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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗
DOE OSTI2023

Cost-efficiency enhancement of X- and Ku-band split waveguides for industrial accelerators

Compact microwave electron linear accelerators must operate at high frequencies in order to maintain tight SWaP (size, weight, and power) requirements, set by modern applications. Currently, the frequencies are practically limited to X- and Ku-bands because of the availability of MW-class magnetrons, required to achieve beam energies of several MeV, and tight fabrication tolerances. The latter is associated with micron-level accuracy and further waveguide frequency tuning process, both increasing its costs dramatically. By implying a novel split structure fabrication approach, it is possible to relax these tolerances to the values of 10–20 μm and eliminate the tuning step, greatly reducing their total costs. Finally, this paper presents the results of microwave measurements of split X- and Ku-band accelerating structures of different types and discusses the benefits of our fabrication approach.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Physics Design of Proton/Ion SRF Accelerators

Superconducting Radio Frequency (SRF) technology has become foundation of the modern high energy particle accelerators. The technology enables a higher accelerating field with minimal power dissipation and a stronger compact magnetic field. These advancements have broadened the operational horizon of the particle accelerators making a higher duty factor and Continuous Wave (CW) beam operations both feasible and economically viable. The intensity frontier research founded on generation of intense beam of exotic particles including but not limited to neutrinos, muons, kaons and neutrons as well as practical applications involving transmutation of nuclear reactor waste, rare isotopes generation, sub-critical nuclear power generation etc. could be accomplished efficiently only by using superconducting proton/ions particle accelerators. As a result, many newly constructed or under construction high energy accelerator facilities around the world such as Proton Improvement Plan-II (PIP-II) at Fermilab, FRIB at MSU, ESS at Sweden are utilizing SRF accelerators. This talk presents the design philosophy of SRF proton/ion particle accelerator, with a focus on optimizing its performance while addressing physics and operational challenges including the fault scenarios, machine availability and preservation of crucial beam parameters.

Saini, Arun↗
DOE OSTI2023

A scalable wave resource assessment methodology: Application to U.S. waters

Waves deliver large quantities of energy to populated coastlines around the world, and wave energy technology research and development has accelerated over the last two decades. Throughout this time national and regional resource assessments have utilized disparate methodologies, which can cause confusion and skepticism. Here, in this work, we describe a theoretical wave resource assessment methodology that addresses many of the major areas of inconsistency and debate. Applying this revised methodology to U.S. waters, we find the theoretical U.S. wave energy resource to be 3300 TWh/yr, with region totals of 2000 TWh/yr in Alaska, 510 TWh/yr along the U.S. west coast, 380 TWh/yr in Hawaii, 290 TWh/yr along the east coast, 69 TWh/yr in the Gulf of Mexico, and 17 TWh/yr in Puerto Rico and the U.S. Virgin Islands. We also find significant uncertainty in these estimates associated with the underlying model dataset, which emphasizes the importance of thorough model validation and calibration as well as quantifying uncertainty.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Assessment of Aging Degradation Mechanisms of Alloy 709 for Sodium Fast Reactors

This project was initiated in October 2015 to investigate the creep and creep-fatigue behavior of Alloy 709 for structural components in Gen IV sodium cooled fast spectrum reactors. The goal of this project is to develop an understanding of the mechanisms responsible for the behavior of austenitic stainless steel alloy 709 under accelerated testing conditions to confidently predict long term creep and creep-fatigue behavior at the times (500,000 hours) and temperatures (550°C) of interest for fast reactor structural applications. Alloy 709 has exhibited significantly better creep resistance than Alloy 316H, which is currently specified in design of fast reactor structural components. However, the alloy has not been code qualified for elevated temperature nuclear design. The elevated temperature microstructure stability and creep and creep-fatigue behavior need to be better understood so service life can be accurately predicted. Alloy 709 was developed for fossil boiler applications, which operate at a higher temperature than the nuclear components. Thus, there is a strong need to characterize its creep and creep-fatigue behavior at these lower temperatures and corresponding longer service lifetimes. The overall objective of this project is to develop sufficient understanding of the mechanisms responsible for behavior of Alloy 709 under accelerated testing conditions to confidently predict long term creep and creep-fatigue behavior at the times (500,000 hours) and temperatures (550°C) of interest for fast reactor structural applications. The following report summarizes the findings of the creep-fatigue and creep behavior with respect to the research questions identified during the course of the project. Additionally, the training and professional development that occurred through the project and the products resulting from the project are summarized.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of Accelerated High Temperature Mechanical Testing Techniques

The Advanced Materials and Manufacturing Technologies (AMMT) Program focuses on advancing materials and manufacturing techniques for nuclear energy applications, particularly in the qualification of materials for high-temperature structural use. This report presents work on refining the creep testing of small specimen geometries. Efforts include the development of a new specimen geometry for sub-sized specimens, which were subjected to uniaxial creep tests. The results contribute to the understanding of material behavior under stress at elevated temperatures and offer potential improvements in creep data collection methods. These findings support ongoing advancements in material qualification processes essential for nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid discovery of high hardness multi-principal-element alloys using a generative adversarial network model

Multi-principal element alloys (MPEAs) continue to gain research prominence due to their promising high-temperature microstructural and mechanical properties. Recently, machine learning (ML) and materials informatics have been used extensively for screening MPEAs, however, most of these efforts were focused on constructing classification and regression models for predicting phase stability and mechanical properties of known compositions. These approaches may accelerate the screening process but optimizing new compositions with desirable properties within a practical time frame from an infinitely large design space of MPEA systems remains a grand challenge. To tackle this composition optimization challenge, a generative adversarial network coupled with a neural-network ML model was utilized to design MPEAs by filtering compositions that have high hardness. Even in a high-dimensional space with 18 elements as descriptors, the ML model was able to generate optimized compositions from which one composition was found to have 10% higher hardness (941 HV) than the maximum in the training data (857 HV). Density-functional theory was used to provide thermodynamic and electronic insights to higher hardness of the new MPEA found. The present work can optimize compositions from a wide design space of 18 elements (including W, Ta and Nb) that presents an opportunity to synthesize new compositions for applications ranging from corrosion-resistant alloys to nuclear materials. Here the findings suggest that generative ML can greatly accelerate materials discovery by identifying novel compositions, which can serve as a data-informed tool to guide experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High-$Q_0$ treatment of CEBAF 1.5 GHz SRF cavities

The Continuous Electron Beam Accelerator Facility (CEBAF) was the first large-scale accelerator to employ superconducting radiofrequency (SRF) cavities for continuous-wave operation. Ongoing research and development efforts continue to focus on increasing the intrinsic quality factor (Q 0 ) of these cavities in order to reduce cryogenic losses while maintaining operational gradients. Here, in this work, we report on the application of high-Q 0 surface treatments to single-cell and multicell C100 and C75 style 1.5 GHz niobium cavities used in the CEBAF accelerator. Nitrogen infusion and oxygen alloying via medium-temperature baking were applied under heat-treatment constraints relevant to existing cavity hardware. Both processes yielded substantial improvements in Q 0 at moderate accelerating gradients, achieving values of approximately 2 × 10 10 at 2.07 K and 20 MV/m. The effectiveness of nitrogen infusion at reduced annealing temperatures and the successful extension of oxygen alloying to multicell cavities are demonstrated. These results establish viable pathways for implementing high-Q 0 treatments in CEBAF-compatible cavities and support future integration into cryomodules for reduced operational cryogenic load.

Dhakal, Pashupati [Thomas Jefferson National Accel↗
DOE OSTI2022

Networks and interfaces as catalysts for polymer materials innovation

Autonomous experimental systems offer a compelling glimpse into a future where closed-loop, iterative cycles—performed by machines and guided by artificial intelligence (AI) and machine learning (ML)—play a foundational role in materials research and development. This perspective draws attention to the roles of networks and interfaces—of and between humans and machines—for the purpose of generating knowledge and accelerating innovation. Polymers, a class of materials with massive global impact, present a unique opportunity for the application of informatics and automation to pressing societal challenges. To develop these networks and interfaces in polymer science, the Community Resource for Innovation in Polymer Technology (CRIPT)—a polymer data ecosystem based on novel polymer data model, representation, search, and visualization technologies—is introduced. The ongoing co-design efforts engage stakeholders in industry, academia, and government to uncover rapidly actionable, high-impact opportunities to build networks, bridge interfaces, and catalyze innovation in polymer technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗
DOE OSTI2024

Hard X-ray inverse Compton scattering at photon energy of 87.5 keV

Abstract Production of hard X-ray via inverse Compton scattering at photon energies below 100 keV range aimed at potential applications in medicine and material research is reported. Experiments have been performed at the Brookhaven National Laboratory, Accelerator Test Facility, employing the counter collision of a 70 MeV, 0.3 nC electron beam with a near infra-red Nd: YAG laser (1064 nm wavelength) pulse containing ~ 100 mJ in a single shot basis. The radiation distribution of the scattered photon beam is assessed to be sufficiently quasi monochromatic to produce clear contrast from the Au K - edge at 80.7 keV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Degradation of REBCO coated conductors due to a combination of epoxy impregnation, thermal cycles, and quench: Characteristics and a method of alleviation

REBa2Cu3Ox (REBCO) coated conductors are an enabling technology for >1 GHz nuclear magnetic resonance spectrometers that need >23.5 T solenoids, compact high-field fusion reactors beyond the International Thermonuclear Experimental Reactor, and 20 T class accelerator magnets. An in-depth understanding of stress and strain management is critically needed for these applications. Here, we report experimental data and an analysis of damages of REBCO-coated conductors in several scenarios relevant for their applications in high-field magnets and unique to their multi-layer thin film structure. The examined scenarios include failure induced by quench, failure induced by epoxy impregnation, and failure induced by a combination of epoxy impregnation and quench. The root cause is film blistering and peeling induced by thermally interfacial stresses characteristic of multilayered heteroepitaxial thin film structures on thick substrates utilized. The quantitative stress analysis is introduced using simple and easy to use formulas and clearly indicates how materials and structural characteristics affect the magnitude and the distribution of stresses and deflections. Finally, a simple method is introduced for removing degradation of REBCO coated conductors due to epoxy impregnation. Our data and analysis help our understanding of the practical limit of REBCO-coated conductors and can be utilized as a guidance for the physical design of REBCO coated conductors and high-current cables assembled from them and for minimizing damages.

Yin, Shijian (ORCID:0000000224312274)↗
DOE OSTI2022

Experimental verification of TNSA protons and deuterons in the multi-picosecond moderate intensity regime

Ion acceleration from high intensity short pulse laser interactions is of great interest due to a number of applications, and there has been significant work carried out with laser energies up to a few 100 J with 10's of femtosecond to 1 ps pulse durations. Here, we report results from an experiment at the OMEGA EP laser, where laser energy and pulse length were varied from 100 to 1250 J and 0.7–30 ps, respectively, in the moderate (2 × 10 17 –2 × 10 18 W/cm 2 ) laser intensity regime. Ions and electrons were simultaneously measured from disk targets made of CH and CD by a Thomson parabola and a magnetic spectrometer, respectively. Measurements showed that the electron temperature, T e (MeV), has a dependence on the laser energy, E L (J), and pulse duration, τ L (ps), and its empirical scaling was found to be 0.015 × E L 0.90 τ L –0.48. The maximum proton and deuteron energies are linearly dependent on the electron temperature, (5.60 ± 0.26) × T e and (3.17 ± 0.18) × T e , respectively. A significant increase in proton numbers with the laser energy was also observed. Furthermore, the increase in the maximum proton energy and proton count with higher energy longer duration pulses presented in this article shows that such laser conditions have a great advantage for applications, such as the proton radiograph, in the moderate laser intensity regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Decomposition characteristics of C4F7N-based SF6-alternative gas mixtures

C4F7N [2,3,3,3-tetrafluoro-2-(trifluoromethyl)propanenitrile]/CO2 gas mixtures are being developed as an eco-friendly electrical insulator to replace SF6, the most potent greenhouse industrial gaseous dielectric. However, recent studies have reported complicated and often conflicting decomposition pathways for C4F7N/CO2 gas mixtures, which has raised concerns. In this work, the decomposition characteristics of C4F7N/CO2 gas mixtures were studied comprehensively by both designed computations and experiments. Computations were performed starting from fundamental propositions of C4F7N/CO2 decompositions, which were further experimentally verified by pyrolysis, long-term thermal aging with/without catalytic materials (industrial-grade molecular sieves 4A), and electrical decomposition by spark discharge. The results of both computations and experiments suggest that in an ideal thermal decomposition, C4F7N is likely to decompose into C2F6 and small fluoronitriles first at high temperatures. The generation of C3F6 and C2N2 from C4F7N thermal decomposition at lower temperatures appears because of the catalytic effect of incompatible materials, for example, the industrial-grade molecular sieves 4A that we tested. The electron impact dissociation of C4F7N plays an important role in C4F7N electrical decomposition, leading to additional formation of distinctive small molecules of CF4 and C2N2 of low concentrations. It was pointed out based on a real arcing test in a load disconnector that the decomposition of C4F7N gas mixtures in real applications will be at a much moderate and manageable rate than what was obtained from the highly accelerated laboratory tests presented in this work. The signatures of decomposition products extracted in this study provide invaluable guidance for developing decomposition-based diagnosis and fixation of decomposition byproducts toward SF6-free power grids.

Physics↗
DOE OSTI2025

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. Refined nuclear interaction models in these energy regimes will also be valuable for other applications, such as measurements of reactor, solar, and atmospheric neutrinos. This manuscript discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Machine learning predicts new anti-CRISPR proteins

The increasing use of CRISPR–Cas9 in medicine, agriculture, and synthetic biology has accelerated the drive to discover new CRISPR–Cas inhibitors as potential mechanisms of control for gene editing applications. Many anti-CRISPRs have been found that inhibit the CRISPR–Cas adaptive immune system. However, comparing all currently known anti-CRISPRs does not reveal a shared set of properties for facile bioinformatic identification of new anti-CRISPR families. Here, we describe AcRanker, a machine learning based method to aid direct identification of new potential anti-CRISPRs using only protein sequence information. Using a training set of known anti-CRISPRs, we built a model based on XGBoost ranking. We then applied AcRanker to predict candidate anti-CRISPRs from predicted prophage regions within self-targeting bacterial genomes and discovered two previously unknown anti-CRISPRs: AcrllA20 (ML1) and AcrIIA21 (ML8). We show that AcrIIA20 strongly inhibits Streptococcus iniae Cas9 (SinCas9) and weakly inhibits Streptococcus pyogenes Cas9 (SpyCas9). We also show that AcrIIA21 inhibits SpyCas9, Streptococcus aureus Cas9 (SauCas9) and SinCas9 with low potency. The addition of AcRanker to the anti-CRISPR discovery toolkit allows researchers to directly rank potential anti-CRISPR candidate genes for increased speed in testing and validation of new anti-CRISPRs. A web server implementation for AcRanker is available online at http://acranker.pythonanywhere.com/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantum magic and multipartite entanglement in the structure of nuclei

Motivated by the Gottesman-Knill theorem, we present a detailed study of the quantum complexity of p -shell and s d -shell nuclei. Valence-space nuclear shell-model wave functions generated by the code are mapped to qubit registers using the Jordan-Wigner mapping (12 qubits for the p shell and 24 qubits for the s d shell), from which measures of the many-body entanglement ( n -tangles) and magic (nonstabilizerness) are determined. While exact evaluations of these measures are possible for nuclei with a modest number of active nucleons, Monte Carlo simulations are required for the more complex nuclei. The broadly applicable Pauli-string I ̂ Z ̂ exact (PSIZe) Markov chain Monte Carlo (MCMC) technique is introduced to accelerate the evaluation of measures of magic in deformed nuclei (with hierarchical wave functions), by factors of ≈ 8 for some nuclei. Significant multinucleon entanglement is found in the s d shell, dominated by proton-neutron configurations, along with significant measures of magic. This is evident not only for the deformed states, but also for nuclei on the path to instability via regions of shape coexistence and level inversion. These results indicate that quantum-computing resources will accelerate precision simulations of such nuclei and beyond. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗