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At least 1,099 records · Page 61

On the merit of hot ion mode for tearing mode stabilization

The stabilization of tearing modes with rf driven current benefits from the cooperative feedback loop between rf power deposition and electron temperature within the island. This effect, termed rf current condensation, can greatly enhance and localize the current driven within magnetic islands. It has previously been shown that the condensation effect opens the possibility of passive stabilization with broad rf profiles, as would be typical of LHCD for steady state operation. Here, we show that this self-healing effect can be dramatically amplified by operation in a hot ion mode, due to the additional electron heat source provided by the hotter ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Upgrade of the helically symmetric experiment Thomson scattering diagnostic suite

The Helically Symmetric eXperiment (HSX) Thomson Scattering (TS) diagnostic is being upgraded to decrease uncertainty in electron temperature and density measurements. Upgrades to the HSX TS diagnostic will consist of a novel redesign of polychromator electronics and digitization of the TS output signal. Here, we also present a study of the benefits of an additional spectral channel that will sample the red-shifted band of the scattered spectrum. In conclusion, to maximize system bandwidth (BW) and gain, while minimizing noise, the existing low-BW polychromator electronics on HSX will be replaced by high-BW, high gain circuitry designed in-house.

47 OTHER INSTRUMENTATION↗

Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules

Bayesian optimization has shown promise for the design optimization of inertial confinement fusion targets. Specifically, in Vazirani et al. [Phys. Plasmas 28 , 122709 (2021)], optimal designs for double shell capsules with graded inner shells were identified using one-dimensional xRAGE simulation yield calculations. While the machine learning models were able to accurately learn and predict one-dimensional simulation target performance, using simulations with higher fidelity would improve design optimization and better match with the expected experimental performance. However, higher fidelity physics modeling, i.e., two-dimensional xRAGE simulations, requires significantly larger computational time/cost, usually at least an order of magnitude, in comparison with one-dimensional simulations. This study presents a multi-fidelity Bayesian optimization, in which the machine learning model leverages low-fidelity (one-dimensional xRAGE) and high-fidelity (two-dimensional xRAGE) simulations to more accurately predict “pre-shot” target performance with respect to the expected experimental performance. By building a multi-fidelity Bayesian optimization framework coupled with xRAGE, the low-fidelity and high-fidelity simulations are able to inform one another, such that we have: (1) improved physics modeling in comparison with using low-fidelity simulations alone, (2) reduced computational time/cost in comparison with using high-fidelity simulations alone, and (3) more confidence in the expected performance of optimized targets during real-world experiments. In the future, we plan to use this robust multi-fidelity Bayesian optimization methodology to expedite the design of graded inner shells further and eventually full capsules as a part of the current double shell campaign at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer

The photon flux resulting from high-energy electron beam interactions with high-field systems, such as those found in the upcoming FACET-II experiments at the SLAC National Accelerator Laboratory, yields deep insight into the electron beam’s underlying dynamics during the interaction. However, extracting this information is an intricate process. To demonstrate how to approach this challenge using modern methods, this paper utilizes simulated data that models plasma wakefield acceleration-derived betatron radiation in experiments to determine reliable methods of reconstructing key beam and beam-plasma interaction properties. For betatron radiation measurements, translating the observed 200⁢ keV to 30⁢ MeV photon double-differential energy-angle spectra obtained from an advanced Compton spectrometer requires testing multiple methods to optimize the pipeline from its response to incident electron beam information. The paper compares maximum likelihood estimation and machine learning to refine the translation of photon spectra into precise electron beam metrics, such as spot size, energy, and emittance, enhancing the understanding of beam behavior within these dense, high-field environments. We also introduce machine learning and the expected maximization algorithm to reconstruct the primary photon spectrum, employing a multilayer neural network for regression analysis of the energy and angle spectra. With appropriate modifications, the advanced methods reproduce relevant incident beam parameters with high accuracy, even for beam sizes in the <10 μ⁢m range. This capacity is critical to understanding intense beam propagation and its optimization in plasma.

Beam code development & simulation techniques↗

Electron acceleration at oblique angles via stimulated Raman scattering at laser irradiance >10 16 W cm –2 μm 2

The generation of hot, directional electrons via laser-driven stimulated Raman scattering (SRS) is a topic of great importance in inertial confinement fusion (ICF) schemes. Little recent research has been dedicated to this process at high laser intensity, in which back, side, and forward scatter simultaneously occur in high energy density plasmas, of relevance to, for example, shock ignition ICF. In this paper, we present an experimental and particle-in-cell (PIC) investigation of hot electron production from SRS in the forward and near-forward directions from a single speckle laser of wavelength λ 0 = 1.053μm, peak laser intensities in the range I 0 = 0.2–1.0×10 17 Wcm –2 and target electron densities between ne = 0.3–1.6% n c , where n c is the plasma critical density. As the intensity and density are increased, the hot electron spectrum changes from a sharp cutoff to an extended spectrum with a slope temperature T = 34 ± 1 keV and maximum measured energy of 350 keV experimentally. Multidimensional PIC simulations indicate that the high energy electrons are primarily generated from SRS-driven electron plasma wave phase fronts with k vectors angled ~50° with respect to the laser axis. These results are consistent with analytical arguments that the spatial gain is maximized at an angle which balances the tendency for the growth rate to be larger for larger scattered light wave angles until the kinetic damping of the plasma wave becomes important. The efficiency of generated high energy electrons drops significantly with a reduction in either laser intensity or target electron density, which is a result of the rapid drop in growth rate of Raman scattering at angles in the forward direction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrating the Value of Resilience into Energy Decisions

The value of resilience can be quantified and integrated into decision making to help inform economic, resilient, and sustainable energy deployment decisions using tools and analysis. Traditionally, distributed energy deployment decisions have often been based on how much energy, or how much money, a system can save. More and more, building owners and communities are recognizing that these systems can also provide a resilience value by sustaining critical loads during an outage. In order to consider the value of resilience in investment decisions, we must quantify how much resilience a system provides, assign a value to that resilience, and monetize that value through grid services, incentives, or other methods. This presentation discusses methods, tools, advantages, and challenges inherent to the process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Intense cavitation-assisted electric discharge as a promising tool for water treatment

This study investigates interrelations between one-electrode Cavitation-Assisted Electric Discharge (CAED), two-electrode CAED, and recently discovered Intense CAED (I-CAED). The one-electrode CAED is a self-triggered nanosecond discharge with pulse energy in the micro-Joule range, which can be generated even by a DC voltage. I-CAED consists of a non-equilibrium part within a low-pressure cavitating region and a micro-spark traversing a liquid film. We hypothesize that CAED propagates from the high-voltage electrode as an ionization wave through bubbles of saturated vapor. Subsequently, the streamer-like discharges in the bubbles may form a continuous plasma channel. Inside the cavitating region, the plasma is strongly non-equilibrium, providing an ideal environment for generating chemically unstable species such as hydrogen peroxide (H 2 O 2 ). Plasma of I-CAED spark is characterized by high electron density and near-thermal equilibrium, emitting a continuous ultraviolet spectrum. The combination of these different discharge parts makes I-CAED in water a highly effective tool for the Advanced Oxidation Process, particularly in water disinfection. Experimentally demonstrated Electric Energy per Order value for disinfection of E. coli-contaminated water is as low as 0.135 ± 0.035 kWh/m 3 /order. Estimates show that the implementation of “dry electrodes” configuration reduces the erosion rate of the electrode material by at least one order of magnitude. Spectral analysis reveals that the continuum emission generated by I-CAED in proximity to metal electrodes deviates from the spectra of discharges spatially decoupled from the electrodes. We assume that this spectral divergence is attributable to blackbody-like emission originating from metallic nanoparticles form during the electrode's erosion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A reaction mechanism for plasma electrolysis of AgNO 3 forming silver nanoclusters and nanoparticles

In plasma-driven solution electrolysis (PDSE), gas-phase plasma-produced species interact with an electrolytic solution to produce, for example, nanoparticles. An atmospheric pressure plasma jet (APPJ) directed onto a liquid solution containing a metallic salt will promote reduction of metallic ions in solution, generating metallic clusters that nucleate to form nanoparticles. In this article, results from a computational investigation are discussed of a PDSE process in which a radio-frequency APPJ sustained in helium impinges on a silver nitrate solution, resulting in growth of silver nanoparticles. A reaction mechanism was developed and implemented in a global plasma chemistry model to predict nanoparticle growth. To develop the reaction mechanism, density functional theory was used to generate probable silver growth pathways up to Ag 9 . Neutral clusters larger than Ag 9 were classified as nanoparticles. Kinetic reaction rate coefficients for thermodynamically favorable growth pathways were estimated based on an existing, empirically determined base reaction mechanism for smaller Ag particle interactions. These rates were used in conjunction with diffusion-controlled reaction rate coefficients that were calculated for other Ag species. The role of anions in reduction of Agn ions in forming nanoparticles is also discussed. Oxygen containing impurities or admixtures to the helium, air entrainment into the APPJ, and dissociation of saturated water vapor above the solution can produce additional reactive oxygen species in solution, resulting in the production of anions and O 2 – in particular. For a given molarity, delivering a sufficient fluence of reducing species will produce similar nanoparticle densities and sizes for all applied power levels. In conclusion, comparisons are made to alternate models for nanoparticle formation, including charged nanoparticles and use of direct current plasmas.

36 MATERIALS SCIENCE↗

High Heat Flux Testing of Castellated Graphite Plasma- Facing Components

As part of the recovery project of the National Spherical Tokamak Experiment–Upgrade (NSTX-U), the divertor plasma-facing components (PFCs) were redesigned to handle significantly higher heat fluxes and longer pulse lengths than NSTX. The design process resulted in a castellated, graphite PFC tile. To verify the thermal performance of this design, dedicated electron beam, high heat flux (HHF) testing was carried out on a de-optimized mock-up PFC target. These tests demonstrated that the tile design is itself robust to large, localized thermal gradients. No mechanical damage to the mock-up was observed during HHF testing, though the actual PFC tile mechanical tie-down was not tested. Rather, when the surface temperature exceeded the sublimation temperature of graphite, carbon blooms from the mock-up tile surface were observed. Finally, this resulted in 1 to 2 mm of surface material ablating from the mock-up after repeated, highly localized electron beam exposures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fusion gain from cylindrical liner-driven implosions of field reversed configurations

MagLIF experiments [M.R. Gomez et al., Phys. Plasmas 22, 056306 (2015)] on Z have demonstrated the basic principles of Magneto-Inertial Fusion (MIF) for wall confined plasmas. Other MIF schemes have been proposed based on the liner implosion of closed field magnetically confined plasmas such as Field Reversed Configurations (FRCs) [T. P. Intrator et al., Phys. Plasmas 15, 042505 (2008)]. We present a semi-analytical model of liner driven FRC implosions that predicts the fusion gain of such systems. The model predicts a fusion gain near unity for an FRC imploded by a liner driven by the Z Machine. We show that FRCs could be formed and imploded at the Z facility using the AutoMag liner concept [S. A. Slutz et al., Phys. Plasmas 24, 012704 (2017)]. Furthermore, an initial bias magnetic field can be supplied by the external magnets used in MagLIF experiments. The reverse field is then supplied by an AutoMag liner, which has helical conducting paths imbedded in an insulating substance. Experiments [Shipley et al., Phys. Plasmas 26, 052705 (2019)] have demonstrated that AutoMag can generate magnetic fields greater than 30 Tesla inside of the liner. We have performed 2D Radiation MHD simulations of the formation and implosion of an FRC, which are in good agreement with the analytical model. The FRC formation process could be studied on small pulsed power machines delivering about 1 MA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Laser Wakefield Accelerator modelling with Variational Neural Networks

A machine learning model was created to predict the electron spectrum generated by a GeV-class laser wakefield accelerator. The model was constructed from variational convolutional neural networks, which mapped the results of secondary laser and plasma diagnostics to the generated electron spectrum. An ensemble of trained networks was used to predict the electron spectrum and to provide an estimation of the uncertainty of that prediction. It is anticipated that this approach will be useful for inferring the electron spectrum prior to undergoing any process that can alter or destroy the beam. In addition, the model provides insight into the scaling of electron beam properties due to stochastic fluctuations in the laser energy and plasma electron density.

43 PARTICLE ACCELERATORS↗

Bias-pulsed atomic layer etching of 4H-silicon carbide producing subangstrom surface roughness

A new approach to atomic layer etching (ALE) has been demonstrated, and its application to 4H-SiC is reported here. By pulsing only the DC bias for an Ar/Cl2 inductively coupled plasma-reactive ion etching system, the etch cycle duration is reduced by more than an order of magnitude relative to conventional ALE processes. Gas flows are not changed throughout the ALE process. With this process protocol, we achieved an etch rate of 2.48±0.09 Å/cycle with 6 s cycles, an RMS surface roughness (Rq) of 0.83±0.08 Å, and an ALE synergy value of S = 99%. The parameters explored within this ALE process demonstrate effective subangstrom smoothening of 4H-SiC surfaces and is well-suited for a variety of classical and quantum device nanofabrication.

42 ENGINEERING↗

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗

Inductively Coupled Nonthermal Plasma Synthesis of Size-Controlled γ-Al 2 O 3 Nanocrystals

Gamma alumina (γ-Al 2 O 3 ) is widely used as a catalyst and catalytic support due to its high specific surface area and porosity. However, synthesis of γ-Al 2 O 3 nanocrystals is often a complicated process requiring high temperatures or additional post-synthetic steps. Here, we report a single-step synthesis of size-controlled and monodisperse, facetted γ-Al 2 O 3 nanocrystals in an inductively coupled nonthermal plasma reactor using trimethylaluminum and oxygen as precursors. Under optimized conditions, we observed phase-pure, cuboctahedral γ-Al 2 O 3 nanocrystals with defined surface facets. Nuclear magnetic resonance studies revealed that nanocrystal surfaces are populated with AlO 6 , AlO 5 and AlO 4 units with clusters of hydroxyl groups. Nanocrystal size tuning was achieved by varying the total reactor pressure yielding particles as small as 3.5 nm, below the predicted thermodynamic stability limit for γ-Al 2 O 3 .

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Modulation-slippage trade-off in resonant four-wave upconversion

Following up on a proposal to use four-wave mixing in an underdense plasma at mildly relativistic laser intensities to produce vastly more energetic x-ray pulses [V. M. Malkin and N. J. Fisch, Phys. Rev. E, 101, 023211 (2020)], we perform the first numerical simulations in one dimension to illustrate amplification of a short high frequency seed through four-wave mixing. Here, we illustrate how parasitic processes including phase modulation and spatial pulse slippage limit the amplification efficiency. Although the regimes studied were not where the optimal efficiencies were expected, these regimes do expose the basic physical processes at play, while still yielding not insignificant spectral power upshift.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterizing W sources in the all-W wall, all-RF WEST tokamak environment

In this work, experimental data, together with interpretive modeling tools, are examined to study trends in the tungsten (W) source in the all-W environment of the WEST tokamak, both from the divertor and from the main chamber. In particular, a poloidal limiter protecting an ion cyclotron resonance heating (ICRH) antenna is used as proxy for main chamber sourcing. The key study is carried out by stepping up lower hybrid current drive (LHCD) power, as the only auxiliary power source. Limiter and divertor W sources exhibit a qualitatively similar proportionality to the total power crossing the separatrix, P SEP , although the main chamber source remains substantially lower than the divertor source, for the range of P SEP accessible in the experiments. Intepretive modeling of the limiter source is carried out with a particle-in-cell (PIC) sheath model coupled to a surface sputtering model. Oxygen is used as a proxy for all light impurity species allowing for characterization of the critical W erosion regions. To get a good quantitative match to the data, it is necessary to assume that the oxygen arrives at the surface mostly at high ionization stages (4+ and above). A separate simulation with SOLEDGE-EIRENE, constrained to measured upstream scrape-off-layer plasma profiles, gives oxygen fractional abundances that are compatible with the PIC simulation result. This is understood to arise from transport processes that dominate over recombination. Substituting the LHCD by ICRH, in an equivalent experiment, the local W source exhibits a 3× enhancement. This can be matched by the simulation, by assuming local RF electric field rectification, based on ~100 eV peak-to-peak, near-antennna electric field. This work has highlighted the particular importance of understanding the ion charge state balance of light impurities as these are most likely the dominant sputtering species in fusion devices with high-Z walls.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nonlinear second order electromagnetic gyrokinetic theory for a tokamak plasma

The steep plasma pressure gradient that forms at the edge of the high confinement, H-mode regime of tokamak operation provides free energy to drive electromagnetic micro-instabilities that are widely believed to influence the transport processes in this so-called pedestal region. This high pressure gradient also provides a high current density (bootstrap current), known to influence ballooning mode stability and to be important for driving kink modes in the ideal magneto-hydrodynamic plasma model (so-called peeling-ballooning modes). Furthermore, efficient, steady state future tokamak power plants must operate with a large bootstrap current in the core and especially concerning spherical tokamaks, confinement will be influenced by electromagnetic turbulence. To accommodate these important situations, conventional electromagnetic gyrokinetic theory is extended to incorporate neoclassical effects in the equilibrium drives, allowing $B_{\vartheta} ~ B_0$ (B0 is the confining magnetic field, and $B_{\vartheta}$ is its poloidal component). This provides a global gyrokinetic model that self-consistently captures the consequences of large bootstrap current fractions on the equilibrium distribution functions.

kink modes↗

Transuranium Sulfide via the Boron Chalcogen Mixture Method and Reversible Water Uptake in the NaCu T S 3 Family

The behavior of 5f electrons in soft ligand environments makes actinides, and especially transuranium chalcogenides, an intriguing class of materials for fundamental studies. Due to the affinity of actinides for oxygen, however, it is a challenge to synthesize actinide chalcogenides using non-metallic reagents. Using the Boron Chalcogen Mixture (BCM) method, we achieved the synthesis of the transuranium sulfide NaCuNpS 3 starting from the oxide reagent, NpO 2 . Via the same synthetic route, the isostructural composition of NaCuUS 3 was synthesized and the material contrasted with NaCuNpS 3 . Single crystals of the U-analog, NaCuUS 3 , were found to undergo an unexpected reversible hydration process to form NaCuUS 3 ·xH 2 O (x ≈ 1.5). Here, a large combination of techniques was used to fully characterize the structure, hydration process, and electronic structures, specifically a combination of single crystal, powder, high temperature powder X-ray diffraction, extended X-ray ab-sorption fine structure, infrared, and inductively coupled plasma spectroscopies, thermogravimetric analysis, and density functional theory calculations. The outcome of these analyses enabled us to determine the composition of NaCuUS 3 ·xH 2 O and obtain a structural model that demonstrated the retention of the local structure within the [CuUS 3 ] – layers throughout the hydration-dehydration process. Band structure, density of states, and Bader charge calculations for NaCuUS 3 , NaCu-US 3 ·xH 2 O, and NaCuNpS 3 along with X-ray absorption near edge structure, UV-vis-NIR and work function measurements on ACuUS 3 (A = Na, K, and Rb) and NaCuUS 3 ·xH 2 O samples were carried out to demonstrate that electronic properties arise from the [CuTS 3 ] – layers and show surprisingly little dependence on the interlayer distance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗