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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 415 records · Page 23

Distributions of Particles Accelerated by Strong Alfvénic Turbulence

This work presents a model for generating nonthermal power-law tails of particles’ energy probability density functions in turbulent collisionless plasmas, applicable to both nonrelativistic and relativistic scenarios. We propose that strong Alfvénic turbulence energizes plasma particles through curvature acceleration, particularly for particles with Larmor radii comparable to the scales of turbulence. When the energy density of the energized particles increases, the efficiency of the energy exchange process diminishes. As a result, the acceleration process saturates, leading to power-law distributions of particle momentum and energy. In the nonrelativistic case, the momentum probability density function scales as f(p)dp ∝ p −3 dp, while in the ultrarelativistic case, the energy probability density function scales as f(γ)dγ ∝ γ −3 dγ, where γ is the Lorentz factor. This model provides a unified framework for understanding particle acceleration in both energy regimes, complementing existing analytical approaches. The predicted scalings are consistent with available observations of energetic ion distributions in the heliosphere and with the findings from numerical simulations of ultrarelativistic particle acceleration in magnetically dominated plasma turbulence.

Alfven waves↗

Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-Driven Analysis of Multipactor Dynamics via Dynamic Mode Decomposition

Multipactor effect is a performance-limiting kinetic plasma effect that can occur in high-power microwave and radio frequency (RF) devices. Multipactor effect is of special concern in vacuum or near-vacuum conditions such as those in particle accelerators and spaceborne devices. In this work, we present a data-driven reduced-order model (ROM) based on dynamic mode decomposition (DMD) for modeling of multipactor effects. We study multipactor effects and the resulting nonlinear harmonic generation by processing high-fidelity data generated from electromagnetic particle-in-cell (EMPIC) simulations using the DMD algorithm. We also investigate time-delay embedding extensions of DMD with improved generalizability and accuracy for modeling the electron plasma current density behavior. Here, the results show that DMD provides valuable insights into multipactor phenomena by extracting relevant modal spatiotemporal patterns and frequencies. In addition, DMD offers the potential to time extrapolate EMPIC simulations at a minimal cost, thereby reducing overall simulation time.

43 PARTICLE ACCELERATORS↗

Corroborating VNA and thermal measurements of transmission loss on the DIII-D ECH waveguide system

Electron cyclotron heating (ECH) and current drive (ECCD) will play a large role in tokamak-based fusion reactors. At the DIII-D tokamak, 110 GHz microwaves injected into the plasma can provide core heating and current drive as well as impurity control, neoclassical tearing mode mitigation, and breakdown assistance. Understanding the physics of these processes relies on accurate estimates of injected ECH power. DIII-D’s ECH system consists of six MW-class Microwave Power Products (MPP) gyrotron microwave sources. Operating the gyrotrons far from the tokamak removes them from magnetic field interference, so 31.75 mm inner-diameter corrugated waveguides transmit the microwave power the 80 m from the gyrotrons to steerable launchers in the tokamak chamber. Estimates of injected power rely on knowing the generated power at the source and then subtracting transmission loss. Conventional transmission loss measurements based on calorimetric dummy loads are onerous and only possible during extended maintenance periods. This work examines two tools that provide more flexibility for the transmission loss measurements. Furthermore, a resistive temperature detector (RTD) array installed along a waveguide measures heat lost to the transmission line, and low power time domain reflectometry (TDR) measurements with a vector network analyzer (VNA) allows loss measurements without burdensome hardware modifications.

ECH↗

Advancements in the modification of TiFe alloys for enhanced hydrogen Storage: Strategies and future Directions

Hydrogen is considered a promising clean energy source, and a potential alternative to conventional fossil fuels. TiFe alloy has been particularly interesting due to its ability to reversibly absorb and desorb hydrogen at room temperature and low pressure. The initial hydrogen absorption stage of TiFe alloy requires activation under high-temperature and high-pressure conditions, which hinders its practical application. Here, this paper primarily examines the impact of elemental substitution methods on the hydrogen storage capabilities of TiFe alloys, with a particular emphasis on elucidating the mechanisms associated with various substituent elements. Commonly utilized elements, such as Mn, V, and Zr, significantly improve the activation performance of TiFe alloys. Additionally, the incorporation of elements such as Ni, Cr, Ce, and Y contributes to the modulation of phase composition, as well as the enhancement of activation and kinetic properties. However, there exists a notable deficiency in systematic investigations concerning alternative elements, coupled with a frequent oversight of the preparation process's influence on the hydrogen storage characteristics of these alloys. Consequently, the mechanisms by which different elements affect the hydrogen storage process in TiFe alloys remain inadequately understood among current research, thereby complicating the establishment of experiment-based design guidelines for TiFe alloys. Furthermore, the plasma treatment and high-entropy alloying present new approaches for optimizing the hydrogen storage properties of TiFe alloys. This paper aims to present novel research perspectives and insights to scholars in the field by introducing methods for the modification of TiFe alloys.

Hydrogen storage↗

Iodine Capture with Copper-Electroplated Nickel Foams

This work explores the use of Ni0 foam scaffolds for Cu0 coatings for use as sorbents for iodine. The Cu0 electroplating was performed from aqueous copper(II) sulfate (CuSO4) solutions under different conditions to achieve a range of Cu0-layer thicknesses (4.89 ± 1.05 μm–57.32 ± 3.95 μm) with 900 A·m–2 current densities and coating times of 15–180 min. The thickest coatings resulted in Cu0-plated Ni0 foams with >89 mass % Cu0 in the final product. Iodine capture experiments showed very high Cu0 utilizations of 91.9–97.3 mass % at iodine loadings of 839–1774 mg·g–1 through the formation of CuI (marshite; space group F-43m). No evidence was found of iodine reactions taking place with the Ni0 scaffold, so it remained in iodine-loaded Cu-electroplated Ni foams as structural support to provide mechanical rigidity to the foams during the iodine loading process. Hot pressing of these materials can be used to create a CuI/Ni ceramic-metal composite waste form for disposal as demonstrated with spark plasma sintering.

Riley, Brian [Pacific Northwest National Laborator↗

Particle Beam Acceleration Using 3 Petawatt Laser Pulses

The Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) is presently operational at the Gerard Mourou Center for Ultrafast Optical Science (CUOS) at the University of Michigan. ZEUS is a significant upgrade of the previous high power laser systems at CUOS and consists of two beamlines thatoperate in perfect synchronization. The 500 TW beamline became operational in 2023, 2 PW operation started in 2025 and full 3 PW power levels will be available in 2026. It is presently the highest power laser system in the US. In this grant the high field science group at CUOS has leveraged this unique high power laser facility to investigate laser wake field acceleration (LWFA) in ultra-high power laser plasma interactions and have shown how this can scale for future electron–positron colliders at high energy. The dual beam experimental configuration enables flexibility for many frontier experiments in laser-driven acceleration research, in particular, enabling extended channelling/acceleration experiments, positron generation/acceleration experiments and proof-of-principle transverse pumping “dephasingless” electron acceleration experiment and theory. LWFA may be able to miniaturize particle accelerators for high energy physics and also enable new sources of ultrafast, extreme brightness and precise x-rays for a wide variety of applications. In laser wake field acceleration, an electron bunch “surfs” on the electron plasma wave (the “wake field”) generated by the ponderomotive force of an intense laser. The plasma wave has a strong longitudinal electric field that stays in phase with the relativistic driver. A relativistic charged particle may, therefore, remain in phase with the accelerating field over long distances and gain ultra-relativistic energies. The accelerating electric field strength that the plasma wave can support can be many orders of magnitude higher than that of conventional accelerators, which makes laser wakefield acceleration an exciting prospect as an advanced accelerator concept. In this research project we have investigated the scaling of this mechanism to laser powers of 2 PW and have measured the x-ray emission and radio frequency emission resulting from the acceleration process. We have also performed theoretical investigation of mechanisms to scale laser driven accelerators to much higher energy using dephasingless acceleration processes.

43 PARTICLE ACCELERATORS↗

The 140 GHz notch filter development for millimeter-wave diagnostics protection on the stellarator Wendelstein 7-X

The notch filter plays a crucial role as a protective component in microwave diagnostics, primarily by addressing issues related to catastrophic interference. Designed for millimeter-wave diagnostics on the stellarator Wendelstein 7-X (W7-X), a WR-6 waveguide-based notch filter has been successfully developed to effectively isolate leakage from auxiliary heating gyrotrons operating at 140 GHz. The filter incorporates cylindrical cavities resonating at 140 GHz for the TE11p mode, with coupling structures that are designed and optimized for high-efficiency coupling. This configuration simplifies fabrication, thereby ensuring high-yield production. Experimental fabrication and in-house characterization confirm the notch filter's exceptional performance, with over 60 dB rejection in the vicinity of 140 GHz and low insertion loss (< 2 dB) above and below the notch frequency across a broad frequency bandwidth (121–138 GHz, 142–163 GHz). Furthermore, the utilization of this high-frequency structure fabrication technology can be applied to millimeter-wave diagnostics on other machines. In addition to the design elements of the notch filter, this paper also provides a detailed discussion of the fabrication process and methodology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗

Characterization of Caenorhabditis elegans sphingomyelin synthases through heterologous expression

Sphingomyelin (SM) is a major component of mammalian cell membranes and particularly abundant in the myelin sheath that surrounds nerve fibers. Its production is catalyzed by SM synthases SMS1 and SMS2, which interconvert phosphatidylcholine and ceramide to diacylglycerol and SM in the Golgi and at the plasma membrane, respectively. As the lipids participating in this reaction fulfill both structural and signaling functions, SMS enzymes have considerable potential to influence diverse important cellular processes. The nematode Caenorhabditis elegans is an attractive model for studying both animal development and human disease. The organism contains five SMS homologues but none of these have been characterized in any detail. Here, we carried out the first systematic analysis of SMS family members in C. elegans . Using heterologous expression systems, genetic ablation, metabolic labeling and lipidome analyses, we show that C. elegans harbors at least three distinct SM synthases and one ceramide phosphoethanolamine (CPE) synthase. Moreover, C. elegans SMS family members have partially overlapping but also unique sub-cellular distributions and together occupy all principal compartments of the secretory pathway. Our findings shed light on crucial aspects of sphingolipid metabolism in a valuable animal model and opens avenues for exploring the role of SM and its metabolic intermediates in organismal development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy dependence of polarized 𝛾⁢𝛾 → 𝑒 + ⁢ 𝑒− in peripheral Au+Au collisions at $\sqrt{s_{NN}}$ = 54.4 and 200 GeV with the STAR experiment at RHIC

We report the differential yields at mid-rapidity of the Breit-Wheeler process (𝛾⁢𝛾 → 𝑒 + ⁢𝑒 − ) in peripheral Au+Aucollisions at $\sqrt{s_{NN}}$ = 54.4 and 200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC), as a function of energy $\sqrt{s_{NN}}$, 𝑒 + ⁢𝑒 − transverse momentum 𝑝 T , 𝑝$^{2}_{T}$, invariant mass 𝑀 𝑒⁢𝑒 , and azimuthal angle. In the invariant mass range of 0.4 < 𝑀 𝑒⁢𝑒 < 2.6GeV/𝑐 2 at low transverse momentum (𝑝 T < 0.15GeV/𝑐), the yields increase while the pair √⟨𝑝$^{2}_{T}$⟩ decreases with increasing $\sqrt{s_{NN}}$, a feature that is correctly predicted by the QED calculation. Here, the energy dependencies of the measured quantities are sensitive to the nuclear form factor, infrared divergence and photon polarization. The data are compiled and used to extract the charge radius of the Au nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Temporal Properties of Compressible Magnetohydrodynamic Turbulence

Describing the temporal properties of compressible magnetohydrodynamic (MHD) turbulence is a fundamental problem that has important implications for particle acceleration and transport in astrophysical plasmas. Here, by carefully analyzing the spatial and temporal properties of compressible MHD turbulence, we derive a new spectral power density function that is supported by simulations. This new function reveals that the low-frequency fluctuations are dominated by modes with small parallel wavenumbers with respect to the mean background magnetic field. Furthermore, for fluctuations with dynamically significant parallel wavenumbers, broadening around their eigenfrequencies is described by this function, which is in close agreement with simulations. We use this formalism to present the scaling properties of individual MHD modes. Such broadening is a direct consequence of nonlinear processes and is different for the three fundamental MHD modes. Our results provide a new window to investigate the temporal properties of turbulence and will enable further studies on the interaction between compressible MHD turbulence and energetic plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗

Using convolutional neural networks to detect edge localized modes in DIII-D from Doppler backscattering measurements

In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs, and by extension, how to detect and mitigate them, is an important challenge. In this paper, we focus on two diagnostic methods—deuterium-alpha (D α ) spectroscopy and Doppler backscattering (DBS). The former detects ELMs by measuring Balmer alpha emission, while the latter uses microwave radiation to probe the plasma. DBS has the advantages of having a higher temporal resolution and robustness to damage. These advantages of DBS diagnostic may be beneficial for future operational tokamaks, and thus, data processing techniques for DBS should be developed in preparation. In sight of this, we explore the training of neural networks to detect ELMs from DBS data, using D α data as the ground truth. With shots found in the DIII-D database, the model is trained to classify each time step based on the occurrence of an ELM event. The results are promising. When tested on shots similar to those used for training, the model is capable of consistently achieving a high f1-score of 0.93. Furthermore, this score is a performance metric for imbalanced datasets that ranges between 0 and 1. We evaluate the performance of our neural network on a variety of ELMs in different high confinement regimes (grassy ELM, RMP mitigated, and wide-pedestal), finding broad applicability. Beyond ELMs, our work demonstrates the wider feasibility of applying neural networks to data from DBS diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Durability of Highly Active PGM Catalyst MEA Tested Via Nitrogen and Air AST Cycling Under HDV Condition

PEMFCs are widely considered as the most promising power sources, particularly for heavy-duty vehicles (HDVs). Unfortunately, the degradation of MEAs under HDV condition remains insufficiently studied. In this work, we systematically investigated two MEAs with catalysts of Pt nanoparticles (NPs) supported over high surface area carbon black. These MEAs were tested for durability under HDV condition in nitrogen using a DOE AST protocol for 180,000 cycles, which is equivalent to 30,000 hours or 1 million miles of operation. The commercial Catalyst MEA also underwent 6,000 AST cycles in air under M2FCT condition. We comprehensively investigated the degradation of catalysts. Our results indicate that both MEAs undergo continuous performance degradation in H 2 /air and H 2 /O 2 during the AST cycling in nitrogen, where analysis employing scanning transmission electron microscopy (STEM) and inductively coupled plasma mass spectrometry (ICP-MS) reveal significant degradation behavior for Pt catalysts. The MEA exhibits more significant degradation, especially within mass transfer region, during the AST process in air. In conclusion, this study describes the long-term degradation behavior and mechanism with AST cycling in nitrogen or air governing highly efficient and durable PGM-catalyst MEA design under HDV conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diagnostics of Magnetohydrodynamic Modes in the Interstellar Medium through Synchrotron Polarization Statistics

One of the biggest challenges in understanding magnetohydrodynamic (MHD) turbulence is identifying the plasma mode components from observational data. Previous studies on synchrotron polarization from the interstellar medium (ISM) suggest that the dominant MHD modes can be identified via statistics of Stokes parameters, which would be crucial for studying various ISM processes such as the scattering and acceleration of cosmic rays, star formation, and dynamo. In this paper, we present a numerical study of the synchrotron polarization analysis (SPA) method through systematic investigation of the statistical properties of the Stokes parameters. We derive the theoretical basis for our method from the fundamental statistics of MHD turbulence, recognizing that the projection of the MHD modes allows us to identify the modes dominating the energy fraction from synchrotron observations. Based on the discovery, we revise the SPA method using synthetic synchrotron polarization observations obtained from 3D ideal MHD simulations with a wide range of plasma parameters and driving mechanisms, and present a modified recipe for mode identification. We propose a classification criterion based on a new SPA+ fitting procedure, which allows us to distinguish between Alfvén mode and compressible/slow mode dominated turbulence. We further propose a new method to identify fast modes by analyzing the asymmetry of the SPA+ signature and establish a new asymmetry parameter to detect the presence of fast mode turbulence. Additionally, we confirm through numerical tests that the identification of the compressible and fast modes is not affected by Faraday rotation in both the emitting plasma and the foreground.

97 MATHEMATICS AND COMPUTING↗

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗

Micropinch formation dynamics in X pinches

High temporal resolution x-ray streak camera studies of micropinch formation in Cu hybrid x pinches reveal key plasma conditions. Analysis of Ne-like Cu lines indicate an average electron temperature of about 200 eV and 4.5×10 28 m -3 electron density. Here, the spectra suggest that the electron temperature jumps to about 1 keV, inferred from the continuum and the postcontinuum line emission that includes Li-like Cu lines. There is no sign of a rapid temperature change or a substantial surge in radiation emission during the 200 ps precontinuum x-ray burst, suggesting that the radiative collapse process does not play a major role in micropinch formation. Two-dimensional extended Magnetohydrodynamic (MHD) simulations, coupled to a collisional-radiative spectral analysis code, suggest the significance of the rapid radial implosion of high-temperature, low-density plasma, the axial outflow, and the dynamic plasma pressure in micropinch formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗