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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Benchmark Solutions for Radiation Transport in Stochastic Media with Inhomogeneous Material Statistics

Accurately solving implicit Monte Carlo (IMC) thermal photon transport problems with mixed material cells is important in realistic applications. The production IMC package at LLNL treats mixed material cells arising from ALE remap and hydrodynamics using the same approximate model. The new Imp IMC thermal photon transport package currently under development has both a material interface reconstruction (MIR) algorithm and a Levermore-Pomraning (LP) stochastic medium algorithm for treating mixed material cells. Existing stochastic medium algorithms for treating mixed material cells in IMC lack a complete theoretical basis. The IMC LP algorithm implementation has been demonstrated to reproduce published deterministic LP solutions for the particular case of spatially homogeneous material statistics. Realistic simulations will include spatially inhomogeneous material statistics (material mean chord lengths). In a previous investigation, the LP-model for transport in binary stochastic media in rod geometry was generalized to accommodate spatially varying material chord lengths, i.e., the mixing statistics were allowed to be nonhomogeneous. Analytical solutions were obtained and used to produce a verifi cation suite for the Imp IMC Levermore-Pomraning implementation for different spatial variations of the chord lengths. However, the accuracy of the LP model when the mixing statistics are nonhomogeneous has not been assessed and leaves open the question of whether local accuracy is improved or further degraded when chord lengths are not uniform. This shortcoming is rectifi ed here by developing benchmark analytic solutions for transport in binary Markovian stochastic mixtures in rod geometry with nonhomogeneous mixing statistics, using spatially varying chord lengths considered in the previous investigation based on the LP model. Methods for sampling a nonhomogeneous Poisson process (NHPP) are first described and used to construct individual realizations of the binary mixtures in rod geometry. Analytic solutions are then obtained for the forward and backward directed fluxes on a given realization, now viewed as a deterministic medium with alternating layers of the two materials with known interface locations. Finally, material averaged scalar fluxes are obtained using these sampling schemes with spatially linear and quadratic chord lengths and used to assess the accuracy of the previously obtained LP-model results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Explicit dispersion relations for warm fluid waves in a uniform plasma (invited)

Classical dispersion relations for waves in a fluid plasma are expressed as implicit functions of wave frequency and wave- number. The implicit dispersion relation must in general be solved numerically. This work introduces an astute method for obtaining an explicit dispersion relation for waves in a fluid plasma. The explicit expression has an advantage of providing eigenmodes without numerical computations and giving a dispersion relation more detailed than the implicit expression. As in the case of cold waves, the wavenumber for an arbitrary frequency can be directly obtained from the explicit formula. The explicit formula also enables an accurate evaluation of finite-temperature effects on a dispersion relation even near the cyclotron resonance, where a numerical analysis of the implicit relation is impractical. As a result, the analytic formula can be used to investigate temperature effects on electromagnetic waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electrolyte Oxidation Pathways in Lithium-Ion Batteries

The mitigation of decomposition reactions of lithium-ion battery electrolyte solutions is of critical importance in controlling device lifetime and performance. However, due to the complexity of the system, exacerbated by the diverse set of electrolyte compositions, electrode materials, and operating parameters, a clear understanding of the key chemical mechanisms remains elusive. In this work, operando pressure measurements, solution NMR, and electrochemical methods were combined to study electrolyte oxidation and reduction at multiple cell voltages. Two-compartment LiCoO 2 /Li cells were cycled with a lithium-ion conducting glass–ceramic separator so that the species formed at each electrode could be identified separately and further reactions of these species at the opposite electrode prevented. One principal finding is that chemical oxidation (with an onset voltage of ~4.7 V vs Li/Li + for LiCoO 2 ), rather than electrochemical reaction, is the dominant decomposition process at the positive electrode surface in this system. This is ascribed to the well-known release of reactive oxygen at higher states-of-charge, indicating that reactions of the electrolyte at the positive electrode are intrinsically linked to surface reactivity of the active material. Soluble electrolyte decomposition products formed at both electrodes are characterized, and a detailed reaction scheme is constructed to rationalize the formation of the observed species. The insights on electrolyte decomposition through reactions with reactive oxygen species identified through this work have a direct impact on understanding and mitigating degradation in high-voltage/higher-energy-density LiCoO 2 -based cells, and more generally for cells containing nickel-containing cathode materials (e.g., LiNi x Mn y Co z O 2 ; NMCs), as they lose oxygen at lower operating voltages.

25 ENERGY STORAGE↗
DOE OSTI2020

CsI-Antisolvent Adduct Formation in All-Inorganic Metal Halide Perovskites

The excellent optoelectronic properties shown by hybrid organic/inorganic metal halide perovskites are all predicated on precisely controlling the exact nucleation and crystallization dynamics that occur during film formation. In general, high-performance thin films are obtained by a method commonly called solvent engineering (or antisolvent quench) processing. The solvent engineering method removes excess solvent, but importantly leaves behind solvent that forms chemical adducts with the lead-halide precursor salts. These adduct-based precursor phases control nucleation and the growth of the polycrystalline domains. There has not yet been a comprehensive study comparing the various antisolvents used in different perovskite compositions containing cesium. In addition, there have been no reports of solvent engineering for high efficiency in all-inorganic perovskites such as CsPbI 3 . In this work, inorganic perovskite composition CsPbI 3 is specifically targeted and unique adducts formed between CsI and precursor solvents and antisolvents are found that have not been observed for other A-site cation salts. These CsI adducts control nucleation more so than the PbI 2 -dimethyl sulfoxide (DMSO) adduct and demonstrate how the A-site plays a significant role in crystallization. The use of methyl acetate (MeOAc) in this solvent engineering approach dictates crystallization through the formation of a CsI-MeOAc adduct and results in solar cells with a power conversion efficiency of 14.4%.

14 SOLAR ENERGY↗
DOE OSTI2020

Locally adaptive artificial viscosity strategies for Lagrangian hydrodynamics

To accurately model inviscid flow with shock waves using staggered-grid Lagrangian hydrodynamics, artificial viscosity is introduced to convert kinetic energy into internal energy, thereby providing a mechanism to generate the required entropy increase across shocks. In this paper, we propose a new method for constructing an adaptive, artificial viscosity in the context of one-dimensional, staggered-grid Lagrangian hydrodynamics. Our adaptive, artificial viscosity is defined in terms of two parameters that depend on density locally in a neighborhood around a shock, and hence, vary cell-by-cell. Our methodology is based on building a reference set of pre-computed optimal, globally constant artificial viscosity coefficients for a family of isolated shock test problems. For arbitrary flows, the evaluation of the unknown coefficients is automated by first estimating shock intensity locally, and second computing the corresponding adaptive parameter value via interpolation over the data from the pre-computed reference set of optimal, globally constant coefficient values. To illustrate the performance of our new approach, we compare our results against two existing methods. The first method is a limiter-based approach, which relies on estimating velocity gradients of the flow, and the second method is utilized in several commercial codes. Finally, we demonstrate that our new adaptive methodology produces more accurate results for a variety of tests with propagating shock waves, as well as for the aforementioned family of isolated shock problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Structure and dynamics of hydrodynamically interacting finite-size Brownian particles in a spherical cavity: Spheres and cylinders

The structure and dynamics of confined suspensions of particles of arbitrary shape are of interest in multiple disciplines from biology to engineering. Theoretical studies are often limited by the complexity of long-range particle-particle and particle-wall forces, including many-body fluctuating hydrodynamic interactions. Here, we report a computational study on the diffusion of spherical and cylindrical particles confined in a spherical cavity. We rely on an immersed-boundary general geometry Ewald-like method to capture lubrication and long-range hydrodynamics and include appropriate non-slip conditions at the confining walls. A Chebyshev polynomial approximation is used to satisfy the fluctuation-dissipation theorem for the Brownian suspension. We explore how lubrication, long-range hydrodynamics, particle volume fraction, and shape affect the equilibrium structure and the diffusion of the particles. It is found that once the particle volume fraction is greater than 10%, the particles start to form layered aggregates that greatly influence particle dynamics. Hydrodynamic interactions strongly influence the particle diffusion by inducing spatially dependent short-time diffusion coefficients, stronger wall effects on the particle diffusion toward the walls, and a sub-diffusive regime-caused by crowding-in the long-time particle mobility. The level of asymmetry of the cylindrical particles considered here is enough to induce an orientational order in the layered structure, decreasing the diffusion rate and facilitating a transition to the crowded mobility regime at low particle concentrations. Our results offer fundamental insights into the diffusion and distribution of globular and fibrillar proteins inside cells.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomically thin interlayer phase from first principles enables defect-free incommensurate SnO2/CdTe interface

Advancing optoelectronic and emerging technologies increasingly requires control and design of interfaces between dissimilar materials. However, incommensurate interfaces are notoriously defective and rarely benefit from first-principles predictions, because no explicit atomic-structure models exist. Here, we adopt a bulk crystal structure prediction method to the interface geometry and apply it to SnO2/CdTe heterojunctions without and with the addition of CdCl2, a ubiquitous and beneficial, but abstruse processing step in CdTe photovoltaics. Whereas the direct SnO2/CdTe interface is highly defective, we discover a unique two-dimensional CdCl2 interphase, unrelated to the respective bulk structure. It facilitates a seamless transition from the rutile to zincblende lattices and removes defect-states from the interface bandgap. Implementing the predicted interface electronic structure in device simulations, we demonstrate the theoretical feasibility of bufferless oxide-CdTe heterojunction solar cells approaching the Shockley–Queisser limit. Our results highlight the broader potential of designing atomically thin interlayers to enable defect-free incommensurate interfaces.

14 SOLAR ENERGY↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2022

Improving Ni-Based SOFC Anode Resilience and Durability through Secondary Phase Formation

The project used a multi-disciplinary approach to test test if 2° materials, added to traditional cermet components, enhanced SOFC mechanical strength, anode resilience and durability when subjected to electrochemical and environmental redox cycling. Findings from fracture testing, electrochemical studies and operando Raman spectroscopy measurements demonstrated that aluminum titanate (Al 2 TiO 5 or ALT) mechanically mixed with NiO-YSZ cermets confers superior mechanical strength and slower degradation rates under polarization. No deleterious effects from ALT in conversion efficiency were observed. Specific accomplishments included the following: (1) Refined methods used to fabricate ALT enhanced anodes into bi-layer anode supports to achieve high power densities; (2) Compared the effects of adding ALT mechanically to Ni-YSZ powders prior to anode fabrication with adding ALT through infiltration and co-infiltration of YSZ scaffolds; (3) Tested the resilience of these novel materials to electrochemical and environmental redox cycling and thermal stresses commonly encountered in functioning SOFCs; and (4) Characterized the ability of ALT to improve the carbon tolerance of Ni-YSZ anodes operating with dry methane.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Real-space representation of the quasiparticle self-consistent GW self-energy and its application to defect calculations

The quasiparticle self-consistent (QS) GW (G for Green's function, W for screened Coulomb interaction) approach incorporates the corrections of the quasiparticle energies from their Kohn-Sham density functional theory (DFT) eigenvalues by means of an energy-independent and Hermitian self-energy matrix usually given in the basis set of the DFT eigenstates. By expanding these into an atom-centered basis set (specifically here the linearized muffin-tin orbitals) a real space representation of the self-energy corrections becomes possible. In this work, We show that this representation is relatively short-ranged. This offers opportunities to construct the self-energy of a complex system from parts of the system by a cut-and-paste method. Specifically for a point defect, represented in a large supercell, the self-energy can be constructed from those of the host and a smaller defect-containing cell. The self-energy of the periodic host can be constructed simply from a GW calculation for the primitive cell. We show for the case of the As Ga in GaAs that the defect part can already be well represented by a minimal eight-atom cell and allows us to construct the self-energy for a 64-atom cell in good agreement with direct QSGW calculations for the large cell. Using this approach to an even larger 216-atom cell shows the defect band approaches an isolated defect level. The calculations also allow us to identify a second defect band which appears as a resonance near the conduction band minimum. The results on the extracted defect levels agree well with Green's function calculations for an isolated defect and with experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanics of the Ring Tension Test (RTT): A Finite Element-based Investigation

The ring tension test (RTT) is an experimental method for determining mechanical behavior in a material’s circumferential or hoop direction. It is a crucial test for testing anisotropic materials with tube geometry, such as nuclear fuel cladding or irradiated pipes. Several RTT configurations exist, each with their own advantages and disadvantages. However, this test is significantly more complex than traditional tensile testing and can be especially sensitive to small differences and inconsistencies in the test setup and geometry, ultimately affecting the derived mechanical properties. Previous research has focused on method development, and little work has been done on understanding the subtle differences between an ideal test and experiments, specifically when the tests are performed on highly irradiated materials in hot cells. In this work, a finite element-based investigation of the RTT is conducted. Two promising test configurations are investigated, comparing their ability to determine accurate material strengths through plastic deformation. Several non-ideal conditions and uncontrollable effects which are likely to occur during experimental testing such as machining tolerances, variations of specimen geometry from nominal dimensions, rotation of specimens and fixturing, and other test setup discrepancies are studied. The sensitivity of measured strengths to these conditions is presented. A mechanics-based approach to describing and correcting raw data to determine actual strengths is also included for one of the configurations, resulting in a robust correction method with highly accurate material strength measurements. Based on these analyses, the hemicylindrical mandrel configuration is recommended with a gauge region oriented at a 45° angle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗
DOE OSTI2020

An analysis of the spatio-temporal resolution of the immersed boundary method with direct forcing

The immersed boundary method (IBM) with direct forcing is very popular in the simulation of rigid particulate flows. In the IBM, an interaction force is introduced at the interface between fluid and particle in order to approximate the no-slip boundary condition. The interaction force is calculated through dividing the velocity difference (or error) between fluid and particle at the interface by the time step. Here, a dynamic equation for the velocity difference is derived. Additionally, analyses on the dynamic equation provide a few new findings: (i) The interaction force is the solution of a least-squares error problem, with the direct implication that the Lagrangian marker distribution has no effect on the large scale flow structure once the distribution of Lagrangian markers become saturated along the interface (i.e., each marker remains properly correlated with all its neighbors); (ii) The Lagrangian volume-weight is a relaxation factor to control how fast the velocity error decays to the ideal value of zero; (iii) The optimal choice of the Lagrangian volume-weight is the largest value permissible by a stability condition. A comprehensive convergence analysis with regard to the spatial and temporal resolution is presented for the velocity error and also for the shear-stress and surface pressure. In three simple canonical problems, it is analytically and numerically shown that the IBM results converge to the theoretical solutions obtained with precise imposition of no-slip and no-penetration boundary conditions. It is observed that it is not necessary to match the Lagrangian marker volume-weight to that of the local Eulerian cell volume and in fact this matching leads to lower than optimal computational efficiency. However, it is found that extremely high Eulerian grid resolution and small time step have to be used to obtain high precision simulation results. Especially, the time step should be inversely proportional to the particle Reynolds number for low Reynolds number flows. For high frequency oscillation problems, the grid size needs to be reduced by a factor of the square root of the frequency, and the time step to be reduced by a factor of the frequency. The theoretical findings here can be used to alleviate the technical difficulties in simulating non-spherical particles by not requiring the Lagrangian marker distribution to match the Eulerian grids and also in the implementation of IBM on non-uniform Eulerian grids. The present work also provides simple practical guidance on the choice of temporal and spatial resolution so as to control the simulation error a priori.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Generalizing Similarity Laws for Radio-Frequency Discharge Plasmas across Nonlinear Transition Regimes

We generalize similarity theory based on the scaling and solution invariance of the Boltzmann equation, coupled with the Poisson equation, and demonstrate similarity laws for radio-frequency (rf) discharge plasmas across three nonlinear transitional regimes, namely, the alpha-gamma mode transition, the stochastic-Ohmic-heating mode transition, and the bounce-resonance-heating mode transition. Fundamental plasma parameters, e.g., the electron power absorption, under similar discharge conditions are examined via fully kinetic particle-in-cell simulations, and electron-kinetic invariance is exemplified in similar rf discharge plasmas. The results unambiguously confirm the applicability of similarity laws for rf plasmas in extended operating regimes, and strengthen the foundations and framework of similarity physics with universality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A weighted Shifted Boundary Method for free surface flow problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods and was recently introduced for the Poisson, linear advection/diffusion, Stokes, Navier-Stokes, acoustics, and shallow-water equations. By reformulating the original boundary value problem over a surrogate (approximate) computational domain, the SBM avoids integration over cut cells and the associated problematic issues regarding numerical stability and matrix conditioning. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. In this article, we extend the SBM to the simulation of incompressible Navier-Stokes flows with moving free-surfaces, by appropriately weighting its variational form with the elemental volume fraction of active fluid. This approach prevents spurious pressure oscillations in time, which would otherwise be produced if the total active fluid volume were to change abruptly over a time step. In fact, the proposed weighted SBM method induces small mass (i.e., volume) conservation errors, which converge quadratically in the case of piecewise-linear finite element interpolations, as the grid is refined. Finally, we present an extensive set of two- and three-dimensional tests to demonstrate the robustness and accuracy of the method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Plasma physics in strong-field regimes: Theories and simulations

In strong electromagnetic fields, unique plasma phenomena and applications emerge whose description requires recently developed theories and simulations [Y. Shi, Ph.D. thesis, Princeton University (2018)]. In the classical regime, to quantify effects of strong magnetic fields on three-wave interactions, a convenient formula is derived by solving the fluid model to the second order in general geometry. As an application, magnetic resonances are exploited to mediate laser pulse compression, whereby higher intensity pulses can be produced in wider frequency ranges, as confirmed by particle-in-cell simulations. In even stronger fields, relativistic-quantum effects become important, and a plasma model based on scalar quantum electrodynamics (QED) is developed which unveils observable corrections to Faraday rotation and cyclotron absorption in strongly magnetized plasmas. Beyond the perturbative regime, lattice QED is extended as a numerical tool for plasma physics, using which the transition from wakefield acceleration to electron-positron pair production is captured when laser intensity exceeds the Schwinger threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗