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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SQUID Readout of a High-$Q$ Superconducting $LC$ Resonator

We demonstrate the readout of a superconducting $LC$ resonator, with $Q \approx 2 \times 10^{6}$ at approximately 250 kHz, using a dc SQUID followed by a SQUID series-array amplifier readout chain. We find that $Q$ depends on the SQUID flux-bias point, increasing near the shallow-slope point of the SQUID modulation curve and decreasing near the steep-slope point, consistent with the previously observed SQUID damping effects. From this variation, we infer the SQUID effective input impedance. We further infer the effective temperature of the resonator circuit from the resonance peak in the noise spectrum and show that it also depends on the SQUID flux-bias point, suggesting a possible contribution from SQUID back-action noise. This system provides a working prototype for future experiments based on lumped-element resonators with SQUID readout, in particular low-mass axion searches within the DMRadio program.

FOS: Physical sciences↗
NASA NTRSDate not supplied

Accelerating SNP Development with Radiation Source Approximations for Far-Field Environment Modeling

The successful development and deployment of space nuclear power and propulsion technology requires a high-fidelity, efficient means of modeling ex-core radiation fields. Monte Carlo particle transport codes provide enable the highest level of fidelity in radiation field modeling but are inefficient for modeling ex-core radiation without modification. This paper details the development of an approach to ex-core radiation field modeling that maintains the fidelity of a Monte Carlo transport approach without sacrificing computational efficiency. This approach is based on recent improvements to an existing Monte Carlo transport acceleration technique known as surface source banking. As the transport of many particles is required to ensure adequate uncertainty in far field transport, analytical reconstruction techniques are employed to represent surface source banks as sampleable series of distributions in particle phase from which an arbitrarily large number of particles can be generated and simulated. All steps of this approach are incorporated into an AMA model to test both the underlying mathematics of the analytical source reconstruction process, as well as the relevance of the technique as a whole towards SNP applications. These tests demonstrated that this approach is capable of accelerating far-field radiation modeling in SNP-relevant scenarios by factors of at least nine over purely eigenvalue-based scenarios without significantly sacrificing simulation accuracy.

Surface Source Banking↗
DOE OSTI2026

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗
DOE OSTI2026

Detecting the full photoemission cone from laser-based ARPES experiments by leveraging deflector technology

Angle-resolved photoemission spectroscopy (ARPES) provides a direct access to the electronic band structure of solid and molecular systems. The momentum range accessible by this technique depends directly on the photon energy used, and low-photon-energy sources are insufficient to photoemit electrons over the full Brillouin zone of most quantum materials. In addition, while electrons are emitted over a 2π solid angle, conventional hemispherical analyzers only collect a small subset of those electrons. A previous work [Gauthier et al., Rev. Sci. Instrum. 92, 123907 (2021)] demonstrated that electrons emitted over a larger field-of-view can be acquired in one fixed configuration by accelerating them toward the analyzer with a bias voltage. Here, in this study, we extend this work by leveraging the deflector technology of novel ARPES hemispherical analyzers. We demonstrate the ability to detect all 2π photoemitted electrons in a fixed configuration for various materials, such as gold, cuprates, and transition-metal dichalcogenides. This approach is especially advantageous for time-resolved ARPES, as electron dynamics over a large momentum range can be accessed with identical measurement conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Cation-Diffusive Carbon Interlayers Stabilize Na Metal and Double the Current in Na-S Redox-Flow Batteries for Grid-Scale Energy Storage

The sodium-sulfur nonaqueous redox-flow batteries (Na-S NARFBs) using earth-abundant elements are highly attractive due to the low material cost and improved energy density for grid-scale energy storage. However, the low current performance, poor Na0/Na+ redox kinetics, and Na dendrite growth pose severe challenges. We introduce cation-diffusive layers (CDLs): thin and Na+ affinitive interlayers at the Na anode that direct Na+ transport and stabilize Na deposition. Benchmarking three archetypal materials—carbon paper (CP), glass microfiber paper (GF), and foam—across Na-Na and Na-Cu, and Na-S cells identifies CP as the optimum. CP reduces symmetric cell overpotential by more than 70%, achieves 98% Na plating-stripping efficiency, and doubles the Na-S cell current density from 0.5 to 1.0 mA cm−2 without sacrificing capacity or efficiency. Ex situ electrochemical and SEM/XPS analysis, combined with molecular dynamics (MD) studies, reveal that electron-rich carbon fibers disperse supporting salt aggregates, enrich near-surface Na+ density, and create ion transport pathways for fast Na0/Na+ exchange while mitigating membrane degradation. Because of the ion-centric mechanism, CDLs can be generalized to other metal-anode designs. Further, this work establishes CDL design rules—cationic affinity and appropriate micro/nanostructure—as a simple, scalable route to high-current, durable metal-anode flow batteries.

Wu, Wenda [ORNL] (ORCID:000900033307687X)↗
NASA NTRS1962

Some Experiments on the Passage of High-Energy Protons in Dense Matter

A series of experiments designed to study the nuclear cascade resulting from the passage of 1 to 3 GeV protons in matter has been in progress at the Brookhaven Cosmotron. Preliminary results on the fluxes of fast neutrons (upper limits) and of strongly interacting particles above 50 MeV are summarized here (Fig. 1 and Table 1). The four cases studied are: 1-GeV protons on Fe, on chondritic material, and on C 5 H 8 O 2 , and 3-GeV protons on Fe.

Proton Irradiation↗
DOE OSTI2024

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET↗
NASA NTRS2023

Cryogenic Flow Boiling in Microgravity: Effects of Reduced Gravity on Two-Phase Fluid Physics and Heat Transfer

With the growing interest in space exploration, cryogenic technologies involving two-phase flow and heat transfer are in high demand to successfully procure advanced space applications such as fuel depots and nuclear thermal propulsion (NTP) systems for deep space missions. However, the unique and extreme thermal properties of cryogenic fluids introduce distinct flow boiling fluid physics and energy transport phenomena, which differ significantly from those observed with conventional fluids. Understanding the unique two-phase physics in cryogenic flow boiling remains an ongoing challenge. Furthermore, the lack of readily available microgravity cryogenic steady-state heat transfer data hinders the assessment of gravitational effects on cryogenic flow boiling. This study aims to elucidate the gravitational effects on two-phase fluid physics and heat transfer by conducting the first-ever experimental measurement of cryogenic flow boiling performance using a steady-state heated method in a reduced gravity environment. Parabolic flight experiments were performed to acquire both heat transfer measurements and high-speed video of interfacial behaviors, under varying gravity levels (microgravity, hypergravity, Lunar gravity, and Martian gravity). The experiments involved flow boiling of liquid nitrogen (LN 2 ) with a near-saturated inlet along a circular heated tube of dimensions 8.5-mm inner diameter and 680-mm heated length. The operating parameters varied are mass velocity of 398.3 - 1342.8 kg/m2s, inlet quality of -0.08 to -0.01, and inlet pressure of 413.68 - 689.48 kPa. Captured microgravity flow patterns range from bubbly to annular, all having vapor structures that are larger than those under higher gravity levels. Under microgravity, absence of buoyancy yields symmetrical vapor structures without flow stratification, laying a physical foundation for the distinct two-phase heat transfer trends during LN 2 flow boiling in microgravity. Transient data collected during the flight parabolas exhibited decreasing heated wall temperature as the aircraft transitioned from hypergravity to microgravity phases. The temperature variation indicated an enhancement in flow boiling heat transfer with decreasing gravity levels and a reduction with increasing gravity levels. The effect of reduced gravity on cryogenic flow boiling heat transfer coefficient (HTC) is discussed based on steady state heat transfer analysis. Seminal HTC correlations are evaluated against the measured microgravity HTC data, of which one is identified for superior accuracy in predicting microgravity data. Finally, a new HTC correlation is proposed to improve accuracy of microgravity predictions, yet there still exists room for further improvement with future terrestrial flow boiling experiments at different flow orientations relative to Earth gravity.

Microgravity↗
DOE OSTI2026

Fine-Grained Power and Energy Attribution on AMD GPU/APU-Based Exascale Nodes

Modern exascale GPU- and APU-based systems provide multiple power and energy sensors, but differences in scope, update rate, timing, and filtering complicate the attribution of short-lived accelerator activity. This paper presents a methodology to characterize and correct these effects on Cray EX systems with AMD Instinct MI250X GPUs (Frontier) and MI300A APUs (Portage). Using controlled square-wave workloads, we quantify update intervals, delay, aliasing, and variability across up to 512 GPUs and 480 APUs with on-chip (rocm-smi/amd-smi) and off-chip Cray Power Management sensors. We reconstruct power from cumulative energy counters to achieve faster response times, validate it against on-chip, off-chip, and node-level sensors, and integrate the resulting streams into a Score-P/PAPI-based tool for time-aligned, phase-level attribution. Applied to rocHPL, rocHPL-MxP, and HPG-MxP, the method separates energy savings due to reduced runtime from changes in power. Mixed precision reduces node energy on Frontier by 79% for rocHPL-MxP and 31% for HPG-MxP, with similar trends on Portage. These results provide portable guidance for sensor validation and power-aware optimization on current and future exascale systems.

Mcdaniel, Adam [ORNL] (ORCID:000000016926028X)↗
DOE OSTI2023

Dense nuclear matter equation of state from heavy-ion collisions

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter under conditions not reached before, endeavors to develop sophisticated and reliable transport simulations to interpret these experiments, and the advent of multi-messenger astronomy, the next decade will bring new opportunities for determining the nuclear matter EOS, elucidating its dependence on density, temperature, and isospin asymmetry. Among controlled terrestrial experiments, collisions of heavy nuclei at intermediate beam energies (from a few tens of MeV/nucleon to about 25 GeV/nucleon in the fixed-target frame) probe the widest ranges of baryon density and temperature, enabling studies of nuclear matter from a few tenths to about 5 times the nuclear saturation density and for temperatures from a few to well above a hundred MeV, respectively. Collisions of neutron-rich isotopes further bring the opportunity to probe effects due to the isospin asymmetry. However, capitalizing on the enormous scientific effort aimed at uncovering the dense nuclear matter EOS, both at RHIC and at FRIB as well as at other international facilities, depends on the continued development of state-of-the-art hadronic transport simulations. Furthermore, this white paper highlights the essential role that heavy-ion collision experiments and hadronic transport simulations play in understanding strong interactions in dense nuclear matter, with an emphasis on how these efforts can be used together with microscopic approaches and neutron star studies to uncover the nuclear EOS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Ramp-release experiments for strength measurements: Strain-rate dependence

This paper presents an enhanced analysis method for investigating material properties at high strain rates, extending the capability of established experimental techniques to gain more information. The ramp-release method has been applied to many experiments reported at high (≈10 5 − 10 6 s −1 ) strain-rates. More recent data gathered at the National Ignition Facility (NIF) has enabled higher (≈10 8 s −1 ) strain-rates to be studied. Here, we present an initial application of ramp-release analysis to NIF ramp-compression data, illustrating both the opportunities and the practical challenges of extending these methods to laser-driven platforms. The higher strain-rates accessed at the NIF mean that there is more strain-rate enhancement to strength, and the experimental configuration means that this enhancement is more readily seen in the data. This is enabled by the capability of avoiding peak-compression attenuation through the sample thickness with a designed hold period made possible by the pulse-shaping capability of NIF. We propose that this combination of experimental conditions and an enhanced analysis method enables the strain-rate enhancement to strength to be studied, and potentially for this to inform physics models at smaller scales than the continuum.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗
DOE OSTI2026

An integrated in-situ coordination strategy enabling high-performance layered cathodes for sodium-ion batteries

O3-type layered transition metal oxide cathodes hold tremendous potential in sodium-ion batteries (SIBs) due to their low cost and high energy density. However, the structure instability associated with detrimental phase transitions and severe interface parasitic reactions exacerbate the material's electrochemical performance degradation. Herein, we develop an integrated in-situ coordination strategy via heteroatomic modulation inducing coherent epitaxial layer to collaboratively enhance the overall framework robustness from surface to bulk. The theoretical calculation and multiple in/ex-situ characterizations demonstrate the charge density around oxygen is redistributed, which promotes the electron localization, thus widening the NaO 2 lattice space and accelerating the Na + transport dynamics. Furthermore, the formed strengthened oxygen bond energy effectively distributes the long-range coordination of Mn 3+ O 6 octahedron, thereby alleviating Jahn-Teller distortion and local stress. Importantly, the in-situ formed conformal buffer layer dramatically relieves the adverse interface side reactions, facilitating the construction of robust cathode-electrolyte interface, which ameliorate the whole structure stability of designed materials. Consequently, the optimized NFMZ@NZO-1.0 exhibits the excellent cycling stability with 80.2% capacity retention after 300 cycles at 1C, and delivers a high discharge capacity of 107.1 mAh g −1 at 10C. In conclusion, this distinctive coupling strategy provides valuable insights for developing high-performance layered cathode materials in SIBs.

Coherent epitaxial layer↗