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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MARIE: A Python-Based Framework for Comprehensive Fuel Recycling Modeling

One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery of valuable materials from UNF assemblies has been considered as part of an overall strategy for minimization of the volume of reactor-based wastes to be managed, the deployment of commercial-scale reprocessing facilities presents an enormous economic challenge. The MARIE software package has been developed as a means of confronting this challenge. Representing components of a generic fuel reprocessing operation as individual physical processes, MARIE is designed as a modular framework intended to allow for analysis and cost-optimization for a hypothetical reprocessing facility while realistically accounting for the physical characteristics of the used fuel source term, such as decay heat, activity, and radiation dose (informing corresponding shielding requirements). Capabilities supported by MARIE include head-end operations such as fuel shearing, voloxidation, and dissolution; generic solvent extraction operations informed by available open-literature data; a suite of unit operations intended to represent electrochemical processing of used fuel assemblies (i.e., oxide reduction, electrorefining, and electrowinning); and finally, accounting for both costs and physical features of discharged waste streams, which can be used to inform follow-on analyses such as the feasibility of deep-borehole disposal of HLW. This paper presents an overview of the MARIE software capabilities, including how individual unit operations are implemented to enable a larger-scale optimization of a hypothetical reprocessing operation on aspects such as cost and recovery of valuable materials.

Skutnik, Steve [ORNL] (ORCID:000000016441135X)↗
DOE OSTI2023

Model selection and signal extraction using Gaussian Process regression

We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Factors that impact the outcomes in testicular germ cell tumors in low–middle-income countries

Germ cell tumors (GCTs) are one of the most common tumors in adolescents and young adults. There is paucity of data on GCT from low–middle-income countries (LMIC). The present study was conducted to assess the demographic features, clinical manifestations, pathology, and outcomes of GCT patients treated at our center. Patients with testicular GCT above the age of 18 years, treated at our center from 2001 to 2015 were included in the study. Data were extracted retrospectively from the case records. Event-free survival (EFS) and overall survival (OS) were calculated using the Kaplan–Meier method and the variables were compared using the log-rank test. The study included 421 patients among whom 128 (30%) had a histological diagnosis of seminoma and 293 (70%) had non-seminomatous germ cell tumor (NSGCT). Metastatic disease at presentation was observed in 83/128 (65%) with seminoma and 254/293 (87%) with NSGCT. According to the International Germ Cell Cancer Collaborative Group (IGCCCG) risk stratification for metastatic disease, good- and intermediate-risk seminoma were observed in 55/83 (66%) and 28/83 (34%) patients, respectively, and good-, intermediate-, and poor-risk NSGCT were observed in 82/254 (32%), 76/254 (30%), and 96/254 (38%) patients, respectively. The median follow-up was 32.3 months (range 0.03–200 months). The 3-year OS for the entire cohort was 80.3%. The 3-year OS for seminoma was 91.4%, and for NSGCT was 75.3%. Factors significantly associated with inferior EFS and OS on multivariate analysis included poor performance status, scrotal orchidectomy, carboplatin-based regimen, NSGCT histology, and treatment default. Patients with testicular GCT in India present in an advanced stage and higher IGCCCG risk compared to Western data. Factors unique to LMIC like treatment default, bulky disease, dose compromise, and scrotal orchidectomy have a negative impact on the outcome.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗
DOE OSTI2022

Spin-exchange Hamiltonian and topological degeneracies in elemental gadolinium

In this report we present a comprehensive study of the magnetic exchange Hamiltonian of elemental gadolinium. We use neutron scattering to measure the magnon spectrum over the entire Brillouin zone and fit the excitations to a spin wave model to extract the first 26 nearest-neighbor magnetic exchange interactions with rigorously defined uncertainty. We find these exchange interactions to follow RKKY behavior, oscillating from ferromagnetic to antiferromagnetic as a function of distance. Finally, we discuss the topological features and degeneracies in Gd, and HCP ferromagnets in general. We show theoretically how, with asymmetric exchange, topological properties could be tuned with a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Coherent elastic neutrino-nucleus scattering with directional detectors

We study the sensitivity of detectors with directional sensitivity to coherent elastic neutrino-nucleus scattering (CE$\textit{ν}$NS), and how these detectors complement measurements of the nuclear recoil energy. In this work we consider stopped pion and reactor neutrino sources, and use gaseous helium and fluorine as examples of detector material. We generate Standard Model predictions, and compare to scenarios that include new, light vector or scalar mediators. We show that directional detectors can provide valuable additional information in discerning new physics, and we identify prominent spectral features in both the angular and the recoil energy spectrum for light mediators, even for nuclear recoil energy thresholds as high as ~50 keV. Combined with energy and timing information, directional information can play an important role in extracting new physics from CE$\textit{ν}$NS experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Identification of Dynamic Force Coefficients for an Additively Manufactured Hermetic Squeeze Film Bearing Support Damper Utilizing a Pass-Through Channel

Abstract The following paper presents breakthrough experimental results for a new hermetic squeeze film damper (HSFD) concept that is integrally designed within an externally pressurized tilting-pad radial gas bearing support. The flexibly damped gas bearing module was designed for a 7.2″ (183 mm) diameter shaft and fabricated using direct metal laser melting (DMLM); also known as additive manufacturing. The bearing and HSFD were sized based on ongoing studies for oil-free supercritical carbon dioxide (sCO2) power turbines in the 8.5 MW–10 MW power range. The development of the new damper concept was motivated by past dynamic testing on HSFD, which generated frequency-dependent stiffness and damping force coefficients. In efforts to eliminate the frequency dependency, a new HSFD architecture was conceived that adds accumulator volumes and a pass-through channel to previously conceived HSFD flow network designs. The other motivation for the work is the need to develop a cost-effective and reliable oil-free bearing technology that is scalable to large power turbomachinery applications. There were several objectives for the following work. The first objective was to successfully design and fabricate a single piece bearing-damper using additive manufacturing, while dimensionally controlling critical design features. The paper discusses the manufacturing steps and shows cut-ups that reveal adequate clearance control capability with internal damper clearances. The second objective was to perform experimental testing with the new HSFD design in efforts to extract stiffness and damping coefficients for excitation frequencies within 20–160 Hz and peak vibration amplitudes between 0.25 mils (6.35 microns) to 1 mil (25.4 microns). The test results for a single HSFD bearing module indicated that the design modifications to the HSFD architecture were successful in eliminating nearly all the frequency dependencies for the stiffness force coefficient. The dynamic tests yielded a stiffness coefficient that varied between 112 klb/in. (19.6 MN/m) and 96 klb/in. (16.8 MN/m). The damping force coefficient however, exhibited relatively more variation with frequency with values residing between 175 lb-s/in. (31 kN-s/m) to 214 lb-s/in. (37 kN-s/m). Finally, the paper advances a three-dimensional fluid-structure interaction (FSI) model using transient finite element analysis (FEA) coupled to a computational fluid dynamics (CFD) model. The FSI analysis performed between 20 Hz and 80 Hz was used to predict the stiffness and damping of the HSFD using a quarter-section model of the damper. The FSI analysis was able to support test results by showing only a 6–7.4% change in the magnitude of force coefficients. Stiffness predictions agree reasonably well with experiments whereas damping is underpredicted.

Engineering↗
DOE OSTI2021

Laser-Induced Recoverable Fluorescence Quenching of Perovskite Films at a Microscopic Grain Scale

Understanding the fundamental properties of metal-halide perovskite materials is driving the development of novel optoelectronic applications. Here, in this paper, we report the observation of a recoverable laser-induced fluorescence quenching phenomenon in perovskite films with a microscopic grain-scale restriction, accompanied by spectral variations. This fluorescence quenching depends on the laser intensity and the dwell time under Auger recombination dominated conditions. These features indicate that the perovskite lattice deformation may take the main responsibility for the transient and show a new aspect to understand halide perovskite photo-stability. We further modulate this phenomenon by adjusting the charge carrier recombination and extraction, revealing that efficient carrier transfer can improve the bleaching resistance of perovskite grains. Our results provide future opportunities to attain high-performance devices by tuning the perovskite lattice disorder and harvesting the energetic carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Baryonic imprints on DM haloes: the concentration–mass relation in the C amels simulations

ABSTRACT The physics of baryons in haloes, and their subsequent influence on the total matter phase space, has a rich phenomenology and must be well understood in order to pursue a vast set of questions in both cosmology and astrophysics. We use the Cosmology and Astrophysics with MachinE Learning Simulation (Camels) suite to quantify the impact of four different galaxy formation parameters/processes (as well as two cosmological parameters) on the concentration–mass relation, cvir−Mvir. We construct a simulation-informed non-linear model for concentration as a function of halo mass, redshift, and six cosmological/astrophysical parameters. This is done for two galaxy formation models, IllustrisTNG and Simba, using 1000 simulations of each. We extract the imprints of galaxy formation across a wide range in mass $M_{\rm vir}\in [10^{11}, 10^{14.5}] \, {\rm M}_\odot \, h^{-1}$ and in redshift z ∈ [0, 6] finding many strong mass- and redshift-dependent features. Comparisons between the IllustrisTNG and Simba results show the astrophysical model choices cause significant differences in the mass and redshift dependence of these baryon imprints. Finally, we use existing observational measurements of cvir−Mvir to provide rough limits on the four astrophysical parameters. Our non-linear model is made publicly available and can be used to include Camels-based baryon imprints in any halo model-based analysis.

Astronomy & Astrophysics↗
DOE OSTI2025

Fingerprints of Triaxiality in the Charge Radii of Neutron-Rich Ruthenium

We present the first measurements with a new collinear laser spectroscopy setup at the Argonne Tandem Linac Accelerator System, utilizing its unique capability to deliver neutron-rich refractory metal isotopes produced by the spontaneous fission of 252 Cf. We measured isotope shifts from optical spectra for nine radioactive ruthenium isotopes 106–114 Ru, reaching deep into the mid-shell region. The extracted charge radii are in excellent agreement with predictions from the Brussels-Skyrme-on-a-Grid models that account for the triaxial deformation of nuclear ground states. We show that triaxial deformation impacts charge radii in models that feature shell effects, in contrast to what could be concluded from a liquid drop analysis. This indicates that this exotic type of deformation should not be neglected in regions where it is known to occur, even if its presence cannot be unambiguously inferred through laser spectroscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Consumptive Water Use in the Production of Ethanol and Petroleum Gasoline — 2018 Update

The production of energy feedstocks and fuels requires substantial water input. Not only do biofuel feedstocks like corn, switchgrass, and agricultural residues need water for growth and conversion to ethanol, but petroleum feedstocks like crude oil and oil sands also require large volumes of water for drilling, extraction, and conversion into petroleum products. Moreover, in many cases, crude oil production is increasingly water dependent. Competing uses strain available water resources and raise the specter of resource depletion and environmental degradation. Water management has become a key feature of existing projects and a potential issue in new ones. This report examines the growing issue of water use in energy production by characterizing current consumptive water use in liquid fuel production. As used throughout this report, “consumptive water use” is the sum total of water input less water output that is recycled and reused for the process. The estimate applies to surface and groundwater sources for irrigation but does not include precipitation. Water requirements are evaluated for five fuel pathways: bioethanol from corn, ethanol from cellulosic feedstocks, gasoline from Canadian oil sands, Saudi Arabian crude, and U.S. conventional crude from onshore wells. Regional variations and historic trends are noted, as are opportunities to reduce water use.

02 PETROLEUM↗
DOE OSTI2019

The Extended Baryon Oscillation Spectroscopic Survey: Measuring the Cross-correlation between the Mg II Flux Transmission Field and Quasars and Galaxies at z = 0.59

We introduce the first attempt at measuring the baryonic acoustic oscillations (BAOs) in the large-scale cross-correlation between the magnesium-II doublet Mg II) flux transmission field and the position of quasar and galaxy tracers. The Mg II flux transmission continuous field at 0.3 < z < 1.6 is measured from 500,589 quasar spectra obtained in the Baryonic Oscillation Spectroscopic Survey (BOSS) and the extended BOSS (eBOSS). The positions of 246,697 quasar tracers and 1346,776 galaxy tracers are extracted from the Sloan Digital Sky Survey I and II, BOSS, and eBOSS catalogs. In addition to measuring the cosmological BAO scale and the biased matter density correlation, this work allows tests and improvements to cosmological Lyα analyses. A feature consistent with that of the BAOs is detected at a significance of Δχ 2 = 7.25. The measured Mg II linear transmission bias parameters are b Mg II(2796) ( z = 0.59) = (-6.82 ± 0.54) × 10 -4 and b Mg II(2804) ( z = 0.59) = (-5.55 ± 0.46) ×10 -4 , and the Mg I bias is b Mg I(2853) ( z = 0.59) = (-1.48 ± 0.24) × 10 -4 . Their redshift evolution is characterized by the power-law index: γ Mg = 3.36 ± 0.46. Moroever, these measurements open a new window toward using BAOs from flux transmission at z < 1 in the final eBOSS sample and in the upcoming sample from the Dark Energy Spectroscopic Instrument.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Precision Measurements of the Neutron Magnetic Form Factor to High Momentum Transfer using Durand's Method

Protons and neutrons, collectively known as nucleons, along with electrons, constitute the funda- mental building blocks of the visible universe. Understanding their internal structure is crucial for addressing key scientific questions about our origin and existence. Elastic electron-nucleon scatter- ing provides insights into the spatial distributions of charge and current within nucleons through their electromagnetic form factors. Accurate knowledge of these form factors over a broad range of Q2, the squared four-momentum transfer in the scattering process, reveals details about the nucleon’s internal structure. However, high-Q2 data of the nucleon electromagnetic form factor is scarce due to the challenges associated with such measurements. This thesis reports preliminary results from high-precision measurements of the neutron magnetic form factor (Gn M ) to unprecedented Q2 using Durand’s method, also known as the “ratio” method. Systematic errors are greatly reduced by extracting Gn M from the ratio of neutron-coincident (D(e, e'n)) to proton-coincident (D(e, e'p)) quasi-elastic electron scattering from deuteron. The scattered electrons were detected in the BigBite spectrometer, which features multiple Gas Elec- tron Multiplier (GEM) layers with large active area for high-precision tracking at very high rates. Simultaneous nucleon detection was performed by the Super BigBite spectrometer, which utilizes a dipole magnet with large solid angle acceptance at forward angles and a novel hadron calorimeter with very high and comparable detection efficiencies for both protons and neutrons. This setup could handle very high luminosity, making high-Q2 measurements feasible. Data were collected at five Q2 points: 3, 4.5, 7.4, 9.9, and 13.6 (GeV/c)2. Preliminary results are reported for all, with the lowest two Q2 points in good agreement with existing world data, while the higher points significantly extend the Q2 range in which Gn M is known accurately. The precision of the highest Q2 point is expected to remain unmatched for years to come.

Datta, Provakar↗
DOE OSTI2021

Extracting correlation effects from momentum-resolved electron energy loss spectroscopy: Synergistic origin of the dispersion kink in Bi 2.1 Sr 1.9 CaCu 2 O 8 + x

We employ momentum-resolved electron energy loss spectroscopy (M-EELS) on Bi 2.1 Sr 1.9 CaCu 2 O 8 + x to resolve the issue of the kink feature in the electron dispersion widely observed in the cuprates. To this end, we utilize the GW approximation to relate the density response function measured in M-EELS to the self-energy, isolating contributions from phonons, electrons, and the momentum dependence of the effective interaction to the decay rates. The phononic contributions, present in the M-EELS spectra due to electron-phonon coupling, lead to kink features in the corresponding single-particle spectra at energies between 40 and 80 meV, independent of the doping level. We find that a repulsive interaction constant in momentum space is able to yield the kink attributed to phonons in ARPES. Hence, our analysis of the M-EELS spectra points to local repulsive interactions as a factor that enhances the spectroscopic signatures of electron-phonon coupling in cuprates. We conclude that the strength of the kink feature in cuprates is determined by the combined action of electron-phonon coupling and electron-electron interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Measurement Error in Atomic-Scale Scanning Transmission Electron Microscopy—Energy-Dispersive X-Ray Spectroscopy (STEM-EDS) Mapping of a Model Oxide Interface

Abstract With the development of affordable aberration correctors, analytical scanning transmission electron microscopy (STEM) studies of complex interfaces can now be conducted at high spatial resolution at laboratories worldwide. Energy-dispersive X-ray spectroscopy (EDS) in particular has grown in popularity, as it enables elemental mapping over a wide range of ionization energies. However, the interpretation of atomically resolved data is greatly complicated by beam–sample interactions that are often overlooked by novice users. Here we describe the practical factors—namely, sample thickness and the choice of ionization edge—that affect the quantification of a model perovskite oxide interface. Our measurements of the same sample, in regions of different thickness, indicate that interface profiles can vary by as much as 2–5 unit cells, depending on the spectral feature. This finding is supported by multislice simulations, which reveal that on-axis maps of even perfectly abrupt interfaces exhibit significant delocalization. Quantification of thicker samples is further complicated by channeling to heavier sites across the interface, as well as an increased signal background. We show that extreme care must be taken to prepare samples to minimize channeling effects and argue that it may not be possible to extract atomically resolved information from many chemical maps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗