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This is a correction to: Nonlinear models for coupling the effects of stimulated Raman scattering to inertial confinement fusion codes
Stimulated Brillouin scattering (SBS) is a potential risk for laser damage in the experiments carried out at the National Ignition Facility (NIF), and by altering the energy deposition pattern in hohlraums, it affects the symmetry of indirect-drive inertial confinement fusion implosions. We have surveyed backward SBS on outer-cone quads across NIF integrated hohlraums of various platforms numerically, using three-dimensional (3D) simulations with the backscatter code pF3D [Berger et al. Phys. Plasmas 5, 4337 (1998)] and ray-based gain calculations. Simulated reflected powers and energies, as well as the spectrum of reflected light all compare favorably with measurements. Ray-based calculations of exponential SBS amplification (“gain”), which assume a strongly damped plasma wave and steady-state response, are performed using a novel method that includes the 3D speckled field of the laser that drives SBS. This approach is useful for understanding qualitative differences between hohlraum designs and identifying regions susceptible to SBS within hohlraums. Quantitatively, gains are not found to correlate with SBS reflectivities in 3D, necessitating fully wave-based calculations that naturally include diffraction and various temporal dependencies.
In direct-drive inertial confinement fusion, target offset from the target chamber center (or center of beam convergence) may lead to significant implosion asymmetry and fusion yield degradation. In addition, cross-beam energy transfer (CBET) has been shown to be a significant source of laser energy scattering and leads to a reduction in implosion velocity and yield. To improve energy coupling and implosion performance, several techniques for CBET mitigation have been proposed. Recent simulations, however, have shown that CBET also substantially mitigates the effect of target offset on implosion asymmetry and yield [Anderson et al., Phys. Plasmas 27, 112713 (2020)]. Furthermore, the inclusion of CBET models in radiation-hydrodynamics codes was shown to greatly improve agreement between simulations and experiments involving substantial target offset distances. This paper explores the intensity dependence of this CBET–offset effect. In addition, it is shown that enhanced sensitivity to target offset can be expected when CBET-mitigation techniques are used in direct-drive implosions. This is shown through simulations of two such CBET-mitigation techniques on the OMEGA laser: (1) decreased beam-to-target radius, and (2) beam-to-beam frequency detuning. For the typical target offset distances (<15 μm) observed in experiments on OMEGA, however, overall yield is still anticipated to be substantially higher when CBET-mitigation techniques are employed.
Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical simulations to guide design. As simulation technology progresses, so too can the fidelity of models used to plan for new experiments. However, these high-fidelity models are by themselves insufficient for optimal experimental design, because their computational cost remains too high to efficiently and effectively explore the numerous parameters required to describe a typical experiment. Therefore, traditionally, ICF design has relied on low-fidelity modeling to initially identify potentially interesting design regions, which are then subsequently explored via selected high-fidelity modeling. In this paper, we demonstrate that this two-step approach can be insufficient: even for simple design problems, a two-step optimization strategy can lead high-fidelity searching toward incorrect regions and consequently waste computational resources on parameter regimes far away from the true optimal solution. We reveal that a primary cause of this behavior in ICF design problems is the presence of low-fidelity optima in different regions of the parameter space far away from high-fidelity optima. To address this issue, we propose an iterative multifidelity Bayesian optimization method based on Gaussian Process Regression that leverages both low- and high-fidelity models simultaneously. We demonstrate, using both two- and eight-dimensional ICF test problems, that our algorithm can effectively utilize both low-fidelity and high-fidelity models to refine the designs. This approach proves to be more efficient than relying solely on high-fidelity modeling for optimization.
3D asymmetries are major degradation mechanisms in inertial-confinement fusion implosions at the National Ignition Facility (NIF). These asymmetries can be diagnosed and reconstructed with the neutron imaging system (NIS) on three lines of sight around the NIF target chamber. Conventional tomographic reconstructions are used to reconstruct the 3D morphology of the implosion using NIS [Volegov et al., J. Appl. Phys. 127, 083301 (2020)], but the problem is ill-posed with only three imaging lines of sight. Asymmetries can also be diagnosed with the real-time neutron activation diagnostics (RTNAD) and the neutron time-of-flight (nToF) suite. Since the NIS, RTNAD, and nToF each sample a different part of the implosion using different physical principles, we propose that it is possible to overcome the limitations of too few imaging lines of sight by performing 3D reconstructions that combine information from all three heterogeneous data sources. This work presents a new machine learning-based reconstruction technique to do just this. By using a simple physics model and group of neural networks to map 3D morphologies to data, this technique can easily account for data of multiple different types. A simple proof-of-principle is presented, demonstrating that this technique can accurately reconstruct a hot-spot shape using synthetic primary neutron images and a hot-spot velocity vector. In particular, the hot-spot’s asymmetry, quantified as spherical harmonic coefficients, is reconstructed to within ±4% of the radius in 90% of test cases. In the future, this technique will be applied to actual NIS, RTNAD, and nToF data to better understand 3D asymmetries at the NIF.
The evolution of plasma profiles and radial electric fields in the edge of tokamaks during a transition to an improved confinement regime is explored in an unfavorable configuration based on self-consistent, flux-driven simulations of reduced Braginskii models with ion pressure dynamics. The edge plasma response to the heating power is explored by varying the heat source strength. The energy transfer from turbulent to mean flows is induced by the large-amplitude fluctuations as the power input becomes sufficiently strong. It is found that ion pressure fluctuations play an important role in the generation of the Reynolds power. Consequently, the plasma spontaneously forms radial electric fields localized at the edge, which reduces the radial correlation and amplitudes of edge fluctuations. An edge temperature pedestal also forms while the density profiles remain nearly unchanged, featuring an I-mode-like regime.
The quantum efficiency of AlGaN ultraviolet light-emitting diodes declines (droops) at increasing operating powers due to Auger–Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron–phonon coupling and alloy disorder can induce bulk C coefficients as large as ~10 –31 cm 6 /s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. Furthermore, this results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop.
Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.
Stronger light confinement can be enabled by nanoantennas in the nanostructure and result in efficient control of the directionality of the scattering. We report on an observation of the well-pronounced multipolar resonances from nickel nanoantennas originating from collective effects. We show that the collective coupling of multipolar modes from weak scatterers can substantially enhance the electric dipole and quadrupole resonances. We also demonstrate the generalized lattice Kerker effect in this nanoantenna array. Resonant multipolar excitations within nickel nanoantenna arrays can significantly enhance phenomena such as magneto-optical effects, indicating promising potential for advanced applications in the field of nanophotonics and sensing.
Energetic charged particles generated by inertial confinement fusion (ICF) implosions encode information about the spatial morphology of the hotspot and dense fuel during the time of peak fusion reactions. The knock-on deuteron imager (KoDI) was developed at the Omega Laser Facility to image these particles in order to diagnose low-mode asymmetries in the hotspot and dense fuel layer of cryogenic deuterium–tritium ICF implosions. However, the images collected are distorted in several ways that prevent reconstruction of the deuteron source. In this paper, we describe these distortions and a series of attempts to mitigate or compensate for them. We present several potential mechanisms for the distortions, including a new model for scattering of charged particles in filamentary electric or magnetic fields surrounding the implosion. Particle-tracing is used to create synthetic KoDI data based on the filamentary field model that reproduces the main experimentally observed image distortions. We conclude that the filamentary scattering model best matches the observed image distortions. Finally, we discuss potential impacts of filamentary fields on other charged-particle diagnostics.
Microscopic segregation and molecular heterogeneities in complex liquids are the result of the interplay between different intermolecular forces, all of which contribute to the energy landscape of the system. A consequence of the intricate energy landscape is the nontrivial effect on the solvation dynamics. Here, the impact of molecular heterogeneities on the solvation dynamics is studied using infrared spectroscopies and molecular dynamics simulations. In particular, this study focuses on the dynamical effect of nanoscopic heterogeneities present in deep eutectic solvents (DESs) composed of lauric acid (LA) and N-methylacetamide (NMA). To this end, a molecular probe containing a carbon triple bond is used as an infrared reporter. The results show that the vibrational probe is likely to be located in the NMA polar domains. Furthermore, the probe solvation dynamics derived from the 2DIR spectra presents a slowdown of its timescale with increasing LA concentration in the DES. Kubo modeling of the probe solvation dynamics shows a correlation between the amplitude of its long time component and the presence of molecular heterogeneities in the sample. Semiclassical modeling of the vibrational line shape of the triple bond stretch demonstrates that the heterogeneities affect the whole solvation dynamics of the system through the amplitudes of the frequency fluctuations. Molecular dynamics simulations confirm the experimental results and their interpretation by showing a slowdown of the solvation dynamics when the LA heterogeneities are present. Overall, the study presents a molecular framework to explain the effect of confinement created by nanoscopic LA heterogeneities on the solvation dynamics of the system.
Laser-driven, indirect-drive inertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) recently achieved a target gain greater than one, where fusion energy output exceeds input laser energy [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Despite this milestone, gain levels remain insufficient for practical applications such as inertial fusion energy, making performance improvement critical. One promising approach is increasing fuel compression by lowering the implosion adiabat. To explore reduced adiabat, experiments were conducted modifying the laser pulse shape and shock timing of an existing 1.9-MJ-drive implosion design performing near the ignition cliff [Abu-Shawareb et al., Phys. Rev. Lett. 129, 075001 (2022)]. These experiments demonstrated increased compression and fusion yield in ICF implosions at the NIF by using a lower fuel adiabat, and increased compression with a reduced adiabat in high-density carbon ablators. The updated design achieved up to 80% higher fusion yield and 14% greater fuel compression compared to the previous best-performing 1.9-MJ experiment, with repeatable performance, and is the only implosion design to achieve a target gain exceeding one with < 2.04 MJ laser energy. Notably, this work was made possible because of recent advances in target quality and pulse shape control allowing experimental access to the ignition regime, and thereby increased sensitivity to adiabat. This work addresses a long-standing question in ICF research and lays the foundation for higher target gains through optimized implosion strategies. It underscores the potential of reduced adiabat designs to enhance compression and fusion yields for future ICF applications.
Current delivery in pulsed power inertial confinement fusion is influenced by collisionless current-carrying microturbulent plasmas, which are sourced from electrode surfaces. In this setting, the lower hybrid drift instability—triggered by plasma acceleration—is a leading candidate driver of difficult-to-predict momentum and energy transport. To characterize the nonlinear state of the microturbulent plasma, a parameterized anomalous transport model is developed for the instability, with analytic formulas for anomalous collision frequency, resistivity, and species heating rates. The formulas are expressed in terms of linear-theory variables and four dimensionless parameters that characterize the macroscopic plasma state. The model is built on linear theory analysis, power law analysis, and quasilinear theory analysis, and is validated using a series of nonlinear continuum kinetic Vlasov–Poisson simulations. The theoretical and computational investigation demonstrates that the anomalous collision frequency associated with the instability can be reliably approximated, within about a factor of five or better, by the unscaled linear theory growth rate of the fastest-growing wavenumber mode. This finding enables efficient calculation of anomalous resistivity and species heating rates over a wide range of plasma conditions, resulting in improved predictive capabilities.
In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.
Engineering shallow nitrogen-vacancy (NV) centers in diamond holds the key to unlocking new advances in nanoscale quantum sensing. We find that the creation of near-surface NVs through delta doping during diamond growth allows for tunable control over both NV depth confinement (with a twofold improvement relative to low-energy ion implantation) and NV density, ultimately resulting in highly sensitive single defects and ensembles with coherence limited by NV–NV interactions. Additionally, we demonstrate the utility of our shallow delta-doped NVs by imaging magnetism in few-layer CrSBr, a two-dimensional magnet. Here, we anticipate that the control afforded by near-surface delta doping will enable new developments in NV quantum sensing from nanoscale nuclear magnetic resonance to entanglement-enhanced metrology.
Using highly resolved three-dimensional radiation-hydrodynamic simulations, the effects of wetted-foam (WF) ablators in direct-drive inertial confinement fusion cryogenic implosions on the OMEGA laser were investigated. The performance of these implosions was compared with that of implosions using targets with solid-plastic ablators. Simulations considering WF ablators as a homogeneous material show no mitigation of the effects of laser imprint, where the absence of this mitigation can be attributed to the use of picket pulses. Heterogeneous random-structure WF ablators introduce large short-wavelength perturbations, which are seeded by WF inhomogeneities. These perturbations exceed the perturbations seeded by the imprint and cause an additional reduction in implosion performance when the average pore size in the WF exceeds ~0.2 μm. Foam-seeded perturbations are expected to be less damaging in more stable high-adiabat ( ≳ 5) implosions. Here, the perturbations introduced by the WF ablators can be substantially reduced by using a foam matrix with a layered structure instead of a random one. Further study of the effects of WFs in ignition designs of the MJ laser energy scale is required in the perspective of future inertial fusion energy mass production.
The next-generation Particle X-ray Temporal Diagnostic (PXTD) has been implemented for simultaneous measurements of x-ray, charged particle, and neutron emission histories from a wide range of inertial confinement fusion and high energy density plasma experiments, demonstrating excellent timing accuracy and greatly improved experimental flexibility. The key changes to the previously fielded system are a redesigned set of thin foil filters in front of the scintillators and individual neutral density filters for each region of the detector. The fully implemented PXTD system can provide unique information about the evolution of ion and electron temperatures in multi-ion and kinetic-physics experiments, proton radiography experiments, and DT experiments executed at the OMEGA facility. The system has 35 ps time resolution and negligible relative timing uncertainty between measured emission history signals. The first use of the upgraded four-channel PXTD system during a set of D 3 He-filled silica-glass implosions on OMEGA captured electron temperatures with a minimum uncertainty of 0.5 keV and resolved both the relative timings and widths of neutron, proton, and x-ray peaks within a single recorded image.
Applying an external magnetic field to laser-driven inertial confinement fusion implosions is a promising approach for enhancing fusion yield. The field is compressed with the plasma, producing a magnetized hotspot that anisotropically suppresses thermal losses and traps alpha particles, making performance sensitive to the compressed field orientation. Here, we derive a simple, readily applicable analytic model that enables rapid evaluation of the compressed field topology and show that ablation into the hotspot amplifies the central field, while the ablated ice near the hotspot edge develops a decaying, radially bent field, with a discontinuity in the field direction. The radially bent field renders thermal insulation at the hotspot edge negligible and largely independent of the applied field strength, whereas insulation in the hotspot core still depends strongly on the applied field. Applying the model to non-axial initial field configurations, we find that an initially applied mirror field provides the greatest suppression, followed by the standard axial field.