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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Plasma instabilities dominate radioactive transients magnetic fields: the self-confinement of leptons in Type Ia and core-collapse supernovae, and kilonovae

The light curves of radioactive transients, such as supernovae and kilonovae, are powered by the decay of radioisotopes, which release high-energy leptons through $\beta ^+$ and $\beta ^-$ decays. These leptons deposit energy into the expanding ejecta. As the ejecta density decreases during expansion, the plasma becomes collisionless, with particle motion governed by electromagnetic forces. In such environments, strong or turbulent magnetic fields are thought to confine particles, though the origin of these fields and the confinement mechanism have remained unclear. Using fully kinetic particle-in-cell (PIC) simulations, we demonstrate that plasma instabilities can naturally confine high-energy leptons. These leptons generate magnetic fields through plasma streaming instabilities, even in the absence of pre-existing fields. The self-generated magnetic fields slow lepton diffusion, enabling confinement, and transferring energy to thermal electrons and ions. Our results naturally explain the positron trapping inferred from late-time observations of thermonuclear and core-collapse supernovae. Furthermore, they suggest potential implications for electron dynamics in the ejecta of kilonovae. We also estimate synchrotron radio luminosities from positrons for Type Ia supernovae and find that such emission could only be detectable with next-generation radio observatories from a Galactic or local-group supernova in an environment without any circumstellar material.

instabilities↗
DOE OSTI2025

Biermann-Battery-Driven Magnetized Collisionless Shock Precursors in Laser-Produced Plasmas

This Letter reports the first complete observation of magnetized collisionless shock precursors formed through the compression of Biermann-battery magnetic fields in laser produced plasmas. At OMEGA, lasers produce a supersonic CH plasma flow which is magnetized with Biermann-battery magnetic fields. The plasma flow collides with an unmagnetized hydrogen gas jet plasma to create a magnetized shock precursor. The situation where the flowing plasma carries the magnetic field is similar to the Venusian bow shock. Imaging 2⁢𝜔 Thomson scattering confirms that the interaction is collisionless and shows density and temperature jumps. Proton radiographs have regions of strong deflections and FLASH magnetohydrodynamic (MHD) simulations show the presence of Biermann fields in the Thomson scattering region. Electrons are accelerated to energies of up to 100 keV in a power-law spectrum. Here, OSIRIS particle-in-cell (PIC) simulations, initialized with measured parameters, show the formation of a magnetized shock precursor and corroborate the experimental observables.

High-energy-density plasmas↗
DOE OSTI2026

Expansion-Driven Self-Magnetization of High-Energy-Density Plasmas

Understanding plasma self-magnetization is one of the fundamental challenges in both laboratory and astrophysical plasmas. Self-magnetization can modify plasma transport properties, altering the dynamical evolution of plasmas. Multiple high-energy-density (HED) experiments have observed the formation of ion-scale magnetic filaments of megagauss strength, though their origin remains debated. Here, in this study, we conduct 2D collisional particle-in-cell (PIC) simulations with a laser ray-tracing module for a fully self-consistent simulation of the plasma ablation, expansion, and magnetization. The simulations use a planar geometry, effectively suppressing the Biermann magnetic fields, to focus on anisotropy-driven instabilities. The laser intensity is varied between 10 13 and 10 14 W/cm 2 , which is relevant to HED and inertial fusion experiments where collisions must be considered. We find that, above a critical intensity, the plasma rapidly self-magnetizes via an expansion-driven Weibel process, producing a plasma beta of 100 (𝛽 = 8⁢𝜋⁢𝑘 𝐵 ⁢𝑛 𝑒 ⁢𝑇 𝑒 /𝐵 2 ) and Hall parameter 𝜔 ce ⁢𝜏 𝑒 >1 within the first few hundred picoseconds. The magnetic field is sufficiently strong to modify plasma heat transport, and simulations with an artificially suppressed magnetic field show noticeably different temperature profiles.

Lezhnin, K. V. [Princeton Plasma Physics Laborator↗
DOE OSTI2025

Particle-in-cell simulations of burning inertial confinement fusion capsule implosions

Anomalies observed in the neutron spectral shift of high-yield shots at the National Ignition Facility (NIF) suggest the presence of suprathermal ions [E. P. Hartouni et al., Nat. Phys. 19, 72 (2023)], implying that kinetic effects play a significant role in burning inertial confinement fusion (ICF) plasmas. Furthermore, recent measurements of reaction-in-flight (RIF) neutrons offer a direct probe of the stopping power in the burning fuel region of high-energy alpha particles and up-scattered fuel ions. We have developed the particle-in-cell code PICNIC, an exactly energy-conserving particle-in-cell Monte-Carlo collision (PIC-MCC) code to simulate the burn stage in ICF. We present results from 1D spherical simulations of NIF shot N210808, which was the first to exceed the Lawson criterion for laser fusion. We find that the suprathermal ions generated by large-angle Rutherford and nuclear elastic scattering (NES) with fusion alphas produce an alpha knock-on neutron (AKN) signal consistent with the extent and relative yield of the AKN spectrum identified in ignition experiments at the NIF. Furthermore, we also find that the inclusion of large-angle scattering physics does not explain the anomalously large spectral shift observed in the experiment.

High-energy-density plasmas↗
DOE OSTI2024

Theoretical Assessment of the Transition Between Electron Emission Mechanisms for Nonplanar Diodes

Theoretically and computationally describing the operation of nanodiodes requires characterizing the transitions between multiple electron emission mechanisms for nanodiodes with complicated geometries. This motivates our development of techniques to determine when simplified theories for individual mechanisms suffice compared to more complete, but more computationally expensive, models. Leveraging recent theories that define a canonical gap distance to translate planar theory to nonplanar diodes, we derive the conditions for the transitions among thermal emission, field emission, and space-charge-limited current density (SCLCD) in vacuum and with collisions for non-Cartesian coordinate systems, including spherical, cylindrical, and prolate spheroidal coordinate systems. Particle-in-cell (PIC) simulations of the current density as a function of applied voltage for a tip-to-plate geometry in vacuum agreed qualitatively with the asymptotes for thermal emission at low voltage and SCLCD at higher voltage using the canonical gap distance. As a result, this demonstrates the utility of this approach for guiding system design and suggests future extensions to save simulation time for more realistic geometries that are more computationally expensive.

Conformal mapping↗
DOE OSTI2026

HELIX

HELIX — Hybrid Envelope-multiparticle LInac eXplorer: TraceWin-compatible linac simulation with 3-D PIC space charge, matching, a PyQt6 workbench, and a voice-driven AI copilot. Built at Fermilab for PIP-II.

Pathak, Abhishek [Fermi National Accelerator Labor↗
DOE OSTI2024

Using a particle-in-cell model for accelerator control room applications

Many accelerator control rooms rely on envelope models to simulate beam dynamics because they are fast and accurate at tracking the beam core. Particle-in-Cell (PIC) models, however, can track particles inside and outside the core and, with the improvements of computers, are now fast enough to be used in control rooms. The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is currently developing a tool to use a Particle-in-Cell model for control room applications. This report covers the progress so far and the future goals of using PyORBIT, a Particle-in-Cell simulation model, in the SNS control room.

Cathey, Brandon↗
DOE OSTI2024

Final Report for Center for Tokamak Transient Simulations at USU

Providing plasma fluid codes like NIMROD with continuum drift kinetic (CDK) physics that is quantitatively valid and computationally feasible throughout the spatial domain is difficult. Work at Utah State University (USU), in collaboration with the Center for Tokamak Transient Simulations (CTTS), focused on applying CDK closures in disruption-related calculations. Three examples where kinetic physics is paramount are (1) the electron stress tensor closure in Ohms law for accurately describing neoclassical tearing mode (NTM) evolution, (2) runaway electron (RE) density (nRE) and current (jRE) moments in NIMROD’s extended MHD model for self-consistent evolution of RE populations during disruptions and, (3) energetic ion effects on a myriad of MHD instabilities. While NTM simulations and continuum and PIC approaches to energetic ions in NIMROD have been a major goals of USU’s closure work for several years, the development of self-consistent CDK RE capability in NIMROD was started and extended considerably during the CTTS effort. Some goals of CDK RE in NIMROD are to explore the effects of the 2D relativistic phase space in 4D simulations and compare with NIMROD’s fluid RE model. Four publications and two PhD theses came out of the USU CTTS effort.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MFiX Development Updates

This presentation discusses recent developments of the Multiphase Flow with Interphase eXchanges (MFiX) software. A brief review of all modeling approaches along with their cost versus accuracy is provided to guide users when selecting a model for a given application. The main new features of the past five official releases of MFiX are described. Improvement in chemistry management allow for easier simulation setup, and faster simulation speed. Progress in the implementation of a thin-wall boundary condition is presented. The major new model development over the past year is the release of the Glued Sphere Particle model (GSP), where component spheres are combined together to represent non-spherical particles. The integration of Machine Learning (ML) workflow in the CFD process is discussed with two applications: a surrogate model for stiff chemistry and the development of a PIC stress model using ML.

Dietiker, Jeff↗
DOE OSTI2025

New model for the ion collection by cylindrical probes over a wide range of collisionality

Langmuir probes remain one of the most important diagnostic tools for plasma processing applications. Modern probe analysis usually relies on the electron current part of the Langmuir probe characteristic using the Druyvesteyn method. However, for electronegative plasmas or for discharges containing dust the analysis of the ion current attracted by the probe can be desirable to determine the ion density. But, even at low pressures of a few Pa, the ion current is affected by collisions due to the large cross section for charge exchange. Available theories for collisional or collision-enhanced ion currents onto probes are complex and not well validated. Thus, in this contribution, we compare available collisional probe theories for the ion current to results of particle-in-cell (PIC) simulations. To this end, the probe surrounded by a semi-infinite plasma is simulated using a modified version of the open-source code EDIPIC. A dataset of currents for different neutral gas pressures is obtained and compared to the different theories from the literature. Based on these results, we propose a simpler and more intuitive model for the ion current collected by the probe, based on the model of Gatti and Kortshagen (Phys. Rev. E 78, 046402, 2008), developed for the charging of dust particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A kinetic study of fusion burn waves in compressed deuterium–tritium and proton–boron plasmas

We present particle-in-cell simulations with Monte Carlo collisions of fusion burn waves in compressed deuterium–tritium and proton–boron plasmas. We study the energy balance in the one-dimensional expansion of a hot-spot by simulating Coulomb collisions, fusion reactions, and bremsstrahlung emission with a Monte Carlo model and inverse bremsstrahlung absorption using a new PIC model. This allows us to self-consistently capture the alpha particle heating and radiative losses in the expanding hot-spot and surrounding cold fuel. After verifying our model in a code-to-code comparison with both kinetic and fluid codes for the case of a deuterium–tritium hot-spot, we simulate the expansion of a proton–boron hot-spot initialized at 200 keV and 1,000 g/cm 3 . Our model predicts that energy radiated by the hot-spot is recaptured by the surrounding high-density opaque fuel reducing the expansion work done by the propagating burn wave. As a result, we find the net fusion energy produced over the course of $20$~ps is twice the initial hot-spot energy independent of whether radiation physics is included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Planar Collisionless Shock Simulations with the Semi-implicit Particle-in-cell Model FLEKS

This study investigates the applicability of the semi-implicit particle-in-cell code FLexible Exascale Kinetic Simulator (FLEKS) to heliospheric shock simulations. We examine one- and two-dimensional local planar shock simulations, initialized using MHD states with upstream conditions representative of plasmas in the hypersonic, β ∼ 1 regime, for both quasi-perpendicular and quasi-parallel configurations. The refined algorithm in FLEKS proves robust, enabling accurate shock simulations with a grid resolution on the order of the electron inertial length d e . Our simulations successfully capture key shock features, including shock structures (foot, ramp, overshoot, and undershoot), upstream and downstream waves (fast magnetosonic, whistler, Alfvén ion-cyclotron, and mirror modes), and non-Maxwellian particle distributions. Crucially, we find that at least two spatial dimensions are critical for accurately reproducing downstream-wave physics in quasi-perpendicular shocks and capturing the complex dynamics of quasi-parallel shocks, including surface rippling, shocklets, short, large-amplitude magnetic structures, magnetic reconnection, and jets. Furthermore, our parameter studies demonstrate the impact of mass ratio and grid resolution on shock physics. This work provides valuable guidance for selecting appropriate physical and numerical parameters for shock simulations using a semi-implicit PIC method, paving the way for incorporating kinetic shock processes into large-scale collisionless plasma simulations with the MHD-AEPIC model.

plasma astrophysics↗
DOE OSTI2025

On operation and control of CW magnetrons for superconducting accelerators

CW magnetrons, developed for industrial RF heaters, were suggested to feed RF cavities of superconducting accelerators due to higher efficiency and lower cost of RF power than provide traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF auto generators with a huge regenerative gain. This causes regenerative instability with a notable noise when a magnetron operates as an auto generator i.e., with the anode voltage above the threshold of self-excitation. Traditionally, an injection locking by a small signal is used for phase stabilization of magnetrons. In this case CW magnetrons with the injection-locked (coherent) oscillations generate a notable level of noise. This may preclude use of CW magnetrons in this mode in the Superconducting RF (SRF) accelerators. This paper reviews PIC modeling and previously obtained experimental results for the operation and control of CW magnetrons, which led to the development of techniques most suitable for various SRF accelerators using forced RF oscillation of magnetrons, when the magnetron is launched by an injected forcing signal, and regenerative noise is suppressed.

Kazakevich, G. [MUONS Inc., Batavia] (ORCID:000000↗
DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗