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DOE OSTI2025

Preface to the Proceedings of the 25th Topical Conference on High-Temperature Plasma Diagnostics

The 25th Topical Conference on High-Temperature Plasma Diagnostics (HTPD 2024) was held in Asheville, NC, USA, at the Renaissance Asheville Downtown Hotel from 21 to 25 April 2024. This biennial conference brings together scientists and engineers from a variety of fields, including magnetic confinement fusion, inertial confinement fusion, space plasmas, astrophysics, and industrial applications, to discuss mutual problems in the development of instrumentation and experimental techniques for the characterization of high-temperature plasmas. As the 25th meeting, HTPD 2024 represents ∼50 years of ongoing international collaboration on these topics.

Biewer, Theodore [ORNL] (ORCID:0000000174563509)↗

DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

A future of inertial confinement fusion without laser-plasma instabilities

From the beginning of inertial confinement fusion (ICF) research, laser-plasma instabilities excited by narrowband lasers have limited the hydrodynamic design space of all laser-based approaches to inertial fusion energy (IFE). With advances in broadband laser technologies, the next generation of ICF drivers will likely have large bandwidth that is engineered to mitigate laser-plasma instabilities, thereby expanding the hydrodynamic design space to include both robust high yields (>200−MJ) with large-energy laser systems (>4 MJ) and high gains (>10) with moderate-energy laser facilities (<2 MJ). State-of-the-art simulations indicate that laser bandwidths of a few percent are required to mitigate instabilities for IFE-relevant conditions. To test these models and demonstrate that high-bandwidth lasers mitigate laser-plasma instabilities, the Fourth-generation Laser for Ultrabroadband eXperiments will be used with the OMEGA Laser System. The goal is to provide the community with the confidence to invest in a multiple-beam high-bandwidth laser facility that will demonstrate the necessary ablation pressures for robust direct-drive ignition without detrimental levels of hot electrons that degrade the implosion performance. It is important to recognize that the highest performing ICF implosions will likely never be completely LPI free because of the significant advantages to maximizing the laser intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Impact of mid- Z gas fill on dynamics and performance of shock-driven implosions at the OMEGA laser

Shock-driven implosions with 100% deuterium (D 2 ) gas fill compared to implosions with 50:50 nitrogen-deuterium (N 2 ⁢D 2 ) gas fill have been performed at the OMEGA laser facility to test the impact of the added mid-Ζ fill gas on implosion performance. Ion temperature (Τ ion ) as inferred from the width of measured DD-neutron spectra is seen to be 34%±6% higher for the N 2⁢ D 2 implosions than for the D 2 -only case, while the DD-neutron yield from the D 2 -only implosion is 7.2±0.5 times higher than from the N 2⁢ D 2 gas fill. The T ion enhancement for N 2 ⁢D 2 is observed in spite of the higher Z, which might be expected to lead to higher radiative loss, and higher shock strength for the D 2 -only versus N 2 ⁢D 2 implosions due to lower mass, and is understood in terms of increased shock heating of N compared to D, heat transfer from N to D prior to burn, and limited amount of ion-electron-equilibration-mediated additional radiative loss due to the added higher-Z material. Further, this picture is supported by interspecies equilibration timescales for these implosions, constrained by experimental observables. The one-dimensional (1D) kinetic Vlasov-Fokker-Planck code ifp and the radiation hydrodynamic simulation codes hyades (1D) and xrage [1D, two-dimensional (2D)] are brought to bear to understand the observed yield ratio. Comparing measurements and simulations, the yield loss in the N 2 ⁢D 2 implosions relative to the pure D 2 -fill implosion is determined to result from the reduced amount of D 2 in the fill (fourfold effect on yield) combined with a lower fraction of the D 2 fuel being hot enough to burn in the N 2 ⁢D 2 case. The experimental yield and T ion ratio observations are relatively well matched by the kinetic simulations, which suggest interspecies diffusion is responsible for the lower fraction of hot D 2 in the N 2 ⁢D 2 relative to the D 2 -only case. The simulated absolute yields are higher than measured; a comparison of 1D versus 2D XRAGE simulations suggest that this can be explained by dimensional effects. The hydrodynamic simulations suggest that radiative losses primarily impact the implosion edges, with ion-electron equilibration times being too long in the implosion cores. The observations of increased T ion and limited additional yield loss (on top of the fourfold expected from the difference in D content) for the N 2 ⁢D 2 versus D 2 -only fill suggest it is feasible to develop the platform for studying CNO-cycle-relevant nuclear reactions in a plasma environment.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Measurement of Energy Reduction of Inertial Alfvén Waves Propagating through Parallel Gradients in the Alfvén Speed

We have studied the propagation of inertial Alfvén waves through parallel gradients in the Alfvén speed using the Large Plasma Device at the University of California, Los Angeles. The reflection and transmission of Alfvén waves through inhomogeneities in the background plasma are important for understanding wave propagation, turbulence, and heating in space, laboratory, and astrophysical plasmas. Here we present inertial Alfvén waves under conditions relevant to solar flares and the solar corona. We find that the transmission of the inertial Alfvén waves is reduced as the sharpness of the gradient is increased. Any reflected waves were below the detection limit of our experiment, and reflection cannot account for all of the energy not transmitted through the gradient. Our findings indicate that, for both kinetic and inertial Alfvén waves, the controlling parameter for the transmission of the waves through an Alfvén speed gradient is the ratio of the Alfvén wavelength along the gradient divided by the scale length of the gradient. Furthermore, our results suggest that an as-yet-unidentified damping process occurs in the gradient.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Amplification of turbulence through multiple planar shocks

We study the amplification of isotropic, incompressible turbulence through multiple planar, collisional shocks, using analytical linear theory. There are two limiting cases we explore. The first assumes shocks occur rapidly in time such that the turbulence does not evolve between shocks. Whereas the second case allows enough time for turbulence to isotropize between each shock. For the latter case, through a quasi-equation-of-state, we show that the weak multishock limit is agnostic to the distinction between thermal and vortical turbulent pressures, like an isotropic volumetric compression. When turbulence does not return to isotropy between shocks, the generated anisotropy—itself a function of shock strength—can feedback on amplification by further shocks, altering choices for maximal or minimal amplification. In addition for this case, we find that amplification is sensitive to the shock ordering. As a result, we map how choices of shock strength can impact these amplification differences due to ordering, finding, for example, shock pairs which lead to identical mean postshock fields (density, temperature, pressure) but maximally distinct turbulent amplification.

Astrophysical fluid dynamics↗

DOE OSTI2025

Automated and highly parallelized Bayesian optimization scheme for direct drive fusion experiments on OMEGA

Finding the optimal implosion design on existing experimental facilities for inertial confinement fusion requires an exhaustive search of the vast design parameter space. This is infeasible both with experiments and with simulations. Consequently, a large fraction of the experimentally realizable design space remains unexplored, and new design schemes are challenging to optimize in a reasonable time frame. On the OMEGA laser facility, predictive machine learning models have been developed to accurately forecast the result of an experiment using only inexpensive simulations and the large dataset of prior experimental data. However, the full design space remains vast enough to be unassailable with simple optimization techniques. Here we develop an automated and optimally parallel Bayesian optimization algorithm that can entirely optimize the target and pulse shape of a direct-drive ICF implosion under a given design paradigm. We use this algorithm to find a markedly improved design for the performance implosions on OMEGA that is predicted to hydroequivalently scale to ignition at 2.15 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Addressing key physics problems in high-energy-density plasmas with a novel kinetic simulation capability

Many important physical processes in inertial confinement fusion (ICF) and dense Z-pinch (DZP) experiments require a kinetic (velocity-space-dependent) description. Conventional particle-in-cell (PIC) methods are poorly suited for high-energy-density (HED) plasmas, due to restrictive time-step constraints and the inability to conserve energy. In a previous LDRD (21-FS-048), we demonstrated that a fully implicit PIC formulation overcomes these limitations: it conserves energy even when coupled with Coulomb collision models and can be solved efficiently with large grid cells and large time steps. Thus, it is feasible to use this method to study kinetic effects in ICF and DZP plasmas on hydro-like time and spatial scales. In this follow-on LDRD, we advanced this methodology into a high-fidelity tool for production-scale simulations and used it to answer key questions relevant to ICF and DZP experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Feynman diagrams for matter wave interferometry

We introduce a new theoretical framework based on Feynman diagrams to compute phase shifts in matter wave interferometry. The method allows for analytic computation of higher order quantum corrections, beyond the traditional semi-classical approximation. These additional terms depend on the finite size of the initial matter wavefunction and/or have higher order dependence on ℏ. We apply the method to compute the response of matter wave interferometers to power law potentials and potentials with an arbitrary spatial dependence. The analytic expressions are validated by comparing to numerical simulations, and estimates are provided for the scale of the quantum corrections to the phase shift response to the gravitational field of the earth, anharmonic trapping potentials, and gravitational fields from local proof masses. We also find that for certain experimentally feasible parameters, these corrections are large enough to be measured and could lead to systematic errors if they are not mitigated. We find that to first order in a spatially dependent potential, quantum corrections vanish when the initial matter wavepacket has spherical symmetry and the potential satisfies Laplace's equation. We anticipate these quantum corrections will be especially important for trapped matter wave interferometers and for free-space matter wave interferometers in the presence of proof masses. These interferometers are becoming increasingly sensitive tools for mobile inertial sensing, gravity surveying, tests of gravity and its interplay with quantum mechanics, and searches for dark energy.

Glick, Jonah [Northwestern U.; Fermilab] (ORCID:00↗

DOE OSTI2024

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Experiments and Simulations of the Dusty Properties of Hypervelocity Impact Plasmas

Hypervelocity impacts, referring to impacts occurring at several times the speed of sound in the target, result in inertial stresses greatly exceeding the material strength and produce behavior that is not fully understood. These impact phenomena are seen in space through impacts of orbital debris and meteoroids on spacecraft and airless natural bodies but can also be produced in laboratory environments using light-gas guns and electrostatic dust accelerators. When a hypervelocity impact occurs, plasma is generated both from thermal ionization and from pressure ionization, producing a wide range of plasma densities depending on the impactor’s velocity. This plasma is initially formed in the warm dense matter (WDM) regime and governed by high energy density (HED) hydrodynamics before it rapidly expands and dissipates, spanning many orders of magnitude in density and length scale. The plasma can also contain a dust component, which is particularly relevant for the lower-velocity range of hypervelocity impacts with parameters that are particularly relevant to Tokamak plasmas. Therefore, the properties and dynamics of these plasmas cannot be fully characterized without considering dusty plasma effects, which are ubiquitous but poorly understood.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Phase-space entropy cascade and irreversibility of stochastic heating in nearly collisionless plasma turbulence

We consider a nearly collisionless plasma consisting of a species of “test particles” in one spatial and one velocity dimension, stirred by an externally imposed stochastic electric field—a kinetic analog of the Kraichnan model of passive advection. The mean effect on the particle distribution function is turbulent diffusion in velocity space—known as stochastic heating. Accompanying this heating is the generation of fine-scale structure in the distribution function, which we characterize with the collisionless (Casimir) invariant C 2 ∝ ∫ ∫ d x d v 〈 f 2 〉 —a quantity that here plays the role of (negative) entropy of the distribution function. We find that C 2 is transferred from large scales to small scales in both position and velocity space via a phase-space cascade enabled by both particle streaming and nonlinear interactions between particles and the stochastic electric field. We compute the steady-state fluxes and spectrum of C 2 in Fourier space, with k and s denoting spatial and velocity wave numbers, respectively. In our model, the nonlinearity in the evolution equation for the spectrum turns into a fractional Laplacian operator in k space, leading to anomalous diffusion. Whereas even the linear phase mixing alone would lead to a constant flux of C 2 to high s (towards the collisional dissipation range) at every k , the nonlinearity accelerates this cascade by intertwining velocity and position space so that the flux of C 2 is to both high k and high s simultaneously. Integrating over velocity (spatial) wave numbers, the k -space ( s -space) flux of C 2 is constant down to a dissipation length (velocity) scale that tends to zero as the collision frequency does, even though the rate of collisional dissipation remains finite. The resulting spectrum in the inertial range is a self-similar function in the ( k , s ) plane, with power-law asymptotics at large k and s . Our model is fully analytically solvable, but the asymptotic scalings of the spectrum can also be found via a simple phenomenological theory whose key assumption is that the cascade is governed by a “critical balance” in phase space between the linear and nonlinear timescales. We argue that stochastic heating is made irreversible by this entropy cascade and that, while collisional dissipation accessed via phase mixing occurs only at small spatial scales rather than at every scale as it would in a linear system, the cascade makes phase mixing even more effective overall in the nonlinear regime than in the linear one. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

The multifunctional use of an aqueous battery for a high capacity jellyfish robot

The batteries that power untethered underwater vehicles (UUVs) serve a single purpose: to provide energy to electronics and motors; the more energy required, the bigger the robot must be to accommodate space for more energy storage. By choosing batteries composed primarily of liquid media [e.g., redox flow batteries (RFBs)], the increased weight can be better distributed for improved capacity with reduced inertial moment. Here, we formed an RFB into the shape of a jellyfish, using two redox chemistries and architectures: (i) a secondary ZnBr 2 battery and (ii) a hybrid primary/secondary ZnI 2 battery. A UUV was able to be powered solely by RFBs with increased volumetric (Q~ 11 ampere-hours per liter) and areal (108 milliampere-hours per square centimeter) energy density, resulting in a long operational lifetime (T~ 1.5 hours) for UUVs composed of primarily electrochemically energy-dense liquid (~90% of the robot’s weight).

Science & Technology - Other Topics↗

DOE OSTI2026

radkit base v1.6

The radkit (base) software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices, cameras, as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations.

Salathe, Marco [Lawrence Berkeley National Laborat↗

DOE OSTI2026

Integrated Process Model Utilization and Development for Inertial Fusion Energy

This CRADA between LLNS and Longview Fusion Energy Systems utilized a modernized LLNL Integrated Process Model (IPM) to assess technoeconomic viability and power plant configurations for Inertial Fusion Energy (IFE). During the collaboration period, a streamlined IPM model was produced by LLNL, which consolidated a combination of 3 models under one file. Additionally, obsolete parameters were removed and parameters available for trade space analysis were organized in a user-friendly fashion on the front interface. Gain scaling curves were discussed and analyzed in the framework of the IPM. Additional updates were made to account for cost scaling to today's dollars using an average inflation rate. Heat transfer material costing was updated using a ground up approach with public vendor data. Further levelized cost of electricity (LCOE) methods and models were discussed and reviewed for applicability to the IPM. Prior published literature on optical scaling was also discussed. Moreover, as part of this CRADA, the Participant developed a fusion technology development roadmap and point designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Integrated Process Model Utilization and Development for Inertial Fusion Energy

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗

DOE OSTI2025

Observations of Subduction, Downward Heat Flux and Dense Filament Collapse in the Northern Gulf of Mexico

Submesoscale processes are important contributors to the global heat budget and generally support upward heat transport through restratification. However, in salinity‐stratified regions, such as the northern Gulf of Mexico with its influx of freshwater from the Mississippi‐Atchafalaya river system, temperature can act like a passive tracer and submesoscale processes can contribute to downward heat transport. Oceanic heat content is a factor in many environmental risks the region faces, for example, hurricane intensification, and marine heatwaves. During the 2022 field campaign of the Submesoscales Under Near‐Resonant Inertial Shear Experiment, a sampling plan was developed to study such submesoscale processes in high resolution. Over 31 hr, four assets (two research ships and two remotely controlled boats) drove in parallel across a dense filament, capturing its evolution in time and space. The observations show that surface waters, warmed by daytime solar radiation, were subducted and that the associated overturning circulation transported heat below the surface layer where it was later irreversibly mixed away. The estimated downward heat flux was as strong as the concurrent net air‐sea heat flux into the ocean. The filament was then observed to rapidly collapse which we attribute to boundary layer turbulence and the breakdown of geostrophic balance. The collapsing fronts display behaviors indicative of gravity currents. These observations highlight how in salinity‐stratified regions, frontal dynamics can be associated with downward heat flux and how the submesoscale can play an important role in the oceanic heat budget.

58 GEOSCIENCES↗