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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluating the Potential to Constrain Dark Matter Annihilation with Fermi-LAT Observations of Ultrafaint Compact Stellar Systems

Recent results from numerical simulations and models of galaxy formation suggest that recently discovered ultrafaint compact stellar systems (UFCSs) in the halo of the Milky Way (MW) may be some of the smallest and faintest galaxies. If this is the case, these systems would be attractive targets for indirect searches of weakly interacting massive particle dark matter (DM) annihilation due to their relative proximity and high expected DM content. In this study, we analyze 14.3 yr of γ-ray data collected by the Fermi-Large Area Telescope coincident with 26 UFCSs. No significant excess γ-ray emission is detected, and we present γ-ray flux upper limits for these systems. Assuming that the UFCSs are DM-dominated galaxies consistent with being among the faintest and least massive MW dwarf spheroidal (dSph) satellite galaxies, we derive the projected sensitivity for a DM annihilation signal. We find that observations of UFCSs have the potential to yield some of the most powerful constraints on DM annihilation, with sensitivity comparable to observations of known dSphs and the Galactic center. This result emphasizes the importance of precise kinematic studies of UFCSs to empirically determine their DM content.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Response of the mode Grüneisen parameters with anisotropic compression: A pressure and temperature dependent Raman study of β-Sn

The lattice dynamic response of body-centered tetragonal beta-Sn (I4 1 /amd) under high-pressure and temperature conditions is determined using experimental optical vibration modes. Here, Raman scattering is used to map the phase stability region of beta-Sn to perform mode Gruneisen analysis, and we demonstrate the necessity of an optical intensity calibration for Raman thermometry. The Gruneisen tensor is evaluated along a set of isotherms to address shortcomings of single-mode Gruneisen parameters with respect to anisotropic deformations of this tetragonal structured soft metal. The changes observed here in the Gruneisen tensor as a function of temperature are related to anharmonicity and denote potential criteria for the onset of premelting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Design, Control and Application of Next Generation Qubits

Design, Control and Application of Next Generation Qubits Arun Bansil, Northeastern University (Principal Investigator) Claudio Chamon, Boston University (Co-Investigator) Adrian Feiguin, Northeastern University (Co-Investigator) Liang Fu, MIT (Co-Investigator) Eduardo Mucciolo, Univ. of Central Florida (Co-Investigator) Qimin Yan, Temple University (Co-Investigator) The quest for developing technologies for manipulating and storing information quantum mechanically is currently led by approaches that include Josephson-junctions, ion-traps, and qubits generated by defect spins in solids. Topological qubits, however, are inherently more robust to decoherence by environmental effects, and should be able to sprint ahead once practical barriers have been overcome. At the present stage of the development of the field, it is important to explore a variety of architectures and materials beyond the conventional paradigms in order to seed breakthroughs toward building a scalable quantum computer. Our comprehensive theoretical research program involved four interconnected thrusts as follows. • A materials discovery effort in two-dimensional compounds in search of materials to support Majorana zero modes and defect structures suitable as qubits. • Exploration of architectures for topological quantum computation by investigating both superconducting Majorana qubits, and robust platforms for braiding with new “meta-materials” built of arrays of Majorana qubits. • Investigation of properties of hybrid metal-organic qubits based on transition-metal centers in graphene, and molecular crystals of polyaromatic complexes with embedded transition-metal atoms. • Development of tensor-network and semiclassical approaches to study decoherence in the presence of random and dispersive spin baths, and NV centers in diamond. The full spectrum of theoretical and numerical approaches was used to address the goals of this project including first-principles, density-matrix-renormalization group, tensor networks, and data-driven high-throughput approaches using materials database and machine-learning.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Round-Robin Interlaboratory Study on Rare-Earth Elements in U.S.-Based Geologic Materials

In a study funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the University of North Dakota (UND) Energy and Environmental Research Center (EERC) performed a first-of-its-kind round-robin interlaboratory study (RRIS) to determine lab-to-lab and method-to-method variability in analyzing the rare earth element (REE) content of domestic resources. Analyses of REEs on eleven different materials were accomplished by the laboratories using four different procedures: ASTM D6357 (Procedure A), ASTM D4503 (Procedure B), an alternate in-house procedure for digestion and REE analysis (Procedure C), and neutron activation analysis (NAA). The results of the RRIS suggest that NAA is the most accurate and reliable method for many of the REEs in these types of materials; however, the method is limited in that it is able to determining only ten of the sixteen REEs. Five of the seven labs reporting data for Procedure A and three of the five labs reporting for Procedure B showed excellent performance in terms of repeatability, reproducibility, agreement with NAA, and SRM recoveries based on AOAC International guidelines on method performance. This indicates that when strictly followed these methods are suitable for REE determination in most materials, although are subject to the overall capabilities and experience of individual laboratories.

58 GEOSCIENCES↗
DOE OSTI2020

In situ microstructural evolution in face-centered and body-centered cubic complex concentrated solid-solution alloys under heavy ion irradiation

This study characterizes the microstructural evolution of single-phase complex concentrated solid-solution alloy (CSA) compositions under heavy ion irradiation with the goal of evaluating mechanisms for CSA radiation tolerance in advanced fission systems. Three such alloys, Cr 18 Fe 27 Mn 27 Ni 28 , Cr 15 Fe 35 Mn 15 Ni 35 , and equimolar NbTaTiV, along with reference materials (pure Ni and E90 for the Cr-FeMnNi family and pure V for NbTaTiV) were irradiated at 50 K and 773 K with 1 MeV Kr ++ ions to various levels of displacements per atom (dpa) using in-situ transmission electron microscopy. Cryogenic irradiation resulted in small defect clusters and faulted dislocation loops as large as 12 nm in face-centered cubic (FCC) CSAs. With thermal diffusion suppressed at cryogenic temperatures, defect densities were lower in all CSAs than in their less compositionally complex reference materials indicating that point defect production is reduced during the displacement cascade stage. High temperature irradiation of the two FCC CSA resulted in the formation of interstitial dislocation loops which by 2 dpa grew to an average size of 27 nm in Cr 18 Fe 27 Mn 27 Ni 28 and 10 nm in Cr 15 Fe 35 Mn 15 Ni 35 . This difference in loop growth kinetics was attributed to the difference in Mn-content due to its effect on the nucleation rate by increasing vacancy mobility or reducing the stacking-fault energy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Full-polarization millimeter wavelength variability of Sagittarius A * during the 2018 EHT campaign

Context. Sagittarius A* (Sgr A*), the supermassive black hole at the center of the Milky Way, provides a unique laboratory to study accretion dynamics and plasma processes near the event horizon. Aims. We investigated the variability and polarization properties of Sgr A* using ALMA observations during the 2018 Event Horizon Telescope campaign. Methods. We analyzed high-cadence full-polarization light curves from ALMA at millimeter wavelengths, performed time-series analysis, and investigated the temporal behavior during an X-ray flare observed by Chandra on 2018 April 24. The variability characteristics are compared with expectations from standard accretion flow models. Results. We find low variability in total intensity (σ/μ < 10%), but significantly higher variability in linear and circular polarization (∼30% and ∼50%, respectively). A time-series analysis reveals red-noise variability, with power spectral densities between −2 and −3 across all Stokes parameters. Polarized intensity shows stable intra-day timescales, while total intensity exhibits more variable timescales, suggesting distinct emission regions, with polarization likely arising from a coherent structure. On April 24, a statistically significant inter-band delay in polarized intensity coincides with a near-simultaneous X-ray and millimeter peak that deviates from the typical delayed flare scenario. This event also features enhanced millimeter variability and coherent polarization loop evolution. The observed simultaneity challenges standard models of transient synchrotron emission with cooling delays, favoring instead a scenario of continuous energy injection in an optically thin region. Conclusions. Our results offer new constraints on the physical mechanisms driving variability in Sgr A*, and provide key observational input for refining theoretical models of accretion and plasma behavior in the vicinity of supermassive black holes.

Galaxy: center↗
DOE OSTI2020

10 MWE CDCL Large Pilot Plant – pre-FEED Study (Final Report)

The Following Document is the Final Technical Scientific Report for the project tittle “10 MWE CDCL Large Pilot Plant – pre-FEED Study” performed by The Babcock & Wilcox Company in collaboration with The Ohio State University, Johnson & Matthey, The Electric Power Research Institute, and the Dover Light & Power Municipal Power Plant. The project Team performed a pre-Front End Engineering Design study of a 10 MWe Coal-Direct Chemical Looping power plant to be hosted at the Dover Light & Power Municipal Plant. As part of the pre-FEED study, the project Team performed multiple pilot test campaigns to obtain design and performance information at the 250 kWth CDCL pilot facility at the Babcock & Wilcox Company’s Research Center. The Techno-Economic analysis was updated based on the FEED study and the pilot tests results. The study shows that the CDCL process is a promising carbon-friendly technology capable of producing electricity with a high efficiency with a cost of electricity of $83.3 / MWh, which corresponded to less than 30% increase in cost of electricity compared to the cost of electricity of a base case study of a supercritical PC boiler.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Tandem Predictions for HPC Jobs

At the core of the predictive analytics applied to High Performance Computing (HPC), the most prominent tasks are the prediction of job runtimes and the prediction of job queue times, both of which have the potential for informing HPC users during their every-day decision making. Accurate runtime predictions can help users better choose so-called wallclock times at job submission, decreasing the odds of their jobs waiting in queues longer than necessary. The accurate and timely queue time predictions offered for the available partitions can inform the favorable selection of partitions for running jobs. This potential is well understood as we see in the abundance of research studies that propose solutions for these tasks, including the work published in the last several years. These tasks are seemingly receptive to the Machine Learning (ML) solutions, considering that there is no shortage of training data where HPC centers over time run millions and millions of jobs. However, we study the existing research literature, as well as look for examples in the toolchains supported on the exemplar HPC facilities, and, surprisingly, do not find any practical solutions that are ready to be adopted. We interpret this as a manifestation of the shortage of UX/UI efforts that support HPC analytics and also as a sign that the research has not come to the consensus on solving these tasks. In this study, we aim to shed new light on the long-running task of job queue time prediction by exploring the utility of runtime predictions in improving prediction accuracy and, actually, predicting these two metrics together, in tandem. In other words, we show how runtime predictions become valuable input in the queue time modeling. We challenge the existing approaches to feature engineering for the queue time prediction and describe promising results we obtained for a large dataset of HPC jobs from a supercomputer at the National Renewable Energy Laboratory.

HPC↗
DOE OSTI2025

Tandem Predictions for HPC Jobs: Preprint

At the core of the predictive analytics applied to High Performance Computing (HPC), the most prominent tasks are the prediction of job runtimes and the prediction of job queue times, both of which have the potential for informing HPC users during their every-day decision making. Accurate runtime predictions can help users better choose so-called wallclock times at job submission, decreasing the odds of their jobs waiting in queues longer than necessary. The accurate and timely queue time predictions offered for the available partitions can inform the favorable selection of partitions for running jobs. This potential is well understood as we see in the abundance of research studies that propose solutions for these tasks, including the work published in the last several years. These tasks are seemingly receptive to the Machine Learning (ML) solutions, considering that there is no shortage of training data where HPC centers over time run millions and millions of jobs. However, we study the existing research literature, as well as look for examples in the toolchains supported on the exemplar HPC facilities, and, surprisingly, do not find any practical solutions that are ready to be adopted. We interpret this as a manifestation of the shortage of UX/UI efforts that support HPC analytics and also as a sign that the research has not come to the consensus on solving these tasks. In this study, we aim to shed new light on the long-running task of job queue time prediction by exploring the utility of runtime predictions in improving prediction accuracy and, actually, predicting these two metrics together, in tandem. In other words, we show how runtime predictions become valuable input in the queue time modeling. We challenge the existing approaches to feature engineering for the queue time prediction and describe promising results we obtained for a large dataset of HPC jobs from a supercomputer at the National Renewable Energy Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Metal–Metal Bonding Influences Hydride Reactivity in [Sn–Rh] 3+ and [Sn–Ni] 2+ Bimetallics

Heavier group 14 metal hydrides serve as key intermediates in catalytic transformations, such as hydroboration. Regenerating such intermediates via a clean hydride source like dihydrogen could provide catalytic processes with a more economical alternative to, e.g., silanes and hydridoborane reagents. Herein, we report our efforts toward this goal using a [Sn–Rh] 3+ bimetallic system with the formal Rh I center acting as a potential dihydrogen activator. Targeting the introduction of a hydride ligand to the bimetallic core, our reactivity studies have revealed a preference for the hydride ligand to be bound to the Rh center, instead of the Sn center. Finally, examination of the electronic structures of these complexes via theoretical and experimental methods has revealed the electron acceptor nature of the Rh center within the bimetallic core and offers an explanation for the localization of the hydride between metal centers.

anions↗
DOE OSTI2024

Advancing Sustainability in Data Centers: Evaluation of Hybrid Air/Liquid Cooling Schemes for IT Payload Using Sea Water

Abstract-The growth in cloud computing, Big Data, AI and high-performance computing (HPC) necessitate the deployment of additional data centers (DC's) with high energy demands. The unprecedented increase in the Thermal Design Power (TDP) of the computing chips will require innovative cooling techniques. Furthermore, DC's are increasingly limited in their ability to add powerful GPU servers by power capacity constraints. As cooling energy use accounts for up to 40% of DC energy consumption, creative cooling solutions are urgently needed to allow deployment of additional servers, enhance sustainability and increase energy efficiency of DC's. The information in this study is provided from Start Campus' Sines facility supported by Alfa Laval for the heat exchanger and CO 2 emission calculations. The study evaluates the performance and sustainability impact of various data center cooling strategies including an air-only deployment and a subsequent hybrid air/water cooling solution all utilizing sea water as the cooling source. Here we evaluate scenarios from 3 MW to 15+1 MW of IT load in 3 MW increments which correspond to the size of heat exchangers used in the Start Campus' modular system design. This study also evaluates the CO 2 emissions compared to a conventional chiller system for all the presented scenarios. Results indicate that the effective use of the sea water cooled system combined with liquid cooled systems improve the efficiency of the DC, plays a role in decreasing the CO 2 emissions and supports in achieving sustainability goals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Progress and innovations in the TCV tokamak research programme

Research on the Tokamak à Configuration Variable addresses a wide range of key questions relevant to ITER and future fusion power plants. Over the past two years, highly productive experimental campaigns have led to major advances across several areas: the ITER baseline scenario; pedestal properties in low-collisionality, peeling-limited conditions; and the development of high- β N , non-inductive regimes. Alternative high-confinement scenarios have likewise received significant attention, with remarkable progress in quasi-continuous exhaust operation, X-point radiator plasmas, and negative triangularity configurations. Substantial achievements were also made in the mitigation or benign termination of runaway electron beams, in elucidating fast-ion loss mechanisms, and in improving exhaust behaviour in both conventional and alternative divertor geometries. These experimental results have been strongly supported by advances in modelling and their direct application to the experiment, ranging from gyrokinetic simulations of core and pedestal turbulence to fluid-based studies of scrape-off layer and divertor physics in diverse geometries. Plasma control has taken on an increasingly important role, with model-based and data-driven approaches now closely intertwined with physics studies. This article provides a overview of these recent activities, together with a brief outlook on forthcoming upgrades and next steps.

EPFL↗
DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Electromechanical response of piezoelectric thin films subjected to large strain

The use of piezoelectric thin sensors, when subjected to large static strain levels in ultrasonic applications is reported in this paper. A novel flipped beam bending method is proposed to induce static strain level nearing twice the incipient yield strain in the beam material (~0.39%). First, the effect of static large strain on ultrasonic guided wave propagation in the beam was studied using the velocity measurements obtained from a laser Doppler vibrometer. Next, the ultrasonic response of thin sensors is studied under compressive and tensile static strain (±0.72%) with the sensors symmetrically bonded on the lower and upper surfaces, and at the same axial location. The ultrasonic guided wave response to varying levels of static strain is recorded at different center frequencies (50–400 kHz) of the narrow banded ultrasonic excitation. As a case study, the variation of the ultrasonic guided wave response of polyvinylidene difluoride (PVDF) thin sensors with center frequencies at different static strain levels was analyzed and compared with that of lead zirconate titanate (PZT) thin sensors. PZT sensors show a higher variation of sensing performance with strain when compared to PVDF sensors. Apart from static strain, the possible effects on the change in performance of sensors, such as the change in the capacitance is discussed. The characterization method provides a reusable beam arrangement to study the ultrasonic sensor performance at large static strain levels. Characterization at large strain level allows the development of fail-safe sensors even under large strain and permanent plastic deformation of structure on which they are bonded, allowing accurate ultrasonic structural health monitoring even in the presence of damage progression. Piezopolymer sensor like PVDF are least susceptible to static strain due to large yield strain and low modulus and can serve as fail-safe sensors under large strain.

Rathod, Vivek↗
DOE OSTI2022

Assessment of chemo-mechanical impacts of CO 2 sequestration on the caprock formation in Farnsworth oil field, Texas

This study evaluates the chemo-mechanical influence of injected CO 2 on the Morrow B sandstone reservoir and the upper Morrow shale caprock utilizing data from the inverted 5-spot pattern centered on Well 13-10A within the Farnsworth unit (FWU). This study also seeks to evaluate the integrity of the caprock and the long-term CO 2 storage capability of the FWU. The inverted 5-spot pattern was extracted from the field-scale model and tuned with the available field observed data before the modeling work. Two coupled numerical simulation models were utilized to continue the study. First, a coupled hydro-geochemical model was constructed to simulate the dissolution and precipitation of formation minerals by modeling three intra-aqueous and six mineral reactions. In addition, a coupled hydro-geomechanical model was constructed and employed to study the effects of stress changes on the caprock’s porosity, permeability, and ground displacement. The Mohr–Coulomb circle and failure envelope were used to determine caprock failure. In this work, the CO 2 -WAG injection is followed by the historical field-observed strategy. During the forecasting period, a Water Alternating Gas (WAG) injection ratio of 1:3 was utilized with a baseline bottom-hole pressure constraint of 5500 psi for 20 years. A post-injection period of 1000 years was simulated to monitor the CO 2 plume and its effects on the CO 2 storage reservoir and caprock integrity. The simulation results indicated that the impacts of the geochemical reactions on the porosity of the caprock were insignificant as it experienced a decrease of about 0.0003% at the end of the 1000-year post-injection monitoring. On the other hand, the maximum stress-induced porosity change was about a 1.4% increase, resulting in about 4% in permeability change. It was estimated that about 3.3% of the sequestered CO 2 in the formation interacted with the caprock. Despite these petrophysical property alterations and CO 2 interactions in the caprock, the caprock still maintained its elastic properties and was determined to be far from its failure.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Effects of Radiation Reaction Physics on High-Current Power Flow

In this study, we examine the effects of the radiation reaction force on electrons in a radial magnetically insulated transmission line (MITL) near a load with peak currents of 60+ MA. More specifically, we study the differences in electron motion and kinetic energy with or without radiation reaction physics using a novel guiding center drift approach that incorporates E $\times$ B and ∇B drifts. A key finding of this study is that an electron's magnetic moment, which would be conserved when radiation reaction physics is not incorporated, can be significantly reduced in magnetic fields on the order of 10,000's T when radiation reaction is included. The reduction of magnetic moment gives rise to a significant reduction in cycloidal kinetic energy as well as a reduction in the electron's ∇B drift.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A multifunctional sesquiterpene synthase integrates with cytochrome P450s to reinforce the terpenoid defense network in maize

Terpenoids, the largest and most structurally diverse class of plant natural products, play essential roles in maize defense and ecological interactions. In this study, we identified and functionally characterized a sesquiterpenoid-based defense pathway in maize centered on α-santalenoic acid, a pathogen-inducible sesquiterpenoid antibiotic. Using a combination of metabolite-based genome-wide association studies (mGWAS), linkage mapping, and heterologous expression assays, we identified ZmTPS9 as a multiproduct terpene synthase that primarily produces α-santalene and β-bisabolene. Sequence analysis and site-directed mutagenesis revealed that threonine at position 413 is critical for enzyme activity, with its deletion resulting in a complete loss of enzyme activity. The sesquiterpene hydrocarbons produced by ZmTPS9 are further oxidized by three cytochrome P450 monooxygenases, ZmCYP71Z16, ZmCYP71Z18, and ZmCYP71Z19, to yield antimicrobial metabolites including α-santalenoic acid, zealexin D1 (ZD1), and zealexin D2 (ZD2). Together, these findings demonstrate a convergent biosynthetic strategy in maize, where multiproduct terpene synthases and promiscuous P450s collaboratively generate a flexible and robust terpenoid defense network.

a-santalenoic acid↗
DOE OSTI2020

Butyltin Keggin Ion with a Rare Four-Coordinate Ca Center

Alkyltin clusters are exploited in nanolithography for the fabrication of microelectronics. The alkyltin Keggin family is unique among Keggin clusters across the periodic table; its members appear to favor the lower-symmetry β and γ isomers rather than the highly symmetrical α and ε isomers. Therefore, the alkyltin Keggin family may provide important fundamental information about the formation and isomerization of Keggin clusters. In this study, we have synthesized and structurally characterized a new butyltin Keggin cluster with a tetrahedral Ca 2+ center, fully formulated [(BuSn) 12 (CaO 4 )(OCH 3 ) 12 (O) 4 (OH) 8 ] 2+ (β-CaSn 12 ). The synthesis is a simple one-step process. Extensive solution characterization including electrospray ionization mass spectrometry, small-angle X-ray scattering, and multinuclear ( 1 H, 13 C, and 119 Sn) nuclear magnetic resonance shows β-CaSn 12 is essentially phase-pure and stable. This differs from the previously reported Na-centered analogues that always form a mixture of β and γ isomers, with facile interconversion. Therefore, this study has clarified prior confusion over complex spectroscopic and crystallographic characterization of the Na-centered analogues. Density functional theory calculations showed the following stability order: γ-CaSn 12 < γ-NaSn 12 < β-CaSn 12 < β-NaSn 12 . The β analogue is always more stable than the γ analogue, consistent with experiment. Notable outcomes of this study include a rare tetrahedral Ca coordination, a Na-free alkyltin cluster (important for microelectronics manufacturing), and a better understanding of Keggin families built of different metal cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗