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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Plasma self-driven current in tokamaks with magnetic islands

Magnetic island perturbations may cause a reduction in plasma self-driven current that is needed for tokamak operation. A novel effect on tokamak self-driven current revealed by global gyrokinetic simulations is due to magnetic-island-induced 3D electric potential structures, which have the same dominant mode numbers as that of the magnetic island, whereas centered at both the inner and outer edge of the island. The non-resonant potential islands are shown to drive a current through an efficient nonlinear parallel acceleration of electrons. In large aspect ratio (large-A) tokamak devices, this new effect can result in a significant global reduction of the electron bootstrap current when the island size is sufficiently large, in addition to the local current loss across the island region due to the pressure profile flattening. It is shown that there exists a critical magnetic island width for large-A tokamaks beyond which the electron bootstrap current loss is global and increases rapidly with the island size. As such, this process may introduce a size limit for tolerable magnetic islands in large-A tokamak devices in the context of steady state operation. On the other hand, the current loss caused by magnetic islands in low-A tokamaks such as spherical tokamak (ST) NSTX/U is minor. The reduction of the axisymmetric current by magnetic islands scales with the square of island width. However, the loss of the current is mainly local to the island region, and the pace of current loss as the island size increases is substantially slower compared to large-A tokamaks. In particular, the bootstrap current reduction in STs is even smaller in the reactor-relevant high-β p regime where neoclassical tearing modes are more likely to develop.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Real-Time Inference For MI/RR Deblending

The Fermilab Main Injector (MI) and Recycler Ring (RR) share a common beam loss monitor (BLM) system, making loss events difficult to attribute to their source machine when beam is present in both simultaneously. The Real-time Edge AI for Distributed Systems (READS) project addresses this by deblending BLM readings in real time using machine learning (ML). The current FPGA based implementation meets the sub-3 ms latency requirement but carries a resource intensive hls4ml development cycle, motivating exploration of GPU based deployment. This paper characterizes inference latency on an NVIDIA Jetson Orin Nano and introduces a packet organization scheme for assembling synchronized event frames from seven distributed BLM DAQ streams. Using a Python based DAQ simulation with injected timing jitter in place of unavailable live beam data, the pipeline achieved an average end to end latency of 0.456 ms (σ = 0.122 ms) across 167,000 test frames, comfortably meeting the timing constraint. Early outliers were attributed to TensorRT warm-up rather than steady state limitations, suggesting GPU based inference is a viable alternative to the existing FPGA implementation.

Yu, Kellen [Cornell U.]↗
DOE OSTI2026

Exploration of Real Time Inference for MI-RR Deblending on GPU/TPU Systems

The Fermilab Main Injector (MI) and Recycler Ring (RR) share a common beam loss monitor (BLM) system, making loss events difficult to attribute to their source machine when beam is present in both simultaneously. The Real-time Edge AI for Distributed Systems (READS) project addresses this by deblending BLM readings in real time using machine learning (ML). The current FPGA based implementation meets the sub-3 ms latency requirement but carries a resource intensive hls4ml development cycle, motivating exploration of GPU based deployment. This paper characterizes inference latency on an NVIDIA Jetson Orin Nano and introduces a packet organization scheme for assembling synchronized event frames from seven distributed BLM DAQ streams. Using a Python based DAQ simulation with injected timing jitter in place of unavailable live beam data, the pipeline achieved an average end to end latency of 0.456 ms (σ = 0.122 ms) across 167,000 test frames, comfortably meeting the timing constraint. Early outliers were attributed to TensorRT warm-up rather than steady state limitations, suggesting GPU based inference is a viable alternative to the existing FPGA implementation.

Yu, Kellen [Fermilab; Cornell U.]↗
DOE OSTI2025

Spatial distribution of sp 3 defects in carbon fibers via time-of-flight secondary ion mass spectrometry

Defects play a significant role in the material properties of carbon fibers (CF). Several defects result in the formation of sp 3 bonds in an otherwise sp 2 -dominant graphitic structure. Understanding the distribution of these defects within CF provides insight into their properties and the effect of manufacturing conditions. Reports showed time-of-flight secondary ion mass spectrometry (ToF-SIMS) is capable of characterizing the spatial distribution of sp 2 and sp 3 content in carbon materials. Here, ToF-SIMS was utilized to investigate the spatial distribution of sp 3 defects in T700, T1000, and M46 CF. M46 had the lowest sp 3 content. Center-to-edge analysis revealed that T700 CF had a gradient of sp 3 defects starting from the center and increasing to the edge, whereas M46 CF had a sudden increase in sp 3 defects roughly 1 μm from the edge. Comparatively, T1000 CF had a relatively uniform radial distribution of sp 3 defects, except for a newly identified sp 2 rich region at 0.8 μm from the center. This is hypothesized to originate from a skin–core structure that forms during CF manufacturing. As a result, this work demonstrates the utility of ToF-SIMS for characterizing the spatial distribution of sp 3 defects within CF, establishing new ways to understand CF formation.

Carbon fibers↗
DOE OSTI2024

Suppressing Atmospheric Degradation of Sulfide-Based Solid Electrolytes via Ultrathin Metal Oxide Layers

Sulfide-based solid-state electrolytes (SSEs) are promising materials with superior Li-ion conductivity; however, their poor atmospheric stability limits commercial manufacturing at scale. Here, we investigate the impact of ultrathin metal oxide layers deposited via atomic layer deposition (ALD) on the stability of Li 6 PS 5 Cl (LPSCl). Al 2 O 3 layers grown directly on LPSCl particles significantly stabilize the surface chemistry and Li-ion transport properties relative to uncoated material upon exposure to both an ambient atmosphere (22% relative humidity, RH) and humidified O 2 (100% RH). Detailed investigations indicate that coatings impede the surface and bulk degradation kinetics of exposed materials, even for coatings as thin as ∼1 Å. Furthermore, this suggests that stabilization is due to more than just a physical barrier. Shifts in valence band edge positions of coated LPSCl indicate that ALD coatings alter the surface electronic structure and resulting oxidation tendency of underlying LPSCl, suggesting new avenues to improving the environmental stability of sulfide SSEs.

Atmospheric chemistry↗
DOE OSTI2025

CaloChallenge 2022: a community challenge for fast calorimeter simulation

Here, we present the results of the ‘Fast Calorimeter Simulation Challenge 2022’—the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of increasing dimensionality, ranging from a few hundred voxels to a few tens of thousand voxels. The 31 individual submissions span a wide range of current popular generative architectures, including variational autoencoders (VAEs), generative adversarial networks (GANs), normalizing flows, diffusion models, and models based on conditional flow matching. We compare all submissions in terms of quality of generated calorimeter showers, as well as shower generation time and model size. To assess the quality we use a broad range of different metrics including differences in one-dimensional histograms of observables, KPD/FPD scores, AUCs of binary classifiers, and the log-posterior of a multiclass classifier. The results of the CaloChallenge provide the most complete and comprehensive survey of cutting-edge approaches to calorimeter fast simulation to date. In addition, our work provides a uniquely detailed perspective on the important problem of how to evaluate generative models. As such, the results presented here should be applicable for other domains that use generative AI and require fast and faithful generation of samples in a large phase space.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Principal Landau determinants

We reformulate the Landau analysis of Feynman integrals with the aim of advancing the state of the art in modern particle-physics computations. We contribute new algorithms for computing Landau singularities, using tools from polyhedral geometry and symbolic/numerical elimination. Inspired by the work of Gelfand, Kapranov, and Zelevinsky (GKZ) on generalized Euler integrals, we define the principal Landau determinant of a Feynman diagram. We illustrate with a number of examples that this algebraic formalism allows to compute many components of the Landau singular locus. We adapt the GKZ framework by carefully specializing Euler integrals to Feynman integrals. For instance, ultraviolet and infrared singularities are detected as irreducible components of an incidence variety, which project dominantly to the kinematic space. We compute principal Landau determinants for the infinite families of one-loop and banana diagrams with different mass configurations, and for a range of cutting-edge Standard Model processes. Furthermore, our algorithms build on the Julia package this http URL and are implemented in the new open-source package this http URL available at this https URL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Finding a needle in a haystack: quantitative HERFD-XRF imaging and HERFD-XANES characterization of trace platinum in gold solidi from the Late Roman and Byzantine Empires

High-Energy Resolution Fluorescence Detection X-Ray Fluorescence (HERFD-XRF) imaging and HERFD X-ray Absorption Near Edge Structure (XANES) spectroscopy are used to quantify and characterize trace platinum (Pt) in gold solidi from the Late Roman and Byzantine Empires. Historically, the elemental analysis of coins has been pivotal in distinguishing authentic artifacts from forgeries, elucidating minting practices, and understanding economic shifts. Notably, a new gold source with high platinum content appeared in the fourth century CE, transforming the Roman economy. Traditional methods struggled to detect platinum due to the overwhelming gold matrix. Here, this study demonstrates the effectiveness of HERFD techniques in resolving this challenge. Three gold solidi, minted between 654 and 659 CE, were analyzed alongside reference gold materials with known Pt concentrations. The HERFD-XRF imaging revealed spatial distributions of platinum, highlighting non-uniformities within the coins. Additionally, HERFD-XANES spectroscopy identified the oxidation states and chemical speciation of platinum. Results demonstrate that platinum in the solidi primarily exists as metallic Pt, with some surface oxidation. The findings align with previous measurements but reveal higher Pt concentrations and significant inhomogeneities. This research confirms the reliability of HERFD methods for quantifying trace elements and provides new insights into the raw material sources and minting techniques of ancient gold coins. The non-destructive nature of this approach allows for extensive analyses, offering valuable data for historical, economic, and archaeological studies. This innovative application of HERFD-XRF imaging and XANES in cultural heritage research underscores the potential for detailed material characterization and conservation, enhancing our understanding of ancient economies and trade patterns.

Van Loon, Lisa L.↗
DOE OSTI2025

Encapsulation of Ba in InSb Framework Introduces Chirality in Clathrate-Like BaIn 4 Sb 4

The discovery of Zintl compounds remains a powerful strategy for identifying materials with tunable electronic and thermal transport properties. During a concerted search for new inorganic clathrates with In–Sb frameworks, we discovered BaIn 4 Sb 4 . The composition of this phase deviates from that expected for a type-I clathrate with tetrahedral coordination of all In and Sb atoms (Ba 8 In 31 Sb 15 ). Instead, in the chiral structure of BaIn 4 Sb 4 (space group P 3 1 21, No. 152), a part of the In atoms have a trigonal planar coordination of 1In + 2Sb, forming Sb 2 –In–In–Sb 2 nonplanar fragments isostructural to diborane(4) B 2 H 4 with D 2 d symmetry. Ba atoms are located inside 16-vertex In 8 Sb 8 polyhedra, which share vertices and edges to form a chiral framework around the 3 1 screw axes. The title compound is electron-balanced, [Ba 2+ ][In 2+ ] 2 [In 3+ ] 2 [Sb3–] 4 , which was confirmed by characterization of the charge and heat transport properties. BaIn 4 Sb 4 exhibits a low thermal conductivity and high Seebeck coefficient, suggesting its untapped potential for thermoelectric applications. Finally, density functional theory (DFT) calculations indicate that chemical doping may enhance carrier concentration and improve the originally low electrical conductivity, thus enhancing thermoelectric performance.

electrical properties↗
DOE OSTI2026

First field test of a novel optical gas analyser in the exhaust of Wendelstein 7-X

A novel optical gas analyser, designed for isotope-resolved exhaust composition measurement, was field-tested at Wendelstein 7-X (W7-X) to validate its laboratory-proven concept under operational fusion experiment conditions. The system, Optix, comprises a cold cathode remote plasma generator and a high-resolution Fabry–Perot spectrometer and was deployed in the exhaust line of W7-X during the OP2.3 campaign. The injection of 3 He and 4 He for minority ion-cyclotron heating provided a test case for helium isotope discrimination. Despite limitations due to background gas and low partial pressures of the target species, isotope-resolved spectral signatures were successfully observed, demonstrating the fundamental viability of the Optix approach. Additionally, the spectrometer was evaluated for plasma emission measurements from both core and edge sightlines. While helium line emission was detectable, interpretation was hindered by complex background signals, highlighting the benefits of controlled remote plasma generators for spectroscopy. This first deployment provides critical insight into pressure requirements, spectral resolution, and operational constraints, informing future applications of optical exhaust diagnostics in fusion devices.

magnetic confinement fusion↗
DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗
DOE OSTI2026

Machine learning at the Spallation Neutron Source accelerator and target

We describe the ongoing efforts to apply Machine Learning techniques to improve the performance of our accelerator and target. Specially, we are looking to minimize halo beam losses in the absence of a proper physics model, automatically detect and log anomalies in the target support systems such as cooling, and detect and prevent errant beam pulses in the linac. We also describe the infrastructure we use to acquire and stream data to the GPU cluster for training, our code development cycle, and edge computing for model inference. To minimize halo beam losses, we use a Reinforcement Learning technique tested on a virtual accelerator. The target anomaly detection is trained on archived data using incomplete physics models and is made part of the existing target reporting system. The errant beam prevention analyzes beam current and beam phase waveforms as well as accelerator configuration data to predict errant pulses. We also develop continual learning to adapt to changes in the accelerator.

Accelerator Physics↗
DOE OSTI2025

A constrained-transport embedded boundary method for compressible resistive magnetohydrodynamics

Motivated by the increased interest in pulsed-power magneto-inertial fusion devices in recent years, we present a method for implementing an arbitrarily shaped embedded boundary on a Cartesian mesh while solving the equations of compressible resistive magnetohydrodynamics. The method is built around a finite volume formulation of the equations in which a Riemann solver is used to compute fluxes on the faces between grid cells, and a face-centered constrained transport formulation of the induction equation. The small time step problem associated with the cut cells is avoided by always computing fluxes on the faces and edges of the Cartesian mesh. We extend the method to model a moving interface between two materials with different properties using a ghost-fluid approach, and show some preliminary results including shock-wave-driven and magnetically-driven dynamical compressions of magnetohydrostatic equilibria. In conclusion, we present a thorough verification of the method and show that it converges at second order in the absence of discontinuities, and at first order with a discontinuity in material properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Cobalt(II) Phthalocyanine Substituents Tune the Electrocatalytic CO 2 Conversion to Methanol

Cobalt phthalocyanine (Co(II)Pc) and its derivatives are promising molecular electrocatalysts for the electrochemical reduction of CO 2 to CO and methanol (CH 3 OH). Despite increasing interest, a detailed mechanistic understanding of how ligand substituents influence catalytic activity, selectivity, and efficiency remains limited. In this study, we employ density functional theory (DFT) to systematically investigate the influence of electron-donating groups (EDGs) and electron-withdrawing groups (EWGs) on the electronic structure and redox properties of the Co(II)Pc electrocatalyst, and to elucidate CO 2 RR mechanistic pathways. Our results reveal that EWGs cause a positive shift in the reduction potentials, favor CO 2 binding over protonation of the Co metal center and promote downstream methanol formation at mild potentials. EDGs show opposite trends including favorable protonation steps, promoting a negative shift in the reduction potential, and facilitating the hydrogen evolution reaction (HER), which competes with the desired CO 2 RR pathway. Notably, CO dissociation is thermodynamically and kinetically unfavorable across all systems, positioning the redox potential versus CO dissociation energy as a key factor for methanol selectivity. Furthermore, these insights provide a predictive framework for rational catalyst design and underscore the critical role of electronic tuning in advancing molecular electrocatalysts for sustainable CO 2 conversion.

Alcohols↗
DOE OSTI2024

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Particle control via cryopumping and its impact on the edge plasma profiles of Alcator C-Mod

At the high n e proposed for high-field fusion reactors, it is uncertain whether ionization, as opposed to plasma transport, will be most influential in determining n e at the pedestal and separatrix. A database of Alcator C-Mod discharges is analyzed to evaluate the impact of source modification via cryopumping. The database contains similarly-shaped H-modes at fixed I P = 0.8 MA and B t = 5.4 T, spanning a large range in P net and ionization. Measurements from an edge Thomson scattering system are combined with those from a midplane-viewing Ly α camera to evaluate changes to n e and T e in response to changes in ionization rates, S ion ∙ $n^{sep}_e$ and $T^{ped}_e$ are found to be most sensitive to changes to $S^{sep}_{ion}$, as opposed to $n^{ped}_e$ and $T^{sep}_e$. Dimensionless quantities, namely α MHD and v*, are found to regulate attainable pedestal values. Select discharges at different values of P net and in different pumping configurations are analyzed further using SOLPS-ITER. It is determined that changes to plasma transport coefficients are required to self-consistently model both plasma and neutral edge dynamics. Pumping is found to modify the poloidal distribution of atomic neutral density, n 0 , along the separatrix, increasing n 0 at the active X-point. Opaqueness to neutrals from high n e in the divertor is found to play a role in mediating neutral penetration lengths and hence, the poloidal distribution of neutrals along the separatrix. Pumped discharges thus require a larger particle diffusion coefficient than that inferred purely from 1D experimental profiles at the outer midplane.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Short-Term Inhibition and Long-Term Enhancement of Irreversible Trace Metal Binding to Goethite in Multi-Metal Systems

Iron (oxyhydr)oxide minerals are important sorbents of trace metals in aquatic environments. Adsorption–desorption hysteresis has been documented for trace metals after aging, suggesting that they become incorporated over time. We previously found that ion size controls the extent of irreversible metal binding of single metals to goethite. In this study, we evaluate how the presence of multiple metals influences irreversible binding. Mixed Ni–Zn and Ni–Cd solutions were aged with goethite at pH 7 for 2 days, 30 days, and 60 days, after which isotope exchange experiments were performed to assess the lability of the adsorbed metal pools. After 2 days of aging, Ni and Cd in mixed-metal systems were more labile than in single-metal systems, indicating that competitive adsorption may partially block irreversible binding on short time scales. After 60 days, all three metals had larger irreversibly bound fractions than in single-metal systems. X-ray absorption near-edge structure (XANES) spectroscopy indicates that irreversibly bound fractions correlate with incorporation into goethite. This study demonstrates that pools of coadsorbed metals are bioaccessible on a time scale of minutes. Cooperative effects promote the structural sequestration of even large trace metals, causing reactive transport models to likely overpredict metal mobility. Long-term metal entrapment processes hinder micronutrient availability, impact contaminant sequestration and critical mineral recovery, and yield complex pathways through which metal solubilization may be enhanced or hindered during redox cycling.

58 GEOSCIENCES↗