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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evidence of gas phase nucleation of nanodiamond in microwave plasma assisted chemical vapor deposition

The mechanism of ballas-like nanodiamond formation still remains elusive, and this work attempts to analyze its formation in the framework of activation energy (Ea) of nanodiamond films grown from a H2/CH4 plasma in a 2.45 GHz chemical vapor deposition system. The Ea was calculated from the Arrhenius equation corresponding to the thickness growth rate using substrate temperature (∼1000−1300 K) in all the calculations. While the calculated values matched with the Ea for nanodiamond formation throughout the literature, these values of ∼10 kcal/mol were lower compared to ∼15–25 kcal/mol for standard single crystal diamond (SCD) formation, concluding thus far that the energetics and processes involved were different. Further, the substrate preparation and sample collection method were modified while keeping the growth parameters constant. Unseeded Si substrate was physically separated from the plasma discharge by a molybdenum disk with a pinhole drilled in it. Small quantity of a sample substance was collected on the substrate. The sample was characterized by electron microscopy and Raman spectroscopy, confirming it to be nanodiamond, thus suggesting that nanodiamond self-nucleated in the plasma and flowed to the substrate that acted as a mere collection plate. It is hypothesized then, if nanodiamond nucleates in gas phase, gas temperature has to be used in the Arrhenius analysis. The Ea values for all the nanodiamond films were re-calculated using the simulated gas temperature (∼1500−2000 K) obtained from a simple H2/CH4 plasma model, giving new values within the range characteristic to SCD formation. Based on these findings, a unified growth mechanism for nanodiamond and SCD is proposed, concluding that the rate-limiting reactions for nanodiamond and SCD formation are the same.

Materials Science↗
DOE OSTI2021

Probing gravity with the DES-CMASS sample and BOSS spectroscopy

ABSTRACT The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey. In this paper, we demonstrate the feasibility of adopting DMASS as the equivalent of CMASS for a joint analysis of DES and BOSS in the framework of modified gravity. We utilize the angular clustering of the DMASS galaxies, cosmic shear of the DES metacalibration sources, and cross-correlation of the two as data vectors. By jointly fitting the combination of the data with the RSD measurements from the CMASS sample and Planck data, we obtain the constraints on modified gravity parameters $\mu _0=-0.37^{+0.47}_{-0.45}$ and $\Sigma _0=0.078^{+0.078}_{-0.082}$. Our constraints of modified gravity with DMASS are tighter than those with the DES Year 1 redMaGiC sample with the same external data sets by 29 per cent for μ0 and 21 per cent for Σ0, and comparable to the published results of the DES Year 1 modified gravity analysis despite this work using fewer external data sets. This improvement is mainly because the galaxy bias parameter is shared and more tightly constrained by both CMASS and DMASS, effectively breaking the degeneracy between the galaxy bias and other cosmological parameters. Such an approach to optimally combine photometric and spectroscopic surveys using a photometric sample equivalent to a spectroscopic sample can be applied to combining future surveys having a limited overlap such as DESI and LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modeling Redshift-space Clustering with Abundance Matching

Abstract We explore the degrees of freedom required to jointly fit projected and redshift-space clustering of galaxies selected in three bins of stellar mass from the Sloan Digital Sky Survey Main Galaxy Sample (SDSS MGS) using a subhalo abundance matching (SHAM) model. We employ emulators for relevant clustering statistics in order to facilitate our analysis, leading to large speed gains with minimal loss of accuracy. We are able to simultaneously fit the projected and redshift-space clustering of the two most massive galaxy samples that we consider with just two free parameters: scatter in stellar mass at fixed SHAM proxy, and the dependence of the SHAM proxy on dark matter halo concentration. We find some evidence for models that include velocity bias, but including orphan galaxies improves our fits to the lower-mass samples significantly. We also model the clustering signals of specific star formation rate (sSFR) selected samples using conditional abundance matching (CAM). We obtain acceptable fits to projected and redshift-space clustering as a function of sSFR and stellar mass using two CAM variants, although the fits are worse than for stellar-mass-selected samples alone. By incorporating nonunity correlations between the CAM proxy and sSFR, we are able to resolve previously identified discrepancies between CAM predictions and SDSS observations of the environmental dependence of quenching for isolated central galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tailoring additive manufacturing to optimize dynamic properties in 316L stainless steel

With the advent of additive manufacturing, manipulation of typical microstructural elements such as grain size, texture, and defect densities is now possible at a faster time scale. While the processing–structure–property relationship in additive manufactured metals has been well studied over the past decade, little work has been done in understanding how this process affects the dynamic behavior of materials. We postulate that additive manufacturing can be used to alter the material microstructure and used to enhance its dynamic strength. In this work, 316L stainless steel (SS) was manufactured via selected laser melting and its microstructure was altered through changing build parameters like laser power, speed, and hatch spacing systematically. These samples were then subjected to spall recovery experiments to measure the spall strength and quantify the amount of damage as a function of build parameters. By mapping the spall strength as a function of build parameters, this work demonstrated that indeed additive manufacturing can be used to tailor the spall strength of 316L SS. This work also determined the optimum build parameters (laser power=195W; scanning speed=1083mm/s; hatch spacing=0.09mm; layer thickness=0.02mm) to obtain the highest spall strength and the least amount of total damage in 316L SS. Microstructural characterization of the pre- and post-mortem samples revealed that increased grain average misorientation and textural index were the main driving force behind this higher spall strength. This work aims to enhance microstructural engineering techniques to design materials with greater resistance to dynamic shock loading.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Differentiable stochastic halo occupation distribution

ABSTRACT In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep reinforcement learning can be used to perform efficient parameter inference over stochastic, simulation-based, forward models. As a particular example, we focus on the problem of estimating parameters of halo occupation distribution (HOD) models that are used to connect galaxies with their dark matter haloes. Using a combination of continuous relaxation and gradient re-parametrization techniques, we can obtain well-defined gradients with respect to HOD parameters through discrete galaxy catalogue realizations. Having access to these gradients allows us to leverage efficient sampling schemes, such as Hamiltonian Monte Carlo, and greatly speed up parameter inference. We demonstrate our technique on a mock galaxy catalogue generated from the Bolshoi simulation using a standard HOD model and find near-identical posteriors as standard Markov chain Monte Carlo techniques with an increase of ∼8× in convergence efficiency. Our differentiable HOD model also has broad applications in full forward model approaches to cosmic structure and cosmological analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining RV variation using highly reddened Type Ia supernovae from the Pantheon+ sample

ABSTRACT Type Ia supernovae (SNe Ia) are powerful tools for measuring the expansion history of the Universe, but the impact of dust around SNe Ia remains unknown and is a critical systematic uncertainty. One way to improve our empirical description of dust is to analyse highly reddened SNe Ia [E(B − V) > 0.4, roughly equivalent to the fitted SALT2 light-curve parameter c > 0.3]. With the recently released Pantheon+ sample, there are 57 SNe Ia that were removed because of their high colour alone (with colours up to c = 1.61), which can provide enormous leverage on understanding line-of-sight RV. Previous studies have claimed that RV decreases with redder colour, though it is unclear if this is due to limited statistics, selection effects, or an alternative explanation. To test this claim, we fit two separate colour–luminosity relationships, one for the main cosmological sample (c < 0.3) and one for highly reddened (c > 0.3) SNe Ia. We find the change in the colour–luminosity coefficient to be consistent with zero. Additionally, we compare the data to simulations with different colour models, and find that the data prefers a model with a flat dependence of RV on colour over a declining dependence. Finally, our results strongly support that line-of-sight RV to SNe Ia is not a single value, but forms a distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Star-forming S0 galaxies in the SDSS-IV MaNGA survey

ABSTRACT To investigate star-forming activities in early-type galaxies, we select a sample of 52 star-forming S0 galaxies (SFS0s) from the SDSS-IV MaNGA survey. We find that SFS0s have smaller stellar masses compared to normal S0s in MaNGA. After matching the stellar mass to select the control sample, we find that the mean Sérsic index of SFS0 bulges (1.76 ± 0.21) is significantly smaller than that of the control sample (2.57 ± 0.20), suggesting the existence of pseudo-bulges in SFS0s. After introducing the environmental information, SFS0s show smaller spin parameters in the field than in groups, while the control sample has no obvious difference in different environments, which may suggest different dynamical processes in SFS0s. Furthermore, with derived N/O and O/H abundance ratios, SFS0s in the field show nitrogen enrichment, providing evidence for the accretion of metal-poor gas in the field environment. To study the star-formation relation, we show that the slope of the spatially resolved star-formation main sequence is nearly 1.0 with MaNGA integral field unit data, confirming the self-regulation of star-formation activity on kpc scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Environments of dwarf galaxies with optical AGN characteristics

ABSTRACT This study aims to explore the relation between dwarf galaxies (M* ≤ 5 × 109 M⊙) with active galactic nuclei (AGNs) and their environment by comparing neighbourhood parameters of AGN and non-AGN samples. Using the NASA-Sloan Atlas, both the local environment and the immediate environment of dwarf galaxies with z ≤ 0.055 are analysed. Of the 145 155 galaxies in the catalogue, 62 258 of them are classified as dwarf galaxies, and by employing two AGN selection methods based on emission-line fluxes (BPT and WHAN), 4476 are found to have AGN characteristics in their optical spectra. Regardless of selection method, this study finds no discernible differences in environment between AGN and non-AGN host dwarf galaxies and these results indicate that environment is not an important factor in triggering AGN activity in dwarf galaxies. This is in line with existing literature on environments of regular galaxies with AGNs and suggests universality in terms of reaction to environment across the mass regime. The biases of AGN selection in low-mass galaxies, and the biases of different measures of environment are also considered. It is found that there are several mass trends in emission-line ratios and that the SDSS fibre covers galaxies non-uniformly with redshift. These biases should be accounted for in future work by possibly including other wavelength regimes or mass weighting of emission-line ratios. Lastly, a discussion of the environment estimation methods is included since they may not gauge the desired properties due to factors such as time delay or using loosely constrained proxy parameters.

Kristensen, Mikkel T.↗
DOE OSTI2022

Size Effect of Local Current-Voltage Characteristics of MX 2 Nanoflakes: Local Density of States Reconstruction from Scanning Tunneling Microscopy Experiments

Local current-voltage characteristics for low-dimensional transition-metal dichalcogenides (LDTMD), as well as the reconstruction of their local density of states (LDOS) from scanning tunneling microscopy (STM) experiments, are of fundamental interest and can be useful for advanced applications. Most of the existing models either have limited applicability for complex-shaped LDTMDs (e.g., those based on the Simmons approach) or require solving of an ill-defined integral equation to deconvolute the unknown LDOS (e.g., those based on the Tersoff approach). Using a serial expansion of the Tersoff formulas, we propose a flexible method to reconstruct the LDOS from local current-voltage characteristics measured in STM experiments. We establish a set of key physical parameters, which characterize the tunneling current of a STM-probe–sample contact and the sample LDOS expanded in Gaussian functions. Using a direct variational method coupled with probabilistic analysis, we determine these parameters from the STM experiments for MoS2 nanoflakes with different numbers of layers. The main result is the reconstruction of the LDOS in a relatively wide energy range around the Fermi level, which allows us to gain insight into the local band structure of LDTMDs. The reconstructed LDOS reveal pronounced size effects for the single-layer, two-layer, and three-layer MoS 2 nanoflakes, which we relate to the low dimensionality and strong bending or corrugation of the nanoflakes. We hope that the proposed elaboration of the Tersoff approach, allowing LDOS reconstruction, will be of critical interest for the quantitative description of STM experiments and also of use to better understand the microscopic physical aspects of the surface, strain, and bending contributions to the LDTMDs’ electronic properties.

42 ENGINEERING↗
DOE OSTI2021

Synthesis of Zn2NbN3 ternary nitride semiconductor with wurtzite-derived crystal structure

Binary III-N nitride semiconductors with wurtzite crystal structure such as GaN and AlN have been long used in many practical applications ranging from optoelectronics to telecommunication. The structurally related ZnGeN2 or ZnSnN2 derived from the parent binary compounds by cation mutation (elemental substitution) have recently attracted attention, but such ternary nitride materials are mostly limited to II-IV-N2 compositions. This paper demonstrates synthesis and characterization of zinc niobium nitride (Zn2NbN3) – a previously unreported II2-V-N3 ternary nitride semiconductor. The Zn2NbN3 thin films are synthesized using a one-step adsorption-controlled growth, and a two-step deposition/annealing method that suppresses the loss of Zn and N. Measurements indicate that this sputtered Zn2NbN3 crystalizes in cation-disordered wurtzite-derived structure, in contrast to chemically related rocksalt-derived Mg2NbN3 compound, also synthesized here for comparison using the two-step method. The estimated wurtzite lattice parameter ratio of Zn2NbN3 is 1.55, and the optical absorption onset is at 2.1 eV. Both of these values are lower compared to published Zn2NbN3 computational values of c/a = 1.62 and Eg = 3.5 - 3.6 eV. Additional theoretical calculations indicate that this difference is due to cation disorder in experimental samples, suggesting a way to tune the structural parameters and the resulting properties of heterovalent ternary nitride materials. Overall, this work expands the wurtzite family of nitride semiconductors to include Zn2NbN3, and suggests that related II2-V-N3 and other ternary nitrides should be possible to synthesize.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2021

The first Hubble diagram and cosmological constraints using superluminous supernovae

In this work, we present the first Hubble diagram of superluminous supernovae (SLSNe) out to a redshift of two, together with constraints on the matter density, Ω M , and the dark energy equation-of-state parameter, w(≡p/ρ). We build a sample of 20 cosmologically useful SLSNe I based on light curve and spectroscopy quality cuts. We confirm the robustness of the peak–decline SLSN I standardization relation with a larger data set and improved fitting techniques than previous works. We then solve the SLSN model based on the above standardization via minimization of the χ2 computed from a covariance matrix that includes statistical and systematic uncertainties. For a spatially flat Λ cold dark matter (ΛCDM) cosmological model, we find $\Omega _{\rm M}=0.38^{+0.24}_{-0.19}$, with an rms of 0.27 mag for the residuals of the distance moduli. For a w 0 w a CDM cosmological model, the addition of SLSNe I to a ‘baseline’ measurement consisting of Planck temperature together with Type Ia supernovae, results in a small improvement in the constraints of w 0 and wa of 4 per cent. We present simulations of future surveys with 868 and 492 SLSNe I (depending on the configuration used) and show that such a sample can deliver cosmological constraints in a flat ΛCDM model with the same precision (considering only statistical uncertainties) as current surveys that use Type Ia supernovae, while providing a factor of 2–3 improvement in the precision of the constraints on the time variation of dark energy, w 0 and w a . This paper represents the proof of concept for superluminous supernova cosmology, and demonstrates they can provide an independent test of cosmology in the high-redshift (z > 1) universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Phase Doppler Interferometry for Efficient Cloud Drop Size Distribution, Number Density, and LWC Measurements

Threats to aviation safety as a result of super-cooled large drops (SLD) has been addressed by the FAA rules change (14 CFR Part 25) with the additional icing certification requirement. SLD clouds often consist of bi-modal drop size spectra leading to significant problems in simulating and characterizing these conditions in situ and in icing wind tunnels. Legacy instrumentation for measuring drop size distributions and liquid water content are challenged under these conditions. The large size range measurement problem is addressed with the development of the Phase Doppler Interferometer, Flight Probe Dual-Range (PDI FPDR). The method is described in this report along with the measurement capabilities including the dynamic measurement range and overall working size range. The PDI instrument bases drop size measurements on the light wavelength as the measurement length scale. The light wavelength is a much more robust scale, especially as compared to the light scattering intensity. Additionally, methods for accurately characterizing the sample volume in situ based on measured drop velocity and transit time are reviewed, given the importance of this parameter for merging results and measuring LWC. Droplet coincidence in the sample volume can be problematic so this condition is treated with an innovative signal parsing approach. Measurement examples acquired in the NASA IRT are provided. Measurements of LWC showed good agreement with the Artium Particle Imaging (PI) instrument but diverged from the tunnel calibration results for larger MVD values.

42 ENGINEERING↗
DOE OSTI2023

FY23 Update: Surface Sampling Activities for the Canister Deposition Field Demonstration

This report describes the results of a field demonstration of the proposed surface sampling techniques and plan for the multi-year Canister Deposition Field Demonstration (CDFD). The CDFD will evaluate salt deposition rates on three commercial 32PTH2 NUHOMS welded stainless steel storage canisters in Advanced Horizontal Storage Modules. Exposure testing is planned for up to 10 years and will incorporate periodic surface sampling campaigns. The goal of the planned dust sampling and analysis is to determine important environmental parameters that impact the potential occurrence of stress corrosion cracking on spent nuclear fuel (SNF) dry storage canisters. Specifically, measured dust deposition rates and deposited particle sizes will improve parameterization of dust deposition models employed to predict the potential occurrence and timing of stress corrosion cracks on the stainless steel SNF canisters. Previously, a preliminary sampling plan was developed, identifying possible sampling locations on the canister surfaces and sampling intervals; possible sampling methods were also described. Building from previous work, this report documents hand sampling from a spent nuclear fuel canister on a transfer skid mockup designed by Sandia National Laboratories. The sampling took place from a boom lift and salts were collected from mounted sample plates. The results of these efforts are presented in this report and compared to previous laboratory-controlled tests. The information obtained from the CDFD will be critical for ongoing efforts to develop a detailed understanding of the potential for stress corrosion cracking of SNF dry storage canisters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

TensorBNN: Bayesian inference for neural networks using TensorFlow

We report that TensorBNN is a new package based on TensorFlow that implements Bayesian inference for modern neural network models. The posterior density of neural network model parameters is represented as a point cloud sampled using Hamiltonian Monte Carlo. The TensorBNN package leverages TensorFlow's architecture and its ability to use modern graphics processing units in both the training and prediction stages.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Measurements of the thermal conductivity of reference liquids using a modified transient hot-wire needle probe

Many power generation processes feature some type of working fluid that plays a critical role in the transfer of heat throughout the system. To optimize thermal efficiencies, an accurate characterization of the temperature-dependent thermal conductivity of the fluid is needed. Herein, this study develops a time-domain Modified Transient Hot-wire Needle Probe to overcome phenomena that have impaired traditional measurement techniques when the fluid is both corrosive and at an elevated temperature. First, the physical design of the instrument is presented to demonstrate features that limit interference from corrosion, electrical conduction, and convective and radiative heat transfer. Next, a governing equation for 1D (radial) heat conduction is fully developed using the thermal quadrupoles technique. A finite-element study is performed for validation. A sensitivity analysis is done to assess the time-dependent influence of critical parameters in the governing equation for several samples. Finally, thermal conductivity measurements are presented for seven different liquid substances by fitting the thermal model to experimental data across a range of temperatures. Reference correlations are included for comparison. The sample thermal conductivity and ambient temperature of the experimental conditions range from 0.125–16.5$\frac{W}{m·K}$ and 10–400°C, respectively. The total uncertainty, comprised of both the experimental design and fitting process, of all measurements is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗