Search NASA⌕ Search

SEARCH · Search NASA

Results for “LET”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗
DOE OSTI2021

Exosomes secreted from mesenchymal stem cells mediate the regeneration of endothelial cells treated with rapamycin by delivering pro-angiogenic microRNAs

Highlights: • MSC-derived exosomes play an important role in promoting endothelial regeneration treated with rapamycin in vitro. • A distinct class of exosomal miRNAs is identified to be tightly related to endothelial regeneration. • The therapeutic effects of MSC-exosomes may be ascribed to the delivery of pro-angiogenic miRNAs to endothelial cells. • MSC-exosomes may serve as a cell-free therapy for clinical treatment of delayed endothelial healing after DES implantation. Delayed endothelial healing after drug eluting stent (DES) implantation is a critical clinical problem in treatment of coronary artery diseases. Exosomes exhibit proangiogenic potential in a variety of ischemic diseases. However, the association of exosomes with endothelial regeneration after DES implantation has been rarely reported. In this study, we aimed to investigate the therapeutic effects of mesenchymal stem cell (MSC)-derived exosomes on endothelial cells treated with rapamycin and explore the potential mechanisms of MSC-derived exosomes in promoting endothelial regeneration. Exosomes were isolated from MSCs by ultracentrifugation and identified by transmission electron microscopy, nanoparticle tracking analysis, and Western blot assay. The in vitro effects of MSC-derived exosomes on the proliferation and migration of endothelial cells treated with rapamycin were evaluated by integrated experiment, cell counting kit-8, scratch, tube formation, and transwell assays. And the apoptosis of rapamycin-induced endothelial cells loaded with MSC-derived exosomes was detected using TUNEL and Annexin-V FITC and PI double-staining assays. The microRNA (miRNA) cargo of MSC-derived exosomes was identified by high-throughput RNA sequencing. Pro-angiogenic miRNAs and key pathways were further characterized. Our results indicated that MSC-derived exosomes could be ingested into umbilical vein endothelial cells (HUVECs) and significantly enhanced cell proliferation rate, migratory and tube-forming capabilities in vitro. MSC-derived exosomes also inhibited the apoptosis of HUVECs induced by rapamycin. A distinct class of exosomal miRNAs was further identified, including six miRNAs tightly related to neovasculogenesis. Silencing the expression of exosomal miRNA-21–5p and let-7c-5p attenuated the pro-proliferative and pro-migratory capacity of MSC-derived exosomes. Moreover, functional enrichment analysis indicated that metabolic pathways might contribute to reendothelialization. This study highlights a proregenerative effect of MSC-derived exosomes in vitro, which may be partly explained by the delivery of pro-angiogenic miRNAs to endothelial cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Description of global EGAM in the maximum of local frequency during current ramp-up discharges in DIII-D

Energetic-particle-induced geodesic acoustic modes, EGAMs (Fu, Phys. Rev. Let., vol. 101, 2008, pp. 185002), driven by neutral beam injection (NBI), have been observed in many DIII-D tokamak experiments (Nazikian et al., Phys. Rev. Lett., vol. 101, 2008, pp. 185001). This mechanism has been theoretically investigated in (Qiu et al., Plasma Phys. Control. Fusion, vol. 52, 2010, pp. 095003), using a sharp energetic particle distribution function, and in (Qu et al., Plasma Phys. Control. Fusion, vol. 59, 2017, pp. 055018), where the dispersion relation and eigenmode behaviour were obtained for the situation of early beam scenario, that is, for times smaller than the beam slowing down time. In this work, we extend these studies determining the eigenmode for beyond the slowing down time, in a scenario with reverse safety factor q profile, where a small concentration of energetic ions can produce an off-axis maximum in the GAM dispersion relation. Here, the characteristics of EGAM are analytically studied with the drift kinetic equation together with the MHD code NOVA. The toroidal energetic ion transit frequency, coupled with the GAM frequency, produces the maximum in the dispersion relation where the eigenmode can be found. The quantitative correspondence of experimental results with the predictions of the proposed model is analysed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Ligand–Metal Complementarity in Rare-Earth and Actinide Chemistry

In this article, the rare-earths are comprised of scandium, yttrium, and the lanthanides (atomic numbers 21, 39, and 57–71). (1) While these elements are essential to modern life, they were historically characterized as simple, perhaps dull, compared to the rich multielectron chemistry of d-block metals in catalysts and enzymes. These descriptions were quite fair and largely true at the time that these elements were being discovered and the first compounds containing them were being synthesized, although much progress has been made to overturn this view of the rare earths. Similarly, discussions about actinide chemistry are sometimes limited to research pertinent to the nuclear industry, which, while comprising technologies vital to modern society, does not celebrate the fascinating chemical space that much of the actinide series occupies. These historic characterizations of most of the rare-earth and actinide elements persist in some textbooks, and we acknowledge that it is a helpful place to start; however, altogether these series comprise 32 elements-27% of the 118 known by 2024-and we suggest it would be an unfortunate twist of physics if such a large proportion of the Periodic Table were genuinely dull. Indeed, as this Inorganic Chemistry Forum Issue “Ligand-Metal Complementarity in Rare-Earth and Actinide Chemistry” highlights, the chemistry-let alone the physics, that is, spectroscopy and magnetism-of these elements is rich and depends on ligands!

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Material, Phase, and Interface Stability of Photovoltaic Perovskite: A Perspective

The past decade has witnessed the unprecedented boost of power conversion efficiency (PCE) of photovoltaics based on halide perovskite materials since its early discovery. Despite its remarkably good performance, long-term stability is yet one of the last barriers before commercializing halide perovskite photovoltaics is possible. In this perspective, we discuss the challenges and concurrently the strategies regarding the stability of the perovskite materials, photoactive crystal phases, and the performance as well as stability limiting interfaces. Future perspectives of stable halide perovskite and perovskite solar cells are also proposed to shine light on letting perovskite technology satisfy long-term operation warranty.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanocluster Active Sites Formed on Heterogeneous Thermal Catalysts and Electrocatalysts by Operando Reactive Environments

Here, in this Viewpoint, we summarize our recent studies in this endeavor, ending with a forward-looking perspective into the remaining challenges and open questions for consideration by the catalysis community. Through a computationally efficient framework of systematically investigating metal atom ejection from and migration onto metal surfaces, leading to the formation of metal atom clusters, we show that the surface of a metal catalyst is dynamic and much less rigid than previously thought. We suggest that the operando formed metal atom clusters are novel active sites, which can dominate the activity of steps or kinks (let aside terraces) from where their constituent atoms were ejected. Through more readily responding to reaction conditions by forming catalytically active clusters, solid metal catalysts approach not only homogeneous catalyst motifs, thus establishing a bridge between homogeneous and heterogeneous catalysis, but also liquid metals which have been suggested to be better than traditional heterogeneous catalysts.

adsorption↗
DOE OSTI2023

Subtle Molecular Changes Largely Modulate Chiral Helical Assemblies of Achiral Conjugated Polymers by Tuning Solution-State Aggregation

Understanding the solution-state aggregate structure and the consequent hierarchical assembly of conjugated polymers is crucial for controlling multiscale morphologies during solid thin-film deposition and the resultant electronic properties. However, it remains challenging to comprehend detailed solution aggregate structures of conjugated polymers, let alone their chiral assembly due to the complex aggregation behavior. Herein, we present solution-state aggregate structures and their impact on hierarchical chiral helical assembly using an achiral diketopyrrolopyrrole-quaterthiophene (DPP-T4) copolymer and its two close structural analogues wherein the bithiophene is functionalized with methyl groups (DPP-T2M2) or fluorine atoms (DPP-T2F2). Combining in-depth small-angle X-ray scattering analysis with various microscopic solution imaging techniques, we find distinct aggregate in each DPP solution: (i) semicrystalline 1D fiber aggregates of DPP-T2F2 with a strongly bound internal structure, (ii) semicrystalline 1D fiber aggregates of DPP-T2M2 with a weakly bound internal structure, and (iii) highly crystalline 2D sheet aggregates of DPP-T4. These nanoscopic aggregates develop into lyotropic chiral helical liquid crystal (LC) mesophases at high solution concentrations. Intriguingly, the dimensionality of solution aggregates largely modulates hierarchical chiral helical pitches across nanoscopic to micrometer scales, with the more rigid 2D sheet aggregate of DPP-T4 creating much larger pitch length than the more flexible 1D fiber aggregates. Combining relatively small helical pitch with long-range order, the striped twist-bent mesophase of DPP-T2F2 composed of highly ordered, more rigid 1D fiber aggregate exhibits an anisotropic dissymmetry factor (g-factor) as high as 0.09. This study can be a prominent addition to our knowledge on a solution-state hierarchical assembly of conjugated polymers and, in particular, chiral helical assembly of achiral organic semiconductors that can catalyze an emerging field of chiral (opto)electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The Role of Nonequilibrium Solvent Effects in Enhancing Direct CO 2 Capture at the Air–Aqueous Amino Acid Interface

Direct air capture (DAC) technologies are limited by the poor understanding of the dynamic role of interfaces in modulating the chemisorption of CO 2 from air into solutions. While the reactivity of aqueous amine-based solvents in the bulk environment is strongly inhibited by nonequilibrium solvent effects, promoting DAC at interfaces posits a possibility to reduce the coupling with the solvent and significantly accelerate DAC. Building on an experimentally proven concept to bring an anionic glycine absorbent to the interface through ion-pairing interactions with a positively charged surfactant, we establish the fundamental time scales for key elementary steps involved in DAC with rate theory and enhanced-sampling ab initio molecular dynamics simulations. Here, we elucidate the mechanism by which water influences the free energy barriers and dynamical crossing-recrossing of those barriers, affecting the reaction rates. We find that water reorganizes to partially dehydrate [-NH 2 ], facilitating S N 2-based CO 2 conversion to a zwitterion, which then releases a proton via overhydration of [-NH 2 ]. The low-density interfacial water favors dehydration over overhydration, leading to a comparatively higher barrier (slower kinetics) for proton release. The barrier-recrossing events neutralize this effect, letting both steps occur at the same time scale (sub-microseconds) and making the overall DAC process faster at the interface than in the bulk water. Such an understanding of environment-sensitive solvent effects on the reaction kinetics will help design tailored interfaces for enhanced CO 2 capture kinetics via control of solvation and ion paring.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Differentiable Hydrology Approach for Modeling With Time-Varying Parameters

In the analysis of observational data with mathematical models, it is often desirable to let one or more model parameters vary with time to account for changing environmental conditions or to offer more flexibility. A standard approach for dynamic models is to allow for the number of parameters to grow as a function of time, leading to a high-dimensional inference problem for long data records. We propose using Hamiltonian Monte Carlo, a gradient-based Markov chain Monte Carlo (MCMC) method, to perform Bayesian inference for time-varying parameters (TVP) in hydrology models. As derivatives of model error functions with regard to parameters are not available in closed form, we implemented the GR4J rainfall-runoff models in Theano/PyMC3, and Jax/NumPyro, allowing for the application of automatic differentiation techniques. A simulation experiment assessing the viability of these methods for recovering underlying temporal variation in parameters indicates that a discrete Gaussian random walk-based prior appears to be best suited across a range of scenarios while the continuous-time Gaussian process compares relatively poorly. In an analysis of 20 years of daily real-world streamflow records from the Model Parameter Estimation Experiment (MOPEX) hydrology data set with increasing data sparsity and at multiple temporal resolutions, we find that TVP inference with gradient-based MCMC is a flexible and reliable approach for analyzing hydrology models with dynamic parameter sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Functional protein mining with conformal guarantees

Molecular structure prediction and homology detection offer promising paths to discovering protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a statistically principled approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model. Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of uncharacterized proteins with likely desirable functional properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels

Abstract A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. Its success is largely attributed to the GP’s analytical tractability, robustness, and natural inclusion of uncertainty quantification. Unfortunately, the use of exact GPs is prohibitively expensive for large datasets due to their unfavorable numerical complexity of $$O(N^3)$$ O ( N 3 ) in computation and $$O(N^2)$$ O ( N 2 ) in storage. All existing methods addressing this issue utilize some form of approximation—usually considering subsets of the full dataset or finding representative pseudo-points that render the covariance matrix well-structured and sparse. These approximate methods can lead to inaccuracies in function approximations and often limit the user’s flexibility in designing expressive kernels. Instead of inducing sparsity via data-point geometry and structure, we propose to take advantage of naturally-occurring sparsity by allowing the kernel to discover—instead of induce—sparse structure. The premise of this paper is that the data sets and physical processes modeled by GPs often exhibit natural or implicit sparsities, but commonly-used kernels do not allow us to exploit such sparsity. The core concept of exact, and at the same time sparse GPs relies on kernel definitions that provide enough flexibility to learn and encode not only non-zero but also zero covariances. This principle of ultra-flexible, compactly-supported, and non-stationary kernels, combined with HPC and constrained optimization, lets us scale exact GPs well beyond 5 million data points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗
DOE OSTI2020

Evolution of the ROOT Tree I/O

The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

ROOT’s RNTuple I/O Subsystem: The Path to Production

The RNTuple I/O subsystem is ROOT’s future event data file format and access API. It is driven by the expected data volume increase at upcoming HEP experiments, e.g. at the HL-LHC, and recent opportunities in the storage hardware and software landscape such as NVMe drives and distributed object stores. RNTuple is a redesign of the TTree binary format and API and has shown to deliver substantially faster data throughput and better data compression both compared to TTree and to industry standard formats. In order to let HENP computing workflows benefit from RNTuple’s superior performance, however, the I/O stack needs to connect efficiently to the rest of the ecosystem, from grid storage to (distributed) analysis frameworks to (multithreaded) experiment frameworks for reconstruction and ntuple derivation. With the RNTuple binary format soon arriving at its first production release, we present RNTuple’s feature set, integration efforts, and its performance impact on the time-to-solution. We show the latest performance figures of RDataFrame analysis code of realistic complexity, comparing RNTuple and TTree as data sources. We discuss RNTuple’s approach to functionality critical to the HENP I/O (such as multithreaded writes, fast data merging, schema evolution) and we provide an outlook on the road to its use in production.

Blomer, Jakob↗
DOE OSTI2021

Computational discovery of stable and metastable ternary oxynitrides

Materials design from first principles enables exploration of uncharted chemical spaces. Extensive computational searches have been performed for mixed-cation ternary compounds, but mixed-anion systems are gaining increased interest as well. Central to computational discovery is the crystal structure prediction, where the trade-off between reliance on prototype structures and size limitations of unconstrained sampling has to be navigated. We approach this challenge by letting two complementary structure sampling approaches compete. We use the kinetically limited minimization approach for high-throughput unconstrained crystal structure prediction in smaller cells up to 21 atoms. On the other hand, ternary—and, more generally, multinary—systems often assume structures formed by atomic ordering on a lattice derived from a binary parent structure. Thus, we additionally sample atomic configurations on prototype lattices with cells up to 56 atoms. Using this approach, we searched 65 different charge-balanced oxide–nitride stoichiometries, including six known systems as the control sample. The convex hull analysis is performed both for the thermodynamic limit and for the case of synthesis with activated nitrogen sources. We identified 34 phases that are either on the convex hull or within a viable energy window for potentially metastable phases. We further performed structure sampling for “missing” binary nitrides whose energies are needed for the convex hull analysis. Among these, we discovered metastable Ce3N4 as a nitride analog of the tetravalent cerium oxide, which becomes stable under slightly activated nitrogen condition µN > +0.07 eV. Given the outsize role of CeO2 in research and application, Ce3N4 is a potentially important discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Leaving in the lead: Priorities for perovskite photovoltaics

The need for moving electricity generation to a sustainable model requires the development of low cost ubiquitous photovoltaics (PVs) to harvest the planet’s primary energy source, the Sun. Building upon the successes of Si-based and CdTe-based PV technologies, PVs with lower-embodied energy and requiring lower carbon dioxide equivalent to produce will be required to meet long-term sustainability goals. In particular, thin-film technologies, such as high-efficiency metal halide perovskite (MHP) PV modules, provide avenues to reduced embodied energy, lower energy payback times, and enabling energy-dense tandems [H. M. Wikoff et al., Joule 6(7), 1710–1725 (2022) and V. Fthenakis, Renewable Sustainable Energy Rev. 13(9), 2746–2750 (2009)]. The ability to improve efficiency and lower energy payback time of next generation thin-film PV modules is a critical foundation for green H2 and electrification more broadly. In this regard, Pb-based MHP-PVs have separated themselves as a result of the high-efficiencies that can be realized across a range of electronic gaps. Questions regarding Pb-based MHP-PVs that are often asked, as the challenges of efficiency and reliability are met, revolve around the “problem” of the Pb content. Specifically, “does Pb toxicity preclude MHP-PV modules from being deployed at the TW scale?” To provide this sense of scale, in 2021, the United States burned 10.5 quads of coal, with 90% of that used for electricity generation. Given the energy content of coal of 29 MJ/kg and a residual lead content in that coal of 30 mg/kg, electricity generation from coal resulted in more lead emitted into the atmosphere than what would be required to produce over 2 TW of MHP-PV name plate capacity (assuming a 20% module efficiency and an ∼700 nm active layer). This amounts to more PV power than has been deployed across all PV technologies and geographies to date. This only includes US coal consumption; the rest of the world would be much larger. This example illustrates the scale of the material usage relative to the energy production. Imagine a power-generation technology that offsets these Pb emissions from coal and essentially sequesters this Pb content between two sheets of impermeable glass. Why should we let Pb’s history of misuse prevent it from being included in next generation PV modules that can enable a sustainable energy future?

14 SOLAR ENERGY↗
DOE OSTI2023

Performance evaluation of cosmic ray muon trajectory estimation algorithms

Muons, being elementary particles with minimal interaction with nuclear materials and abundant at sea level, have sparked interest in utilizing them for imaging various applications, such as mining [Borselli et al., Sci. Rep. 12, 22329 (2022)], volcano imaging [Nagamine et al., Nucl. Instrum. Meth. A, 356, 585(1995)], and underground tunnel detection [Guardincerri et al., Pure Appl. Geophys. 174, 2133 (2017)]. Recently, their use in nuclear nonproliferation and safeguard verification has gained attention, particularly in cargo screening for nuclear waste smuggling [Baesso et al., J. Instrum. 9, C10041 (2014)], source localization [L. J. Schultz et al., Nucl. Instrum. Meth. A 519, 687 (2004)], and locating nuclear fuel debris in reactors [Borozdin et al., Phys. Rev. Let. 109, 152501 (2012)]. However, the resolution of muon image reconstruction techniques is limited due to multiple Coulomb scattering (MCS) within the target object. To achieve robust muon tomography, it is crucial to develop efficient and flexible physics-based algorithms that can model the MCS process accurately and estimate the most probable trajectory of muons as they pass through the target object. To address this limitation, in this study, a novel algorithmic approach utilizing the Bayesian probability theory and Gaussian approximation of MCS is chosen. Different energy levels, materials, and target sizes were considered in the evaluations. The results demonstrate that the Generalized Muon Trajectory Estimation (GMTE) algorithm offers significant improvements over currently used algorithms. Across all test scenarios, the GMTE algorithm demonstrated ~50% and 38% increase in precision compared to Straight Line Path (SLP) and Point of Closest Approach (PoCA) algorithms, respectively. Furthermore, it exhibited 10%–35% and 10%–15% increases in muon flux utilization for high and medium Z materials, respectively, compared to the PoCA algorithm. In conclusion, the extensive simulations confirm the enhanced performance and efficiency of the GMTE algorithm, offering improved resolution and reduced measurement time for cosmic ray muon imaging compared to the current SLP and PoCA algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Theory and simulations of cross-beam energy transfer between speckled laser beams

In this paper, we introduce a realistic modeling of laser beams smoothed by random phase plates to investigate cross-beam energy transfer (CBET). We compute the total field of the smoothed laser beams, which allows us to perform accurate simulations and to build a model accounting for the realistic structure of the speckles. This lets us confirm the results already discussed in a previous work given by Oudin et al. [Phys. Plasmas 29, 112112 (2022)]. When CBET is induced by a plasma flow, plane wave models can predict the exchange between smoothed laser beams. By contrast, when the exchange is caused by a wavelength shift between the laser fields of each beam, plane wave models overestimate the energy transfer, even for strongly Landau-damped ion acoustic waves. We also show that the laser angular spread, which results from its focusing, affects the resonance between the ponderomotive force induced by the laser fields and the ion acoustic wave. It increases the resonance width, which weakly depends on the Landau damping rate when there is a wavelength shift and no flow. In addition, the power transfer obtained with or without a phase plate is essentially the same in the perturbative regime and for small crossing angles.

Laser plasma interactions↗