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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Estimating Electron Temperature and Density Using Van Allen Probe Data: Typical Behavior of Energetic Electrons in the Inner Magnetosphere

Abstract The Earth's inner magnetosphere contains multiple electron populations influenced by different factors. The cold electrons of the plasmasphere, warm plasma that contributes to the ring current, and the relativistic plasma of the radiation belts often seem to behave independently. Using omni‐directional flux and energy measurements from the HOPE and Magnetic Electron Ion Spectrometer instruments aboard the Van Allen Probes, we provide a detailed density and temperature description of the inner magnetosphere, offering a comprehensive statistical analysis of the entire Van Allen Probe era. While number density and temperature data at geosynchronous orbit are available, this study focuses on the warm plasma in the inner magnetosphere . Values of density and temperature are extracted by fitting energy and phase space density to obtain the distribution function. The fitted distributions are related to the zeroth and second moments to estimate the number density and temperature. Analysis has indicated that a two Maxwellian fit is sufficient over a wide range of and that there are two independent plasma populations. The more energetic population has a median number density of approximately and a temperature of around 130 keV, with a temperature peak observed between L * = 4 and L * = 4.5. This population is relatively uniform in magnetic local time (MLT). In contrast, the less energetic warm electron population has a median number density of about and a temperature of 7.4 keV. Strong statistical trends in density and temperature across both L * and MLT are presented, along with potential sources driving these variations.

58 GEOSCIENCES↗
DOE OSTI2021

Overview of SoLID

SoLID spectrometer was proposed to fully exploit the potential of JLab 12 GeV energy upgrade. It is a large acceptance detector which can handle very high luminosity. An overview of the rich physics program will be given, which includes number of planned measurements: a multi-dimensional mapping of semi-inclusive DIS asymmetries for tomography of the nucleon in momentum space in the high-x region and precision determination of the tensor charge; a measurement of parity-violating DIS to provide a precision test of the Standard Model, reaching a sensitivity to new physics at 10-20 TeV level; a precision measurement of J/psi photo- and electro-production cross sections in the threshold region to probe the strong color fields in the nucleon and to study the origin of the proton mass. The current status and the plan of the project will be discussed.

Chen, Jian-Ping↗
DOE OSTI2021

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Amino‐Functionalised Hybrid Ultramicroporous Materials that Enable Single‐Step Ethylene Purification from a Ternary Mixture

Abstract Pyrazine‐linked hybrid ultramicroporous (pore size <7 Å) materials (HUMs) offer benchmark performance for trace carbon capture thanks to strong selectivity for CO 2 over small gas molecules, including light hydrocarbons. That the prototypal pyrazine‐linked HUMs are amenable to crystal engineering has enabled second generation HUMs to supersede the performance of the parent HUM, SIFSIX‐3‐Zn , mainly through substitution of the metal and/or the inorganic pillar. Herein, we report that two isostructural aminopyrazine‐linked HUMs, MFSIX‐17‐Ni (17=aminopyrazine; M=Si, Ti), which we had anticipated would offer even stronger affinity for CO 2 than their pyrazine analogs, unexpectedly exhibit reduced CO 2 affinity but enhanced C 2 H 2 affinity. MFSIX‐17‐Ni are consequently the first physisorbents that enable single‐step production of polymer‐grade ethylene (>99.95 % for SIFSIX‐17‐Ni ) from a ternary equimolar mixture of ethylene, acetylene and CO 2 thanks to coadsorption of the latter two gases. We attribute this performance to the very different binding sites in MFSIX‐17‐Ni versus SIFSIX‐3‐Zn .

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

Latent variable Gaussian process models: A rank‐based analysis and an alternative approach

Abstract Gaussian process (GP) models have been extended to emulate expensive computer simulations with both qualitative/categorical and quantitative/continuous variables. Latent variable (LV) GP models, which have been recently developed to map each qualitative variable to some underlying numerical LVs, have strong physics‐based justification and have achieved promising performance. Two versions use LVs in Cartesian (LV‐Car) space and hyperspherical (LV‐sph) space, respectively. Despite their success, the effects of these different LV structures are still poorly understood. This article illuminates this issue with two contributions. First, we develop a theorem on the effect of the ranks of the qualitative factor correlation matrices of mixed‐variable GP models, from which we conclude that the LV‐sph model restricts the interactions between the input variables and thus restricts the types of response surface data with which the model can be consistent. Second, following a rank‐based perspective like in the theorem, we propose a new alternative model named LV‐mix that combines the LV‐based correlation structures from both LV‐Car and LV‐sph models to achieve better model flexibility than them. Through extensive case studies, we show that LV‐mix achieves higher average accuracy compared with the existing two.

Tao, Siyu↗
DOE OSTI2022

Double copy for massive scalar field theories

We explore extensions of the double copy to massive theories and find a new cubic theory with a local double copy. We consider the nonlinear sigma model and the special galileon theory, massless versions of which are known to be related through the double copy. We show that by performing a Kaluza-Klein reduction of these theories from five dimensions down to four, a double copy relation exists between the resulting massive four-dimensional scalar field theories. This requires the vanishing contribution of new galileon terms arising in high dimensions. We further explore if other interactions that do not arise from a dimensional reduction of the nonlinear sigma model could be double copied and find a new cubic interaction which satisfies the BCJ relations up to 5-point amplitudes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A Goldstone boson equivalence for inflation

The effective field theory of single-field inflation characterizes the inflationary epoch in terms of a pattern of symmetry breaking. An operator acquires a time-dependent vacuum expectation value, defining a preferred spatial slicing. In the absence of dynamical gravity, the fluctuations around the time-dependent background are described by the Goldstone boson associated with this symmetry breaking process. With gravity, the Goldstone is eaten by the metric, becoming the scalar metric fluctuation. In this paper, we will show that in general single-field inflation, the statistics of scalar metric fluctuations are given by the statistics of this Goldstone boson decoupled from gravity up to corrections that are controlled as an expansion in slow-roll parameters. This even holds in the presence of additional parameters, like the speed of sound, that naively enhance the impact of the gravitational terms. In the process, we derive expressions for leading and sub-leading gravitational corrections to all-orders in the Goldstone boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A unified system for Coleman–De Luccia transitions

Highlights: • Monotonicity controls whether radius of CDL bounce is negative mode direction. • Decays from de Sitter and Anti-de Sitter analyzed in single geometric framework. • de Sitter to Anti-de Sitter instantons come in two types, similar to type-A vs type-B. We show that the presence or absence of negative modes associated with the expansion or contraction of Coleman–De Luccia instantons is controlled by the monotonicity properties of a single function parameterized by the tension and two vacuum energies. This approach simplifies and unifies certain aspects of phase transitions between two de Sitter vacua, between two Anti-de Sitter, and between one of each. This strategy may serve as a guide for identifying negative modes in more complicated gravitational theories, for instance supergravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quantum dynamics of photon in rainbow gravity

In the present article, quantum dynamics of the photon is investigated in the cosmic string spacetime via gravity’s rainbow. We solve the mDKP (massless Duffin–Kemmer–Petiau) equation exactly and obtain the energy spectrum of photon. Then, we solve the Maxwell equations in the same gravity’s rainbow background and show that the solutions obtained are equivalent to the results of the photon equation. The energy spectrum of the photon is analyzed for three different rainbow functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Layered oxide cathode-inspired secondary hard carbon microsphere anode material for high-power and long-life rechargeable batteries

A new anode material that will provide lithium ion (Li-ion) batteries with high energy and power density is urgently needed. In this work, a layered oxide cathode-inspired secondary hard carbon microsphere (CMS) anode material was designed, and exhibited excellent rate performance and long cyclability. Polyacrylonitrile/poly(styrene-co-acrylonitrile) (PAN/SAN) compositions displaying the meatball-like shape of the PAN precursor were carbonized into CMSs having turbostratic microstructures. The CMS carbonized at 1,000°C (CMS1000) displayed high specific capacity at the highest current density of 1,000mAg -1 , i.e., 77.6 % of its average charge capacity at 100 mA g -1 , and considerable cycling retention after 500 cycles, i.e., 83.8 % of the specific capacity at cycle 25. In conclusion, our work demonstrates that the design of new anode materials is a fruitful route to improve commercial Li-ion batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Multi-arrival infrasound from meteoroids: Fragmentation signatures versus propagation effects in a fine-scale layered atmosphere

Infrasonic signatures of meteoroid fragmentation are frequently ambiguous: do multiple arrivals signify a complex breakup or merely the distorting effects of a layered atmosphere? Resolving this ambiguity is critical for accurate energy estimates and source reconstruction. In this study, we address this challenge by analyzing a unique regional dataset of well-constrained meteoroid events observed by the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. We employ pseudo-differential parabolic equation (PPE) simulations to quantify how fine-scale gravity-wave structures in the stratosphere and lower thermosphere modify acoustic waveforms at ranges <300 km. Our modeling reveals that while fine-scale layering can stretch signals and generate diffuse oscillatory tails, it does not produce discrete, high-amplitude pulse splitting at ranges below ∼140 km. By applying these results to the rare multi-arrival event 20060305, we demonstrate that its distinct double arrival at 100 km range is inconsistent with atmospheric multipathing and provides definitive evidence of separate fragmentation episodes. These findings establish new diagnostic criteria for separating source physics from propagation artifacts, improving the reliability of infrasound as a monitoring tool for natural bolides, space debris re-entries, and catastrophic launch failures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2025

Annealing-Driven Phase Control Enables Plasmonic Tunability in Alloy Nanoparticles

A critical aspect of designing and realizing useful solid state materials is controlling phase and structure to tailor physical properties. While common for semiconductor and quantum materials, plasmonic materials have inhabited a narrow phase space typically comprising one or two elements, e.g., face-centered cubic metals. While this simplicity has enabled robust use and understanding of Au and Ag nanoparticles, it has also limited the design and manipulation of solid state properties. Here, we show that by tuning the phase and elemental composition of binary Au−Sn nanoparticles, the steady-state absorbance and ultrafast thermalization properties of plasmonic nanoparticles can be controlled. Solid state characterization suggests this is due to the dealloying of Sn and destabilization of the AuSn phase, leading to higher quality Au 5 Sn intermetallic phases alongside Au. Consequently, this work shows that phase control can profoundly influence the properties of plasmonic nanoparticles, providing important tunability for applications in catalysis, photothermal heating, and sensing.

Gold↗
DOE OSTI2020

Fundamentals of Using Cracked Film Lithography to Pattern Transparent Conductive Metal Grids for Photovoltaics

The fundamentals of using cracked film lithography (CFL) to fabricate metal grids for transparent contacts in solar cells were studied. The underlying physics of drying-induced cracks were well-predicted by an empirical correlation relating crack spacing to capillary pressure. CFL is primarily controlled by varying the crack template thickness, which establishes a three-way tradeoff between the areal density of cracks, crack width, and spacing between cracks, which in turn determine final grid transmittance, grid sheet resistance, and the semiconductor resistance for a given solar cell. Since CFL uses a lift-off process, an additional constraint is that the metal thickness must be less than 1/3 of the crack template thickness. Furthermore, the transmittance/grid sheet resistance/wire spacing tradeoffs measured in this work were used to calculate solar cell performance: CFL-patterned grids should outperform screen-printed grids for narrow cells (0.5–2 cm wide) and/or cells with high semiconductor sheet resistance (=100 O/sq), making CFL attractive for monolithically integrated thin-film photovoltaic modules.

14 SOLAR ENERGY↗
DOE OSTI2021

Physics-Informed Neural Network Method for Forward and Backward Advection-Dispersion Equations

Advection-dispersion equations (ADEs) are commonly used to describe transport phenomena in porous media. Even though mature discretization-based numerical methods for ADEs exist, some challenges still remain, especially when it comes to solving advection-dominated forward ADEs and diffusion-dominated backward ADEs. The latter problem usually arises in the source identification context and leads to numerically unstable grid-based solutions that require a form of regularization or should be treated as an inverse problem that is computationally more expensive because it requires solving the forward problem multiple times. In this study, we propose a discretization-free approach based on the physics-informed neural network (PINN) method for solving coupled ADE and Darcy flow equations with space-dependent hydraulic conductivity. In this approach, the hydraulic conductivity, hydraulic head, and concentration fields are approximated with deep neural networks (DNNs). We assume that the conductivity field is given by its values on a grid, and we use these values to train the conductivity DNN. The head and concentration DNNs are trained by minimizing the residuals of the flow equation and ADE and using the initial and boundary conditions as additional constraints. The PINN method is applied to one- and two-dimensional forward ADE problems, where its performance for various P\'{e}clet numbers ($Pe$) is compared with the analytical and numerical solutions. We find that the PINN method is accurate with errors of less than 1\% and outperforms some conventional discretization-based methods for $Pe$ larger that 100. Next, we demonstrate that the PINN method remains accurate for the backward ADEs, with the relative errors in most cases staying under 5\% compared to the reference concentration field. Finally, we show that when available, the concentration measurements can be easily incorporated in the PINN method and significantly improve (by more than 50\% in the considered cases) the accuracy of the PINN solution of the backward ADE.

He, Qizhi↗
DOE OSTI2026

Rotation‐Controlled Diurnal Evolution of Uranus' Asymmetric Bow Shock at Equinox

Uranus possesses the most extreme magnetic and rotational geometry in the solar system, resulting in a uniquely dynamic and asymmetric interaction between its magnetosphere and the solar wind. Here we investigate the diurnal evolution of the Uranian bow shock (BS) at equinox using global multifluid magnetohydrodynamic simulations constrained by Voyager 2 observations. The BS structure and variability are quantified using the stand‐off distance, terminator distance, flaring parameter, and BS parameter, enabling a systematic assessment of its global asymmetry over one planetary rotation. Our results show that the BS exhibits pronounced diurnal asymmetry that is primarily controlled by planetary rotation. Even under steady upstream solar wind conditions, the BS undergoes periodic expansion and contraction, reflecting rotation‐driven reconfiguration of the planetary magnetospheric topology. This diurnal modulation represents a remarkably large asymmetry in planetary BS geometry within the solar system. These results establish planetary rotation as the intrinsic primary driver of Uranus' BS dynamics at equinox and provide essential constraints for the design and formulation of future space missions to the ice giants. These findings also offer a unique framework for understanding shock physics in the abundant population of ice‐giant exoplanets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Probabilistic effects of porosity and chemical kinetics on the shock initiation of an octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) based explosive

In this work, we investigate the effects of porosity and chemical reactivity on the shock initiation of an HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine)-based polymer bonded explosive due to thin flyer impact using two-dimensional mesoscale simulations. Microstructural samples are computationally generated, and the calculated shock response is compared to experiments. The sample dimensions are 0.1×1.05 mm 2 , and each sample accounts for grain scale heterogeneities, including randomized grain morphology and pore spacing. Simulations are performed using the Lawrence Livermore National Laboratory (LLNL) arbitrary Lagrangian–Eulerian multi-physics code ALE3D. Chemistry and equation of states are handled with LLNL's thermochemical code Cheetah. We employ a modified Arrhenius-based chemical kinetics model that scales the temperature exponent fitting parameter with flyer shock conditions. This new model is calibrated to the mean response of experimental shock initiation thresholds for three separate Kapton flyer thicknesses. A simplified shock initiation criterion is proposed, which classifies the macroscale initiation response based on cross-sectional temperature profiles of the shocked sample. This criterion is used to further investigate the probabilistic response of the sample to variations in the mean porosity and chemical kinetics rate, and we find an inverse correlation between the shock pressure and the confidence interval of the experimental threshold velocity. Furthermore, the methodology presented in this work for quantifying the probabilistic nature of shock initiation is material agnostic. These mesoscale studies may be used to inform continuum scale models and expedite the development of future, tailored energetic formulations.

36 MATERIALS SCIENCE↗