydrolase (GH) repertoire of B. coagulans MA-13 under diverse growth conditions. The highest enzymatic activity was detected on β-1,4 and α-1,6-glycosidic linkages and the enzymes responsible for these activities were unambiguously identified as β-galactosidase (GH42) and α-galactosidase (GH36), respectively. Whilst the former has been found only in the cytosol, the latter is localized also extracellularly. The export of this enzyme may occur through a not yet identified secretion mechanism, since a typical signal peptide is missing in the α-galactosidase sequence. A full biochemical characterization of the recombinant β-galactosidase has been carried out and the ability of this enzyme to perform homo- and hetero-condensation reactions to produce galacto-oligosaccharides, has been demonstrated. Probiotics which are safe for human use and are capable of producing high levels of both α-galactosidase and β-galactosidase are of great importance to the food industry. In this work we have proven the ability of B. coagulans MA-13 to over-produce these two enzymes thus paving the way for its potential use in treatment of gastrointestinal diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The precession frequency measurement in the Muon $g - 2$ experiment at Fermilab

The Muon g-2 (E989) experiment aims to reduce the uncertainty on the muon magnetic anomaly value (aμ = g-22 ) by a factor four (0.14 ppm) compared to the previous experiment at Brookhaven National Laboratory (BNL) in order to clarify the difference (now greater than 3 σ) between the experimental value and the Standard Model (SM) prediction. E989 collected a dataset with the same statistical power of the BNL experiment during the Run 1 data taking (2018). The analysis of data is approaching the final stage and the first result should become available in2021. In this paper, I will briefly describe the experimental setup and discuss the measure of the muon’s spin anomalous precession frequency.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

The DPG Method for the Convection-Reaction Problem, Revisited

In this work, we study both conforming and non-conforming versions of the practical DPG method for the convection-reaction problem. We determine that the most common approach for DPG stability analysis – construction of a local Fortin operator – is infeasible for the convection-reaction problem. We then develop a line of argument based on a direct proof of discrete stability; we find that employing a polynomial enrichment for the test space does not suffice for this purpose, motivating the introduction of a (two-element) subgrid mesh. The argument combines mathematical analysis with numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Models, data, and scripts associated with “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning”

This data package is associated with the publication “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning’’ submitted to the Journal of Geophysical Research: Machine Learning and Computation (Scheibe et al. 2024). River sediment respiration observations are expensive and labor intensive to obtain and there is no physical model for predicting this quantity. The Worldwide Hydrobiogeochemisty Observation Network for Dynamic River Systems (WHONDRS) observational data set (Goldman et al.; 2020) is used to train machine learning (ML) models to predict respiration rates at unsampled sites. This repository archives training data, ML models, predictions, and model evaluation results for the purposes of reproducibility of the results in the associated manuscript and community reuse of the ML models trained in this project. One of the key challenges in this work was to find an optimum configuration for machine learning models to work with this feature-rich (i.e. 100+ possible input variables) data set. Here, we used a two-tiered approach to managing the analysis of this complex data set: 1) a stacked ensemble of ML models that can automatically optimize hyperparameters to accelerate the process of model selection and tuning and 2) feature permutation importance to iteratively select the most important features (i.e. inputs) to the ML models. The major elements of this ML workflow are modular, portable, open, and cloud-based, thus making this implementation a potential template for other applications. This data package is associated with the GitHub repository found at Please see the file level metadata (flmd; “sl-archive-whondrs_flmd.csv”) for a list of all files contained in this data package and descriptions for each. Please see the data dictionary (dd; “sl-archive-whondrs_dd.csv”) for a list of all column headers contained within comma separated value (csv) files in this data package and descriptions for each. The GitHub repository is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning models trained on the data in “input_data”; (3) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; (4) “examples” contains the visualization of the results in this repository including plotting scripts for the manuscript (e.g., model evaluation, FPI results) and scripts for running predictions with the ML models (i.e., reusing the trained ML models); (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. Furthermore, depending on the number of features used to train the ML models, the preprocessing and postprocessing scripts, and their intermediate results, can also be different branch-to-branch. The “main-*” branches are meant to be starting points (i.e. trunks) for each model branch (i.e. sprouts). Please see the Branch Navigation section in the top-level README.md in the GitHub repository for more details. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please the top-level README.md in the GitHub repository for more details on the automation.

13C↗
DOE OSTI2020

Preliminary description of a new creep-fatigue design method that reduces over conservatism and simplifies the high temperature design process

The report provides the initial description of a new creep-fatigue design method for structural components in high temperature nuclear service. The new method is based on an integrated elastic-perfectly plastic (EPP) analysis and Simplified Model Test (SMT) approach that reduces over conservatism, improves the treatment of elastic follow up, and simplifies the design procedure, when compared with the current creep-fatigue design methods in ASME Boiler and Pressure Vessel Code. Developing the design charts for the EPP-SMT design method requires extrapolating SMT test data as a function of hold time and follow up factor. The report develops the preliminary design charts for Alloy 617 at temperatures between 800°C and 950°C by combining two extrapolation approaches developed in a previous work. The report also presents a comparative analysis between the EPP-SMT design method and the current ASME creep-fatigue design methods by evaluating design life of two sample geometries under different loading conditions. Results from the comparative analysis verify the EPP-SMT design charts but suggest the requirement of additional test data in the low strain range regime for improving the extrapolation procedure that will further reduce the over conservatism in the creep-fatigue damage evaluation. The report also concludes that the EPP-SMT design procedure can account for effect of primary load on creep-fatigue life by using a fixed, bounding value of follow up in constructing the design charts. The conclusions to this report describe the future work required to complete this new design method so it can be codified through a nuclear Code Case.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

The DPG Method for the Convection-Reaction Problem Revisited

We study both conforming and non-conforming versions of the practical DPG method for the convection-reaction problem. We determine that the most common approach for DPG stability analysis (construction of a local Fortin operator) is infeasible for the convection-reaction problem. We then develop a line of argument based on the direct construction of a global Fortin operator; we find that employing a polynomial enrichment for the test space does not suffice for this purpose, motivating the introduction of a (two-element) subgrid mesh. The argument combines mathematical analysis with numerical experiments

42 ENGINEERING↗
DOE OSTI2023

Status of Multiphysics Modeling of Critical DPCs in a Geological Repository

A summary of previous work focused on the first two scenarios is presented as an established workflow. These canisters could reach an equilibrium at a low quasi–steady-state power level that could be sustained for thousands of years. The majority of this report describes an effort to expand the initial methodology to include the scenario in which a DPC has enough excess reactivity to boil the water inside the canister. This scenario involves a variety of tools and modeling approaches to capture the two-phase behavior, including RELAP5-3D, STAR-CCM+, and TRACE. Efforts using the high-fidelity computational fluid dynamics results to verify the accuracy of RELAP5-3D and TRACE for boiling DPCs are also presented. A new modeling strategy using TRACE appears to be the most promising approach for expanding the analysis of critical DPCs beyond the subcooled scenarios. Finally, this report describes ongoing work investigating the fourth scenario, in which a critical DPC is sealed in saturated bentonite. The primary goal in this research is to understand the power output and associated pressure increase to inform geomechanics simulations that could predict the impact on a geological repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Determination of Neutrino Oscillation Parameters through the Feldman-Cousins Method by the NOvA Experiment

The NOvA experiment presents new measurements of the neutrino oscillation parameters obtained through a fit to data from the one megawatt NuMI neutrino beam in the NOvA detectors. The analysis uses muon-neutrino disappearance and electron-neutrino appearance in both neutrino and antineutrino beam polarities. With the addition of $\sim$ 100%\) more neutrino-mode beam exposure over the previously reported results, this analysis employs the unified approach of Feldman and Cousins to determine the confidence level intervals for the oscillation parameters $\theta_{23}, \delta_{CP}$, and $\Delta m_{32}^2$ for both neutrino mass orderings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Optimization of the artificial viscosity in Lagrangian staggered discretization codes. Modeling 1D stand-alone shock - case study

We have developed new measures of errors for numerical shock. The new approach is based on analysis of the structure function, and separation of the errors related to oscillations and shock width, which also include error in the position of the ”center” of the numerical shock. We have demonstrated that those measures correctly characterize the numerical solution. We introduced an objective function in, which both types of errors are weighted, and presented optimal values of the coefficients of the linear and quadratic viscosity for different weights and different Mach numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Latest Three-Flavor Neutrino Oscillation Results from NOvA

NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It aims to constrain neutrino oscillation parameters by analyzing $\nu_\mu (\bar{\nu}_\mu)$ disappearance and $\nu_e (\bar{\nu}_e)$ appearance data. The experiment uses the Neutrinos at Main Injector (NuMI) beamline at Fermilab, which delivers a high-purity 900 KW beam of neutrinos and anti-neutrinos. The detectors are functionally identical finely granulated liquid tracking calorimeters, both situated 14.6 mrad off-axis to the beam direction. The NOvA Near Detector (ND), situated 100 meters underground and 1 kilometer from the beam source, detects the un-oscillated $\nu_\mu (\bar{\nu}_\mu)$ and beam $\nu_e (\bar{\nu}_e)$ events. The Far Detector (FD), located in Ash River, MN, USA, 809 kilometers from the ND, records the oscillated $\nu_e (\bar{\nu}_e)$ and the un-oscillated $\nu_\mu (\bar{\nu}_\mu)$ events. NOvA employs an extrapolation technique to predict the expected events at the Far Detector based on the Near Detector data, thereby providing a significant constraint on systematic uncertainties in the oscillation analyses. As NOvA accumulates more data, controlling these systematic uncertainties becomes increasingly important. This talk will detail the NOvA neutrino oscillation analysis framework and its approach to minimizing dominant systematic uncertainties using Near Detector data. The latest three flavor neutrino oscillation results based on a neutrino-beam exposure of $26.60 \times 10^{20}$ POT and an anti-neutrino beam exposure of $12.50\times 10^{20}$ POT and a novel low energy $\nu_e$ sample, will also be presented.

Choudhary, Brajesh↗