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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Focusing of laser-accelerated ions with spherically curved targets

A theoretical model for laser-accelerated ion focusing from spherically curved targets using a Gaussian self-similar solution is presented. This model describes the evolution of the focal location and focal radius with final ion energy and the initial radial boundary of the ions, the latter being a function of both target geometry and the ion acceleration radius for a given ion energy. The theory is supported by particle-in-cell simulations of a variety of target shapes with varying radii of curvature and target opening angles, as well as variations in the injected electron beam radius and energy spectrum. The theory and simulations suggest that the focal location varies linearly with the radius of curvature, with the square root of the ratio of ion energy to effective electron temperature, and monotonically increases with the energy-dependent ratio of the initial ion radial boundary to the radius of curvature. Considering ponderomotive acceleration, this suggests that the focal length should scale inversely with intensity, $(I_Lλ_L^2)$ −1/4 , suggesting a 10× increase in intensity will reduce the focal distance by ̃1.8× for a given ion energy.

Physics - Plasma physics↗
DOE OSTI2025

Randomized Algorithms for Low-Rank Matrix and Tensor Decompositions

This paper surveys randomized algorithms in numerical linear algebra for low-rank decompositions of matrices and tensors. The survey begins with a review of classical matrix algorithms that can be accelerated by randomized dimensionality reduction, such as the singular value decomposition (SVD) or interpolative (ID) and CUR decompositions. Recent advances in randomized dimensionality reduction are discussed, including new methods of fast matrix sketching and sampling techniques, which are incorporated into classical matrix algorithms for fast low-rank matrix approximations. The extension of randomized matrix algorithms to tensors is then explored for several low-rank tensor decompositions in the CP and Tucker formats, including the higher-order SVD, ID, and CUR decomposition.

Pearce, Katherine J. [The University of Texas at A↗
DOE OSTI2024

Theory of Beam Echoes

We develop the theory of beam echoes in circular accelerators under several different conditions. We derive detailed expressions for the echo amplitude and pulse width with nonlinear quadrupole and dipole kicks, first without and then with momentum spread. We use the theory with the linearized dipole and quadrupole kicks to solve the diffusion equation for different dependencies of the diffusion coefficient on the action. We then consider the use of multiple quadrupole kicks to increase the maximum echo amplitude. We have extended these calculations partially to the 2D case and we also have partial results for longitudinal echoes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

ORBITAL ANGULAR MOMENTUM BEAMS RESEARCH USING A FREE-ELECTRON LASER OSCILLATOR

We present a Fixed-Field-Alternating (FFA) permanent magnet racetrack electron accelerator with energy range between 10-60 GeV for the future LHeC. Electron beam is brought back to the linac by the single beam line without requiring electric power REDUCING estimated wall power of 100 MW in the present LHeC design to a negligible power for arcs as the permanent magnets are used. The design is based on experience from the very successful commissioning of the Cornell University and Brookhaven National Laboratory Energy Recovery Test Accelerator ? ?CBETA?. The proposal supports sustainability efforts for LHeC by making a 'green' accelerator. It is an energy recovery linac with 99.9% energy efficiency and reduces the power consumption by using small permanent magnets. The FFA non-linear gradient design is a racetrack shape, where, as in the CBETA, the arcs are matched by adiabatic transition to the two (LHeC) or multiple straight sections. Two 10 GeV superconducting linacs are placed on both sides of the Interaction Region (IR) significantly reducing the power of synchrotron radiation loss.

Trbojevic, D.↗
DOE OSTI2024

Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques

For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

An efficient second-order adaptive procedure for inserting CAD geometries into hexahedral meshes using volume fractions

Here, this paper is concerned with inserting three-dimensional computer-aided design (CAD) geometries into meshes composed of hexahedral elements using a volume fraction representation. An adaptive procedure for doing so is presented. The procedure consists of two steps. The first step performs spatial acceleration using a k-d tree. The second step involves subdividing individual hexahedra in an adaptive mesh refinement (AMR)-like fashion and approximating the CAD geometry linearly (as a plane) at the finest subdivision. The procedure requires only two geometric queries from a CAD kernel: determining whether or not a queried spatial coordinate is inside or outside the CAD geometry and determining the closest point on the CAD geometry’s surface from a given spatial coordinate. We prove that the procedure is second-order accurate for sufficiently smooth geometries and sufficiently refined background meshes. We demonstrate the expected order of accuracy is achieved with several verification tests and illustrate the procedure’s effectiveness for several exemplar CAD geometries.

Adaptive↗
DOE OSTI2025

Ultranarrow electroluminescence from magnetic excitons in the van der Waals antiferromagnetic semiconductor NiPS 3

Electrically driven light emission from two-dimensional (2D) semiconducting materials has enabled numerous optoelectronic technologies, including light-emitting diodes, solid-state lasers, and single-photon sources for quantum communication. Here we report ultranarrow electroluminescence from the magnetic excitonic state of the van der Waals antiferromagnetic semiconductor NiPS 3 . This electroluminescence is enabled by the fabrication of gate-tunable NiPS 3 devices that remain electrically conductive below the antiferromagnetic ordering temperature of 155 K, ultimately allowing field-effect mobilities of 1.3 cm 2 V –1 s –1 and 4.5 cm 2 V –1 s –1 to be directly measured at room temperature and 7 K, respectively. By applying a high-frequency square wave voltage to the gate electrode of the resulting field-effect transistors, electroluminescence is capacitively induced from the magnetic excitons of NiPS 3 . Due to the coupling of these excitons with the underlying NiPS 3 antiferromagnetic order, the electroluminescence has an ultranarrow linewidth of 1 meV and a high degree of linear polarization (ρ = 0.78). In addition to facilitating fundamental studies of the coupling between spin states and excitons in van der Waals magnetic semiconductors, this work will accelerate the development of emerging 2D opto-spintronic applications.

two-dimensional materials↗
DOE OSTI2025

Beam Non-Uniformity Characterization at the SpinQuest and DarkQuest Experiments

The SpinQuest experiment, including upgrades to SpinQuest designed to increase sensitivity to dark sector searches (commonly known as DarkQuest), utilizes the high-intensity 120 GeV proton beam delivered by the Fermilab Accelerator Complex to probe the inner structure of nucleons and search for new physics beyond the Standard Model. The SpinQuest beam is extracted from the Main Injector synchrotron at Fermilab in what is known as a slow spill . The slow spill involves a complex non-linear half-integer extraction method, which results in non-uniform beam behavior. SpinQuest observes spikes of very high intensity beam which can saturate detectors and reduce trigger efficiency, significantly impacting the experiment's sensitivity. In this project we address this challenge by developing an analysis framework to characterize the beam delivered to SpinQuest. By discovering trends within each spill and by comparing thousands of spills, we can better inform the Accelerator Division and improve the slow spill extraction. We have also begun a collaboration with the Accelerator Division in order to simulate the slow spill and improve the magnet ramp process controls which will improve the uniformity of the beam. These improvements will directly enhance the physics reach of SpinQuest/DarkQuest, increasing their sensitivity to key measurements such as the Sivers function and searches for new physics.

Dolen, James William [Purdue U., Calumet] (ORCID:0↗
DOE OSTI2024

Observation of Skewed Electromagnetic Wakefields in an Asymmetric Structure Driven by Flat Electron Bunches

Relativistic charged -particle beams that generate intense longitudinal fields in accelerating structures also inherently couple to transverse modes. The effects of this coupling may lead to beam breakup instability and thus must be countered to preserve beam quality in applications such as linear colliders. Beams with highly asymmetric transverse sizes (flat beams) have been shown to suppress the initial instability in slab -symmetric structures. However, as the coupling to transverse modes remains, this solution serves only to delay instability. In order to understand the hazards of transverse coupling in such a case, we describe here an experiment characterizing the transverse effects on a flat beam, traversing near a planar dielectric lined structure. Further, the measurements reveal the emergence of a previously unobserved skew-quadrupolelike interaction when the beam is canted transversely, which is not present when the flat beam travels parallel to the dielectric surface. We deploy a multipole field fitting algorithm to reconstruct the projected transverse wakefields from the data. We generate the effective kick vector map using a simple two -particle theoretical model, with particle -in -cell simulations used to provide further insight for realistic particle distributions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Demonstration of improvement of energy conversion rate from kJ PW laser to protons with electron confinement

Kilojoule-class relativistic intensity lasers can produce energetic protons with high energy conversion efficiencies in the interaction with a thin foil target. Using the national ignition facility advanced radiographic capability (NIF-ARC) laser, we demonstrated an enhancement of energy conversion from laser to protons by the effective confinement of fast electrons in the laser spot by random kicks from the self-excited field. The number of fast electrons was increased by 4.6 times by increasing the ratio of the laser spot size to the foil thickness to strengthen the confinement effect. The energy conversion efficiency from laser to protons increases approximately linearly with the enhancement of the number of fast electrons. The conversion rate for protons with energies above 8 MeV was 1.8 %. The result leads to high efficiency proton acceleration which is beneficial in applications, such as proton radiography and plasma heating in laser fusion.

Physics↗
DOE OSTI2024

Performance and Durability of Heavy-Duty Fuel Cell Systems with an Advanced Ordered Intermetallic ORR Alloy Catalyst and Novel Support

Ordered PtCo intermetallic (OIM) catalyst (L1 0 -PtCo/C) is a promising candidate as the oxygen reduction reaction (ORR) catalyst in hybrid fuel cell systems (FCS) for class-8 heavy duty (HD) trucks. Compared to a baseline annealed Pt on high surface area carbon (a-Pt/HSC) catalyst, its mass activity (MA) is 71% higher initially and 144% higher after 90,000 potential cycles in an accelerated stress test (AST). Analysis of the AST data indicates that the ORR kinetic constants do not change with aging and the degradation in the OIM catalyst activity is linearly proportional to the loss in the electrochemically active surface area (ECSA). Several operational strategies are investigated to mitigate catalyst degradation and achieve 25,000-h electrode lifetime and 2.5 kW g −1 Pt utilization on a HD truck duty cycle including load sharing with the hybrid battery, regulating the radiator fan power to maintain the coolant temperature close to 60 °C, clipping the maximum cell voltage below 850 mV, limiting the ECSA loss to 55%, and oversizing the active area of the membrane electrode assemblies by 20%. Drive cycle simulations indicate that the lifetime average voltage degradation rate is about 1.8 μV h −1 and the integrated stack and FCS drive cycle efficiencies decrease by 3.5 to 3.9%.

25 ENERGY STORAGE↗
DOE OSTI2026

Variational Optical Phase Learning on a Continuous-Variable Quantum Compiler

Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an analog quantum operation is digitized by compiling it into a series of basic gates. While there has been significant focus on quantum compiling for discrete-variable systems, the continuous-variable (CV) framework has received comparatively less attention. We present an experimental implementation of a CV quantum compiler that uses two-mode squeezed light to learn a Gaussian unitary operation. We demonstrate the compiler by learning a parameterized linear phase unitary through the use of target and control phase unitaries to demonstrate a factor of 5.4 increase in the precision of the phase estimation and a 3.6-fold acceleration in the time-to-solution metric when leveraging quantum resources. We further show how our approach can be extended to higher-dimensional compilation tasks. Our results are enabled by the tunable control of our cost landscape via variable squeezing, thus providing a critical framework to simultaneously increase precision and reduce time-to-solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Water Temperature, Prey Concentration and Salmonid Density Influence Daily Growth of Wild Juvenile Salmonids in Tributaries of the Upper Salmon River, Idaho ( USA )

ABSTRACT Theory, experiments and field studies indicate that the somatic growth rate of freshwater consumers is shaped by the individual, additive and multiplicative effects of multiple factors, including consumer size and condition, temperature, prey resources and biotic interactions. While our understanding of how these factors affect wild populations of freshwater consumers is improving, the topic remains poorly studied, especially with respect to mobile species. Here, we report on an 8‐year, seven‐stream ( n = 49 stream‐year combinations) observational study examining the individual and interactive effects of invertebrate prey concentration (F, mg/m 3 ), mean daily water temperature (T, °C) and juvenile Chinook salmon ( Oncorhynchus tshawytscha ) density (D, fish/100 m 2 ) on summer daily growth rates (%/d) of mobile, anadromous, juvenile Chinook salmon (age‐0+, n = 382) and sub‐yearling (age‐0+, n = 61) and yearling (age‐1+) steelhead trout ( O. mykiss , n = 70) rearing in cold (mean daily summer: 12.1°C, range: 4.2°C–16.7°C) mountain tributaries of the Salmon River basin in central Idaho (USA). AIC c model selection indicated that daily juvenile salmonid growth positively correlated with water temperature, prey biomass concentration, local juvenile Chinook density and the interaction between water temperature and food but with species and age‐specific differences. Water temperature was a covariate in all top‐ranked models, with daily growth (%/day) rate increasing (0.05%–0.23%/d) linearly with mean daily summer water temperature. In addition to a direct positive relationship with daily growth rate, there was evidence that prey concentration positively interacted with water temperature to accelerate daily growth (F × T). The positive relationship between juvenile salmonid daily growth rate and juvenile Chinook density is difficult to explain and could result from confounding factors. The individual success observed in these streams may contribute to population‐level benefits for the focal consumers, as prey‐rich, warm summers may result in larger individuals with higher energy reserves at the end of the summer/autumn growing season, contributing to improved overwinter survival. Our results, taken in combination with evidence from models, experiments and observational studies, have climate change implications. Current and predicted increases in water temperature will necessitate higher rates of prey consumption by aquatic ectothermic consumers to offset accelerated metabolic demands. Thus, to improve the resilience of mobile freshwater consumers in a warming climate, we suggest that natural resource managers not only consider physical and chemical habitat conditions but also biotic conditions, including the spatiotemporal quantity and quality of prey resources.

Kiffney, Peter. M. [Fish Ecology, Northwest Fisher↗
DOE OSTI2025

Kinetic Simulations of the Kruskal–Schwarzschild Instability in Accelerating Striped Outflows: Dynamics and Energy Dissipation

Astrophysical relativistic outflows are launched as Poynting-flux dominated, yet the mechanism governing efficient magnetic dissipation, which powers the observed emission, is still poorly understood. We study magnetic energy dissipation in relativistic "striped" jets, which host current sheets separating magnetically dominated regions with opposite field polarity. The effective gravity force g in the rest frame of accelerating jets drives the Kruskal–Schwarzschild instability (KSI), a magnetic analog of the Rayleigh–Taylor instability. By means of 2D and 3D particle-in-cell simulations, we study the linear and nonlinear evolution of the KSI. The linear stage is well described by linear stability analysis. The nonlinear stages of the KSI generate thin (skin-depth-thick) current layers, with length comparable to the dominant KSI wavelength. There, the relativistic drift-kink mode and the tearing mode drive efficient magnetic dissipation. The dissipation rate can be cast as an increase in the effective width Δ eff of the dissipative region, which follows dΔ eff /dt ≃ 0.05 $\sqrt{Δ_{eff} g}$. Our results have important implications for the location of the dissipation region in gamma-ray burst and active galactic nuclei jets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

We present a novel machine learning (ML)-based method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural networks (NNC2PS and NNC2PL), trained in PyTorch (2.0+) and optimized for GPU inference using NVIDIA TensorRT (8.4.1), achieving significant speedups with minimal accuracy loss. The NNC2PS model achieves 𝐿 1 and 𝐿 ∞ errors of 4.54 × 10 −7 and 3.44 × 10−6, respectively, while the NNC2PL model exhibits even lower error values. TensorRT optimization with mixed-precision deployment substantially accelerates performance compared to traditional root-finding methods. Specifically, the mixed-precision TensorRT engine for NNC2PS achieves inference speeds approximately 400 times faster than a traditional single-threaded CPU implementation for a dataset size of 1,000,000 points. Ideal parallelization across an entire compute node in the Delta supercomputer (dual AMD 64-core 2.45 GHz Milan processors and 8 NVIDIA A100 GPUs with 40 GB HBM2 RAM and NVLink) predicts a 25-fold speedup for TensorRT over an optimally parallelized numerical method when processing 8 million data points. Moreover, the ML method exhibits sub-linear scaling with increasing dataset sizes. We release the scientific software developed, enabling further validation and extension of our findings. By exploiting the underlying symmetries within the equation of state, these findings highlight the potential of ML, combined with GPU optimization and model quantization, to accelerate conservative-to-primitive inversion in relativistic hydrodynamics simulations.

conservative-to-primitive conversion↗
DOE OSTI2024

Unveiling the effect of composition on nuclear waste immobilization glasses’ durability by nonparametric machine learning

Abstract Ensuring the long-term chemical durability of glasses is critical for nuclear waste immobilization operations. Durable glasses usually undergo qualification for disposal based on their response to standardized tests such as the product consistency test or the vapor hydration test (VHT). The VHT uses elevated temperature and water vapor to accelerate glass alteration and the formation of secondary phases. Understanding the relationship between glass composition and VHT response is of fundamental and practical interest. However, this relationship is complex, non-linear, and sometimes fairly variable, posing challenges in identifying the distinct effect of individual oxides on VHT response. Here, we leverage a dataset comprising 654 Hanford low-activity waste (LAW) glasses across a wide compositional envelope and employ various machine learning techniques to explore this relationship. We find that Gaussian process regression (GPR), a nonparametric regression method, yields the highest predictive accuracy. By utilizing the trained model, we discern the influence of each oxide on the glasses’ VHT response. Moreover, we discuss the trade-off between underfitting and overfitting for extrapolating the material performance in the context of sparse and heterogeneous datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Guided Mode Evolution and Ionization Injection in Meter-Scale Multi-GeV Laser Wakefield Accelerators

Here, we show that multi-GeV laser wakefield electron accelerators in meter-scale, low density hydrodynamic plasma waveguides operate in a new nonlinear propagation regime dominated by sustained beating of lowest order modes of the ponderomotively modified channel; this occurs whether or not the injected pulse is linearly matched to the guide. For a continuously doped gas jet, this emergent mode beating effect leads to axially modulated enhancement of ionization injection and a multi-GeV energy spectrum of multiple quasimonoenergetic peaks; the same process in a locally doped jet produces single multi-GeV peaks with <10% energy spread. A three-stage model of drive laser pulse evolution and ionization injection characterizes the beating effect and explains our experimental results.

43 PARTICLE ACCELERATORS↗