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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structural and magnetic properties of CoTeMo⁢O 6

Here, we have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMo⁢O 6 . In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi et al., J. Solid State Chem. 182, 3232 (2009)], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMo⁢O 6 , with one occurring at 𝐻 𝑐⁢1 =460 Oe along the 𝑎 axis, and the other at 𝐻 𝑐⁢2 =1.16 T with the field along the 𝑏 axis. The values of 𝐻 𝑐⁢1 and 𝐻 𝑐⁢2 exhibit strong angular dependence and diverge with different rates as the applied field is rotated 90 ° within the 𝑎⁢𝑏 plane. This reflects the distinct nature of these transitions, which is further supported by the different critical behavior of 𝐻 𝑐⁢1 and 𝐻 𝑐⁢2 , characterized by the values of 𝛾, in the function of 𝐻 𝑐 =𝐻 0 ⁡(1−𝑇/𝑇 𝑐 ) 𝛾 . Furthermore, we have demonstrated that there exist structural and magnetic twin domains in CoTeMo⁢O 6 that strongly affect the experimental measurement of their macroscopic properties. Intriguingly, these twin domains can be related to the orthorhombicity/chirality of the crystal structure with the space group 𝑃⁢2 1 ⁢2 1⁢ 2. We further explored the magnetic and structural domains with uniaxial pressure and polarized light microscopy. Our results suggest that CoTeMo⁢O 6 could be used as a unique platform for investigating the intriguing physics involving intertwined degrees of freedom. The tunability of the underlying domain distribution and its strong anisotropy could also be useful for developing functional devices and applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Photonuclear cross sections for 197 Au: An update on the gold standard

Cross sections for the 197 Au(γ, n) reaction are broadly used in nuclear physics as a standard for normalizing photonuclear reaction cross-section data at photon beam energies above approximately 8 MeV. In this paper, we report cross-section measurements for the 197 Au(γ, n) 196 Au g+m1 reaction at beam energies from 13 to 31 MeV. Our measurements provide the first cross-section data for this reaction at beam energies above 20 MeV, enabling the use of this reaction as a cross-section standard up to 30 MeV. Also, this work provides first cross-section measurements for the 197 Au(γ, n) 196 Au m2 reaction. In addition, we measured cross-section data for the 197 Au(γ, 3n) 194 Au reaction, which can be used as a cross-section standard above about 25 MeV. These measurements were performed using a new target activation method that is based on the angle-energy correlation of the laser Compton- scattered photon beams at the High Intensity Gamma-ray Source (HIγS). The technique enables measuring photonuclear reaction cross-sections at several discrete beam energies concurrently via a single irradiation on a stack of different targets. Measurements were carried out by irradiating a stack of concentric-ring targets consisting of Au, TiO 2 , Zn, Os, and Au (in order of the γ-ray beam direction). Our data for the 197 Au(γ,n) 196 Au g+m1 reaction in the energy range of 13 to 20 MeV are in good agreement with existing ones measured using monoenergetic γ-ray beams, but differ from data acquired using a bremsstrahlung γ-ray beam. Also, above 18 MeV, our data for the 197 Au(γ,n) 196 Au g+m1 and 197 Au(γ,n) 196 Au m2 reactions differ significantly from the most recent TENDL and JENDL evaluations, suggesting a need to update these data libraries. Furthermore, the TENDL evaluation and existing data are consistent with our data for the 197 Au(γ,3n) reaction, but differ significantly from the JENDL evaluation above 26 MeV.

190 ≤ A ≤ 219↗
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
DOE OSTI2026

MapsTorch : automatic differentiation for X-ray fluorescence data analysis

X-ray fluorescence (XRF) is a popular spectroscopy technique for elemental analysis. Spectrum fitting and parameter tuning are at the core of XRF analysis and are conventionally manually intensive, especially for synchrotron experiments involving large amounts of diverse samples. This work introduces the automatic differentiation (AD) technique to XRF and an open-source package called MapsTorch. By transforming an analytical model of the XRF spectrum into a differentiable computation graph with AD, MapsTorch enables robust optimization of parameters and elemental intensities. We evaluate MapsTorch by conducting computational experiments on a large number of historical synchrotron XRF datasets and compare its performance with the currently practiced fitting tool NLopt. The results show that MapsTorch consistently achieves high-quality fits and often leads to better fitting quality than NLopt, particularly in tasks such as initial spectrum fitting and elemental intensity refinement. The robust performance of MapsTorch paves the way for developing automated and high-throughput XRF data analysis workflows to handle the increasing data volumes expected from next-generation synchrotron facilities.

X-ray fluorescence↗
DOE OSTI2024

Privacy-Preserving Federated Learning for Science: Challenges and Research Directions

This paper discusses the key challenges and future research directions for privacy-preserving federated learning (PPFL), with a focus on its application to large-scale scientific AI models, in particular, foundation models~(FMs). PPFL enables collaborative model training across distributed datasets while preserving privacy-- an important collaborative approach for science. We discuss the need for efficient and scalable algorithms to address the increasing complexity of FMs, particularly when dealing with heterogeneous clients. In addition, we underscore the need for developing advance privacy-preserving techniques, such as differential privacy, to balance privacy and utility in large FMs emphasizing fairness and incentive mechanisms to ensure equitable participation among heterogeneous clients. Finally, we emphasize the need for a robust software stack supporting scalable and secure PPFL deployments across multiple high-performance computing facilities. We envision that PPFL would play a crucial role to advance scientific discovery and enable large-scale, privacy-aware collaborations across science domains.

Kim, Kibaek [Argonne National Laboratory (ANL)]↗
DOE OSTI2024

Object Proxy Patterns for Accelerating Distributed Applications

Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer—optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns—distributed futures, streaming, and ownership—that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. As a result, we evaluate our implementations through a suite of benchmarks and by applying them in three meaningful scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.

Distributed Computing↗
DOE OSTI2025

Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States

Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.

greenhouse gas emissions↗
DOE OSTI2026

Dynamic asymmetric strain imprinted into substrates by an oxide thin film

In film-substrate systems, the substrate role is often considered to be limited to providing static mechanical constraints. Dynamic film-substrate interactions when a structural change in the film modifies the substrate are generally disregarded. Here, using combined x-ray and electron microscopies, we observed that an electrically induced filament in a vanadium dioxide film created strong asymmetric strain in an underlying sapphire substrate. This asymmetric substrate strain fed back into the film and defined the filament expansion direction, revealing the importance of film-substrate dynamic interactions in determining film functionality. Furthermore, the strain imprint propagated at least tens of micrometers deep into the substrate, exceeding the film thickness by more than 200-fold, potentially enabling substrate functionalization as an active mechanical coupling media in three-dimensional integrated microelectronic architectures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

First demonstration of a TES based cryogenic Li 2 MoO 4 detector for neutrinoless double beta decay search

Cryogenic calorimetric experiments to search for neutrinoless double-beta decay (0vββ) are highly competitive, scalable and versatile in isotope. The largest planned detector array, CUPID, is comprised of about 1500 individual Li 2 100 MoO 4 detector modules with a further scale up envisioned for a follow up experiment (CUPID-1T). In this article, we present a novel detector concept targeting this second stage with a low impedance TES based readout for the Li 2 MoO 4 absorber that is easily mass-produced and lends itself to a multiplexed readout. We present the detector design and results from a first prototype detector operated at the NEXUS shallow underground facility at Fermilab. The detector is a 2-cm-side cube with 21 g mass that is strongly thermally coupled to its readout chip to allow rise-times of ~0.5 ms. This design is more than one order of magnitude faster than present NTD based detectors and is hence expected to effectively mitigate backgrounds generated through the pile-up of two independent two neutrino decay events coinciding close in time. Together with a baseline resolution of 1.95 keV (FWHM) these performance parameters extrapolate to a background index from pile-up as low as 5 • 10 –6 counts/keV/kg/yr in CUPID size crystals. The detector was calibrated up to the MeV region showing sufficient dynamic range for 0vββ searches. In combination with a SuperCDMS HVeV detector this setup also allowed us to perform a precision measurement of the scintillation time constants of Li 2 MoO 4 , which showed a primary component with a fast O(20 μs) time scale. Similar content being viewe

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A Grassroots Network and Community Roadmap for Interconnected Autonomous Science Laboratories for Accelerated Discovery

Scientific discovery is being revolutionized by AI and autonomous systems, yet current autonomous laboratories remain isolated islands unable to collaborate across institutions. We present the Autonomous Interconnected Science Lab Ecosystem (AISLE), a grassroots network transforming fragmented capabilities into a unified system that shorten the path from ideation to innovation to impact and accelerates discovery from decades to months. AISLE addresses five critical dimensions: (1) cross-institutional equipment orchestration, (2) intelligent data management with FAIR compliance, (3) AI-agent driven orchestration grounded in scientific principles, (4) interoperable agent communication interfaces, and (5) AI/ML-integrated scientific education. By connecting autonomous agents across institutional boundaries, autonomous science can unlock research spaces inaccessible to traditional approaches while democratizing cutting-edge technologies. This paradigm shift toward collaborative autonomous science promises breakthroughs in sustainable energy, materials development, and public health.

Ferreira da Silva, Rafael [Oak Ridge National Labo↗
DOE OSTI2025

Modeling the Nucleation and Growth of Lead Sulfate Particles on Lead Electrodes

Lead-acid batteries (LABs) play a pivotal role in the energy storage sector with applications spanning from starting-lighting-ignition batteries to grid energy storage. Passivation of lead negative electrodes by PbSO 4 particles is a fundamental mechanism limiting the performance of LAB. In this regard, an electrochemical model is developed that simulates the nucleation and growth (N&G) dynamics of PbSO 4 particles on a flat lead electrode, responsible for its passivation. The model considers the electrochemical reactions between lead electrode and sulfuric acid, N&G of PbSO 4 particles, passivation of the lead surface, and the ternary transport of PbSO 4 (aq), bisulfate, and protons in H 2 SO 4 electrolyte. The model is validated with a dataset of cyclic voltammetry (CV) responses collected at several scan rates and H 2 SO 4 concentrations. The model shows remarkable qualitative and quantitative agreement with the experimental data including CV peak features, discharge capacity, and particle size. The model was employed to explore key N&G quantities, such as supersaturation, nucleation rate, particle count, growth rate, particle size, and surface coverage, and to examine how their interactions influence electrode utilization. Parametric studies were also conducted to evaluate how scan rates and acid concentrations influence the previously mentioned N&G quantities and, subsequently, the utilization of the electrode.

25 ENERGY STORAGE↗
DOE OSTI2025

Mitigating Transition Metal Dissolution from Mn-rich Cathodes: Influence of Processing and Testing Methods

Manganese-rich oxides continue to gain interest with respect to the development of Earth-abundant options for lithium-ion cathodes. Of the unique challenges that hinder the respective performance of various classes of such materials, manganese dissolution still stands as a common theme. The work herein explores Li 3 PO 4 as a robust surface protection layer on a prototypical, Co-free, manganese-rich cathode in the way of a lithium- and manganese-rich oxide. The study highlights the critical importance of synthesis and processing in realizing optimal performance of a given surface treatment by comparing sol-gel and atomic layer deposition methods. Furthermore, cycling protocols are emphasized as a critical factor in adequately gauging the efficacy of surface protection strategies to mitigate manganese dissolution and the subsequent electrochemical consequence. Optimized Li 3 PO 4 coatings coatings on lithium- and manganese-rich cathode particles are shown to greatly mitigate capacity fade, impedance rise, pore/void formation and mechanical damage during long-term cycling.

Mallick, Subhadip [Argonne National Laboratory (AN↗
DOE OSTI2025

Choline Chloride-Based Water-in-Salt Electrolyte for Efficient Iron Electrodeposition

Electrochemical production of iron is a promising low-cost and modular approach to replace the traditional blast furnace. Aqueous electrolytes for iron electrolysis are advantageous as they can be operated at near-ambient temperatures, but they suffer from inefficiencies due to the parasitic hydrogen evolution reaction. In this work, we identify a new water-in-salt electrolyte (WiSE) based on choline chloride (ChCl) for high coulombic efficiency (>85%) iron deposition. Electrochemical analysis of the partial current densities of iron plating and hydrogen co-evolution revealed that, at optimal WiSE compositions, water reduction is kinetically suppressed resulting in an increase in the Fe plating efficiency. Decreased coordination of water and increased coordination of choline’s alcohol group with the Fe 2+ ion were observed through 1 H NMR providing evidence that water reduction is kinetically suppressed in WiSE. Additionally, Raman spectroscopy revealed that complexation effects (with Cl – ) reduce Fe 2+ diffusion coefficients and corresponding limiting currents as the ChCl concentration is increased. This results in an optimal WiSE composition (4 M ChCl + 1 M FeCl 2 ) that provides kinetic suppression of HER but also low transport resistance to Fe plating yielding 85% coulombic efficiency at high current densities.

Sinclair, Nicholas Scott [Case Western Reserve Uni↗
DOE OSTI2025

Decoupling Failure Pathways in Li-O 2 Cells Operated Under Lean Electrolyte Conditions

The operation of lithium-oxygen (Li-O 2 ) batteries under lean electrolyte conditions offers higher energy density but leads to rapid degradation and short cycle life. Although cathode passivation and electrolyte decomposition occur in all regimes, we show that under lean electrolyte conditions, failure is primarily driven by progressive electrolyte consumption at the lithium/solid electrolyte interphase (SEI), rather than by irreversible cathode passivation. Poor wetting of the lithium surface results in heterogeneous SEI growth and high local current densities, which accelerate electrolyte loss and cell failure. Strategies aimed at improving interfacial stability, including optimized wetting and SEI forming additives, significantly extend cycle life without compromising energy density. Our results establish anode-electrolyte interactions as the dominant degradation mechanism under lean electrolyte conditions, and emphasize the need to engineer a stable Li/SEI interface for long-lasting Li-O 2 batteries.

Córdoba, Daniel [Argonne National Laboratory (ANL)↗
DOE OSTI2025

Cycling Performance and Structure Evolution of Co-Free Lithium- and Manganese-Rich Layered Oxides in Lithium-Ion Batteries

Lithium- and manganese-rich (LMR) layered oxides are high-capacity cathode materials that are being considered for electric vehicle (EV) lithium-ion batteries (LIBs). Here, we investigate the electrochemical cycling behavior of cells containing a cobalt-free LMR oxide, 0.3Li 2 MnO 3 ·0.7LiMn 0.5 Ni 0.5 O 2 , paired with either Li or graphite anodes. Two- and three-electrode cells are cycled under varying conditions to examine the effects of oxide activation, upper cutoff voltage, separator type, and electrolyte composition. Post-cycling characterization of harvested electrodes, with electrochemical, X-ray absorption spectroscopy, and solid-state 6 Li nuclear magnetic resonance spectroscopy techniques, are used to correlate cell performance changes with redox state evolution in the oxide and Li inventory shifts in the cell. Our results show that capacity fade and impedance rise primarily originate at the graphite anode and LMR cathode, respectively. Notably, while Ni undergoes reversible redox, Mn shows no evidence of bulk redox activity even in highly-aged electrodes: only relithiated LMR electrodes show some reduction of Mn. Graphite electrodes degrade due to particle isolation and SEI growth, exacerbated by Mn dissolution and deposition on graphite anodes. These findings highlight the coupled structural and electrochemical degradation mechanisms in LMR/graphite cells and underscore lithium inventory retention and electrode interfacial stability as critical factors for enhancing long-term performance.

Badami, Pavan P. [Argonne National Laboratory (ANL↗
DOE OSTI2026

Cobalt-Free Lithium and Manganese Rich Cathodes for Electric Vehicle Applications: Influence of Inherent Properties on Temperature-Dependent Performance

Lithium- and manganese-rich (LMR) oxides are attractive options as next-generation, earth-abundant cathodes. Despite inherent properties that result in less-than-ideal performance, advancements in this class of cathodes toward commercialization have been steady. Herein, we report a benchmark study on the influence these inherent properties exert on the discharge rate of Co-free, LMR//graphite (Gr) cells as a function of temperature. Because low-temperature performance is an essential consideration in the design of electric vehicle cells, understanding the limitations of current LMR systems is essential in understanding their current applicability as well as strategies for improvement. This work identifies two major limitations in the rate performance of LMR//Gr cells and suggests several areas of focus where practical strategies may provide improvements.

25 ENERGY STORAGE↗
DOE OSTI2025

Q-OPT:Quantum Optimization Toolkit

SF-2025-003 Quantum computing has the potential to solve classical optimization problems. To bring these algorithms into practical use, a comprehensive, high-performance and user-friendly toolkit is essential. The Q-OPT: Quantum Optimization Toolkit is a collection of software tools designed to support complete end-to-end framework for quantum optimization.

Hovland, Paul [Argonne National Laboratory (ANL), ↗
DOE OSTI2025

pyAXEAP1-GUI package

SF-25-076 pyAXEAP1-GUI package is an X-ray emission spectroscopy (XES) data analysis package in the Python language. It can transfer the collected images from a 2D detector into spectra and display XES and RXES data as 3Dimages, 2D images and 1D profiles.

Berno, Alexander↗