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At least 1,027 records · Page 57

Development of a directly driven multi-shell platform: Laser drive energetics

Simulations predict that directly driven multi-shell targets can provide a robust alternative to conventional high-convergence implosion concepts by coupling two to three times more energy into the final igniting thermonuclear fuel assembly than indirect-drive concepts. The three-shell directly driven Revolver concept [K. Molvig, M. J. Schmitt, B. J. Albright, E.S. Dodd, N.M. Hoffman, G.H. McCall, and S.D. Ramsey, Phys. Rev. Lett. 116, 255003 (2016)] utilizes a design that maximizes laser energy conversion into inward kinetic energy of the outermost ablator shell (~9%) while minimizing the DT fuel convergence (~9) to reduce the mixing of material from the innermost shell into the fuel. Inherent in this design concept is the use of 192 narrow beams (with a 1/e laser beam-to-capsule diameter ratio of 0.33) from the National Ignition Facility laser pointed in a polar direct drive laser configuration. In this paper, we demonstrate that low average laser intensity at the capsule surface (≤300 TW/cm 2 ) limits the measured laser backscatter, indicating that a greater amount of laser energy is coupled into the target. Omega experiments have been performed to determine the coupling of laser energy to the outermost shell of a scaled Revolver target (i.e., the ablator shell) by measuring capsule implosion trajectories and scattered-light fractions for two different drive configurations. Comparisons of simulated shell trajectory and velocity profiles with experimental data obtained from self-emission images show good agreement and are consistent with measured scattered light data. Furthermore, the low levels of scattered light measured are consistent with post-shot simulation results that show high hydro-coupling efficiency. These results strengthen the case for using narrow beams at low intensity to drive large ablator capsules for future direct-drive, multi-shell ignition concepts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observation of shock-front separation in multi-ion-species collisional plasma shocks

We observe shock-front separation and species-dependent shock widths in multi-ion-species collisional plasma shocks, which are produced by obliquely merging plasma jets of a He/Ar mixture (97% He and 3% Ar by initial number density) on the plasma liner experiment. Visible plasma emission near the He-I 587.6-nm and Ar-II 476.5–514.5-nm lines is simultaneously recorded by splitting a single visible image of the shock into two different fast-framing cameras with different narrow bandpass filters (589 ± 5 nm for observing the He-I line and 500 ± 25 nm for the Ar-II lines). For conditions in these experiments (pre-shock ion and electron densities ≈5×10 14 cm –3 , ion and electron temperatures of ≈2.2 eV, and relative plasma-merging speed of 22 km/s), the observationally inferred magnitude of He/Ar shock-front separation and the shock widths themselves are <1 cm, which correspond to ~50 post-shock thermal ion–ion mean free paths. These experimental length scales are in reasonable qualitative and quantitative agreement with results from 1D multi-fluid simulations using the CHICAGO code. However, we note there are differences between the experimentally inferred and simulation-predicted ionization states and line emission intensities, particularly in the post-shock region. Overall, the experimental and simulation results are consistent with theoretical predictions that the lighter He ions diffuse farther ahead within the overall shock front than the heavier Ar ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-photon polymerization printed lattices as support structures in multi-shell ICF targets: Platform development and initial assessment

Recent interest in fielding direct drive multi-shell targets on the NIF [K. Molvig et al., Phys. Rev. Lett. 116, 255003 (2016) and S. X. Hu et al., Phys. Rev. E 100, 063204 (2019)] has highlighted the need for a low density structure to support the inner shell(s) and to avoid energy loss in the acceleration and collision process. We have developed a two-shell platform to evaluate the use of low density two-photon polymerization (2PP) printed lattices as a support structure between the shells. Here, 2PP structures are an attractive option because they can be produced at densities as low as 5 mg/cc, which is ideal for multi-shell targets, and their 3D structure can be tailored to the user's needs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-energy reconstructions, central electron temperature measurements, and early detection of the birth and growth of runaway electrons using a versatile soft x-ray pinhole camera at MST

A multi-energy soft x-ray pinhole camera has been designed, built, and deployed at the Madison Symmetric Torus to aid the study of particle and thermal transport, as well as MHD stability physics. This novel imaging diagnostic technique employs a pixelated x-ray detector in which the lower energy threshold for photon detection can be adjusted independently on each pixel. The detector of choice is a PILATUS3 100 K with a 450 μm thick silicon sensor and nearly 100 000 pixels sensitive to photon energies between 1.6 and 30 keV. An ensemble of cubic spline smoothing functions has been applied to the line-integrated data for each time-frame and energy-range, obtaining a reduced standard-deviation when compared to that dominated by photon-noise. The multi-energy local emissivity profiles are obtained from a 1D matrix-based Abel-inversion procedure. Central values of Te can be obtained by modeling the slope of the continuum radiation from ratios of the inverted radial emissivity profiles over multiple energy ranges with no a priori assumptions of plasma profiles, magnetic field reconstruction constraints, high-density limitations, or need of shot-to-shot reproducibility. In tokamak plasmas, a novel application has recently been tested for early detection, 1D imaging, and study of the birth, exponential growth, and saturation of runaway electrons at energies comparable to 100 × Te,0; thus, early results are also presented.

Delgado-Aparicio, L. F. (ORCID:0000000167394380)↗

A multi-sheath model for highly nonlinear plasma wakefields

An improved description for nonlinear plasma wakefields with phase velocities near the speed of light is presented and compared against fully kinetic particle-in-cell simulations. These wakefields are excited by intense particle beams or lasers pushing plasma electrons radially outward, creating an ion bubble surrounded by a sheath of electrons characterized by the source term S≡−1enp(ρ−Jz/c), where ρ and Jz are the charge and axial current densities, respectively. Previously, the sheath source term was described phenomenologically with a positive-definite function, resulting in a positive definite wake potential. In reality, the wake potential is negative at the rear of the ion column which is important for self-injection and accurate beam loading models. To account for this, we introduce a multi-sheath model in which the source term, S, of the plasma wake can be negative in regions outside the ion bubble. Using this model, we obtain a new expression for the wake potential and a modified differential equation for the bubble radius. Numerical results obtained from these equations are validated against particle-in-cell simulations for unloaded and loaded wakes. The new model provides accurate predictions of the shape and duration of trailing bunch current profiles that flatten plasma wakefields. It is also used to design a trailing bunch for a desired longitudinally varying loaded wakefield. We present beam loading results for laser wakefields and discuss how the model can be improved for laser drivers in future work. Finally, we discuss differences between the predictions of the multi- and single-sheath models for beam loading.

Dalichaouch, T. N. (ORCID:0000000247350150)↗

Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications

Optimization of materials’ performance for specific applications often requires balancing multiple aspects of materials’ functionality. Even for the cases where a generative physical model of material behavior is known and reliable, this often requires search over multidimensional function space to identify low-dimensional manifold corresponding to the required Pareto front. In this work, we introduce the multi-objective Bayesian optimization (MOBO) workflow for the ferroelectric/antiferroelectric performance optimization for memory and energy storage applications based on the numerical solution of the Ginzburg–Landau equation with electrochemical or semiconducting boundary conditions. MOBO is a low computational cost optimization tool for expensive multi-objective functions, where we update posterior surrogate Gaussian process models from prior evaluations and then select future evaluations from maximizing an acquisition function. Using the parameters for a prototype bulk antiferroelectric (PbZrO 3 ), we first develop a physics-driven decision tree of target functions from the loop structures. We further develop a physics-driven MOBO architecture to explore multidimensional parameter space and build Pareto-frontiers by maximizing two target functions jointly—energy storage and loss. This approach allows for rapid initial materials and device parameter selection for a given application and can be further expanded toward the active experiment setting. The associated notebooks provide both the tutorial on MOBO and allow us to reproduce the reported analyses and apply them to other systems (https://github.com/arpanbiswas52/MOBO_AFI_Supplements).

36 MATERIALS SCIENCE↗

A multi-dimensional Child–Langmuir law for any diode geometry

While prior theoretical studies of multi-dimensional space-charge limited current (SCLC) assumed emission from a small patch on infinite electrodes, none have considered emission from an entire finite electrode. In this paper, we apply variational calculus (VC) and conformal mapping, which have previously been used to derive analytic solutions for SCLC density (SCLCD) for nonplanar one-dimensional geometries, to obtain mathematical relationships for any multi-dimensional macroscopic diode with finite cathode and anode. We first derive a universal mathematical relationship between space-charge limited potential and vacuum potential for any diode and apply this technique to determine SCLCD for an eccentric spherical diode. We then apply VC and the Schwartz–Christoffel transformation to derive an exact equation for SCLCD in a general two-dimensional planar geometry with emission from a finite emitter. Particle-in-cell simulations using VSim agreed within 4%–13% for a range of ratios of emitter width to gap distance using the thinnest electrodes practical for the memory constraints of our hardware, with the difference partially attributed to the theory's assumption of infinitesimally thin electrodes. After generalizing this approach to determine SCLCD for any orthogonal diode as a function of only the vacuum capacitance and vacuum potential, we derive an analytical formulation of the three-dimensional Child–Langmuir law for finite parallel rectangular and disk geometries. These results demonstrate the utility for calculating SCLCD for any diode geometry using vacuum capacitance and vacuum potential, which are readily obtainable for many diode geometries, to guide experiment and simulation development.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-throughput, in situ imaging of multi-layer powder-blown directed energy deposition with angled nozzle

Laser metal additive manufacturing (AM) has become an increasingly popular technology due to its flexibility in geometry and materials. As one of the commercialized additive processes, powder-blown directed energy deposition (DED) has been used in multiple industries such as aerospace, automotive, medical device, etc. However, a lack of fundamental understanding remains for this process, and many opportunities for alloy development and implementation can be identified. A high-throughput, in situ DED system capable of multi-layer builds that can address these issues is presented here. In this work, implications of layer heights and energy density are investigated through an extensive process parameter sweep, showcasing the power of a high-throughput setup while also discussing multi-layer interactions.

47 OTHER INSTRUMENTATION↗

Multi-fidelity modeling to predict the rheological properties of a suspension of fibers using neural networks and Gaussian processes

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications. There are multiple factors, such as fiber aspect ratio and volume fraction, that play a significant role in altering the rheological behavior of suspensions. Three-dimensional (3D) numerical simulations of coupled differential equations of the suspension of fibers are computationally expensive and time-consuming. Machine learning algorithms can be trained on the available data and make predictions for the cases where no numerical data are available. However, some widely used machine learning surrogates, such as neural networks, require a relatively large training dataset to produce accurate predictions. Multi-fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified constitutive equations, can pave the way for more accurate predictions. Here, we focus on neural networks and the Gaussian processes with two levels of fidelity, i.e., high and low fidelity networks, to predict the steady-state rheological properties, and compare them to the single-fidelity network. High-fidelity data are obtained from direct numerical simulations based on an immersed boundary method to couple the fluid and solid motion. The low-fidelity data are produced by using constitutive equations. Multiple neural networks and the Gaussian process structures are used for the hyperparameter tuning purpose. Results indicate that with the best choice of hyperparameters, both the multi-fidelity Gaussian processes and neural networks are capable of making predictions with a high level of accuracy with neural networks demonstrating marginally better performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Feedback lock-in: A versatile multi-terminal measurement system for electrical transport devices

Here, we present the design and implementation of a measurement system that enables parallel drive and detection of small currents and voltages at numerous electrical contacts to a multi-terminal electrical device. This system, which we term a feedback lock-in, combines digital control-loop feedback with software-defined lock-in measurements to dynamically source currents and measure small, pre-amplified potentials. The effective input impedance of each current/voltage probe can be set via software, permitting any given contact to behave as an open-circuit voltage lead or as a virtually grounded current source/sink. This enables programmatic switching of measurement configurations and permits measurement of currents at multiple drain contacts without the use of current preamplifiers. Our 32-channel implementation relies on commercially available digital input/output boards, home-built voltage preamplifiers, and custom open-source software. With our feedback lock-in, we demonstrate differential measurement sensitivity comparable to a widely used commercially available lock-in amplifier and perform efficient multi-terminal electrical transport measurements on twisted bilayer graphene and SrTiO 3 quantum point contacts. The feedback lock-in also enables a new style of measurement using multiple current probes, which we demonstrate on a ballistic graphene device.

47 OTHER INSTRUMENTATION↗

Design of a Multi-Monochromatic X-ray Imager (MMI) for Kr K-shell line emission

We report the Multi-Monochromatic X-ray Imager (MMI) is a time-gated spectrometer used in implosion experiments at the OMEGA laser facility. From the data, electron temperature and density spatial distributions can be obtained at different implosion times. Previous MMI designs used Ar K-shell emission (3–6 keV) as a spectroscopic tracer and provided a spectral resolution of around 20 eV. However, Ar K-shell line emission becomes less useful at electron temperatures above 2 keV due to over-ionization. Kr K-shell (12–16 keV) has been shown to be an attractive alternative to diagnose hot implosion cores in recent publications. The purpose of this paper is to show a new point design that allows the MMI to detect this higher photon energy range with suitable spectral resolution. The algorithm used to find the optimal design couples a ray-tracing code and an exhaustive parameter space search. This algorithm may be useful as a tool to find optimal MMI designs for other purposes, i.e., other spectral regions for other spectroscopic tracers. So, the main change between the two designs is the replacement of the multi-layer mirror with a flat Bragg Ge (220) crystal. The final Kr K-shell MMI design has a photon energy range from 12 to 16.1 keV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A machine learning framework for elastic constants predictions in multi-principal element alloys

On the one hand, multi-principal element alloys (MPEAs) have created a paradigm shift in alloy design due to large compositional space, whereas on the other, they have presented enormous computational challenges for theory-based materials design, especially density functional theory (DFT), which is inherently computationally expensive even for traditional dilute alloys. In this paper, we present a machine learning framework, namely PREDICT (PRedict properties from Existing Database In Complex alloys Territory), that opens a pathway to predict elastic constants in large compositional space with little computational expense. The framework only relies on the DFT database of binary alloys and predicts Voigt–Reuss–Hill Young’s modulus, shear modulus, bulk modulus, elastic constants, and Poisson’s ratio in MPEAs. We show that the key descriptors of elastic constants are the A–B bond length and cohesive energy. The framework can predict elastic constants in hypothetical compositions as long as the constituent elements are present in the database, thereby enabling property exploration in multi-compositional systems. We illustrate predictions in a FCC Ni-Cu-Au-Pd-Pt system.

Linton, Nathan (ORCID:0000000315485613)↗

The competing effects of wave amplitude and collisions on multi-ion species suppression of stimulated Brillouin scattering in inertial confinement fusion Hohlraums

Reduction in stimulated Brillouin scattering (SBS) from National Ignition Facility Hohlraums has been predicted through the use of multi-ion species materials on Hohlraum walls. This approach to controlling SBS is based upon introducing a lighter ion species to the heavier ion species Hohlraum wall in order to greatly increase the ion Landau damping of ion acoustic waves (IAWs). In a collisionless plasma, if the IAWs driven by SBS reach sufficient amplitudes, this increased damping is reduced or even eliminated by ion trapping in the IAWs. Here, the nonlinear behavior of IAWs is simulated with a multi-ion species Vlasov code, including interspecies ion–ion collisions, self-collisions, and electron–ion pitch-angle collisions. The effect of collisions on the trapping of ions and electrons in a large-amplitude IAW is studied in a regime of relevance to current Inertial Confinement Fusion experiments. Our simulations show that collisions can scatter trapped particles out of resonance with the IAW, suppressing trapping and helping to maintain an effective Landau damping of the IAW. The IAW amplitude required to trap particles in the presence of strong collisions is estimated analytically. These estimates are tested for strongly damped IAWs in tantalum oxide and pure helium plasmas. Here our simulations show that, above a threshold amplitude, the damping is reduced by an amount inversely proportional to the wave amplitude. Thus, the success of controlling SBS using a multispecies plasma may depend sensitively on laser power and pulse length.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-timescale operations of nuclear-renewable hybrid energy systems for reserve and thermal product provision

In this paper, an optimal operation strategy of a nuclear-renewable hybrid energy system (N-R HES), in conjunction with a district heating network, is developed within a comprehensive multi-timescale electricity market framework. The grid-connected N-R HES is simulated to explore the capabilities and benefits of N-R HES of providing energy products, different reserve products, and thermal products. An N-R HES optimization and control strategy is formulated to exploit the benefits from the hybrid energy system in terms of both energy and ancillary services. A case study is performed on the customized NREL-118 bus test system with high renewable penetrations, based on a multi-timescale (i.e., three-cycle) production cost model. Both day-ahead and real-time market clearing prices are determined from the market model simulation. In conclusion, the results show that the N-R HES can contribute to the reserve requirements and also meet the thermal load, thereby increasing the economic efficiency of N-R HES (with increased revenue ranging from 1.55% to 35.25% at certain cases) compared to the baseline case where reserve and thermal power exports are not optimized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A versatile pressure-cell design for studying ultrafast molecular-dynamics in supercritical fluids using coherent multi-pulse x-ray scattering

Supercritical fluids (SCFs) can be found in a variety of environmental and industrial processes. They exhibit an anomalous thermodynamic behavior, which originates from their fluctuating heterogeneous micro-structure. Characterizing the dynamics of these fluids at high temperature and high pressure with nanometer spatial and picosecond temporal resolution has been very challenging. The advent of hard x-ray free electron lasers has enabled the development of novel multi-pulse ultrafast x-ray scattering techniques, such as x-ray photon correlation spectroscopy (XPCS) and x-ray pump x-ray probe (XPXP). These techniques offer new opportunities for resolving the ultrafast microscopic behavior in SCFs at unprecedented spatiotemporal resolution, unraveling the dynamics of their micro-structure. However, harnessing these capabilities requires a bespoke high-pressure and high-temperature sample system that is optimized to maximize signal intensity and address instrument-specific challenges, such as drift in beamline components, x-ray scattering background, and multi-x-ray-beam overlap. We present a pressure cell compatible with a wide range of SCFs with built-in optical access for XPCS and XPXP and discuss critical aspects of the pressure cell design, with a particular focus on the design optimization for XPCS.

47 OTHER INSTRUMENTATION↗

Violation of the Cauchy–Born rule in multi-principal element alloys

Multi-principal element alloys are a novel class of materials that are formed by combining multiple elements in high concentrations and show exceptional properties compared to conventional alloys. These alloys have high configurational entropy due to inherent atomic disorder. The Cauchy–Born rule is a popular homogenization method for linking atomistic to continuum length scales. In this Letter, we use ab initio density functional theory calculations to report that the Cauchy–Born rule, which holds in conventional alloys in the absence of defects, is not valid in multi-principal element alloys. Further, the violation of the Cauchy–Born rule in these alloys is attributed to the presence of atomic disorder due to which the deformations are inhomogeneous. Our results also show the deviations in deformation are related to the magnitude of the stretch and shear by power laws.

36 MATERIALS SCIENCE↗

On anomalous transport of multi-species plasma associated with the resistive ballooning and resistive drift waves driven turbulence

Anomalous transport of multi-species plasma related to the resistive ballooning and resistive drift wave turbulence is considered in a “cold” ion approximation. It is found that similar to the resistive drift wave turbulence [see A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024); and S. I. Krasheninnikov and R. D. Smirnov, Phys. Plasmas (to be published)] the addition of the ballooning drive does not change the main features of anomalous transport of the multi-species plasma: (i) The transport of all ion species is described as a transport of the passive scalars in the turbulent field of the electrostatic potential and electron density perturbation; (ii) the density of ion species with a larger ratio of the mass to charge has the tendency to the accumulation/depletion in the vortices of plasma flow; and (iii) the cross-field transport of all plasma species (including electrons and ions) is described by the same anomalous transport coefficient.

Physics↗