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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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DOE OSTI2025

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗
DOE OSTI2024

Symbiotic bacteriophages exhibit multiple adaptive strategies in activated sludge flocs and contribute to floc stability

Despite the importance of phages for the dynamics and functions of microbial communities, it remains largely unexplored how symbiotic phages adapt in activated sludge systems and influence microbial aggregate stability, which is critical for clarification and reliable performance. Here, based on 12,127 phage contigs recovered from 12 activated sludge microbiomes, the symbiotic phages exhibited broad host ranges and infected dominant prokaryotes in activated sludge. Moreover, these phage communities exhibited high lysogenicity (49% to 66% lysogenic phages) and harbored diverse auxiliary metabolic genes (AMGs) that could enhance microbial aggregate stability, such as genes coding for lipopolysaccharide, peptidoglycan, and extracellular polysaccharide biosynthesis. Additionally, prokaryotic antiviral systems were widely distributed in dominant prokaryotes, particularly the Restriction-Modification (RM) and CRISPR-Cas systems, which could mitigate potential harmful phage infections. Overall, this study reveals the contemporary beneficial relationship between phages and prokaryotic hosts in activated sludge microbiomes and the potential benefits of symbiotic phages on floc stability.

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

Structural evolution of liquid silicates under conditions in Super-Earth interiors

Molten silicates at depth are crucial for planetary evolution, yet their local structure and physical properties under extreme conditions remain elusive due to experimental challenges. In this study, we utilize in situ X-ray diffraction (XRD) at the Matter in Extreme Conditions (MEC) end-station of the Linear Coherent Linac Source (LCLS) at SLAC National Accelerator Laboratory to investigate liquid silicates. Using an ultrabright X-ray source and a high-power optical laser, we probed the local atomic arrangement of shock-compressed liquid (Mg,Fe)SiO 3 with varying Fe content, at pressures from 81(9) to 385(40) GPa. We compared these findings to ab initio molecular dynamics simulations under similar conditions. Results indicate continuous densification of theO-O and Mg-Si networks beyond Earth’s interior pressure range, potentially altering melt properties at extreme conditions. This could have significant implications for early planetary evolution, leading to notable differences in differentiation processes between smaller rocky planets, such as Earth and Venus, and super-Earths, which are exoplanets withmasses nearly three times that of Earth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2024

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Variability of MHD instabilities in benign termination of high-current runaway electron beams in the JET and DIII-D tokamaks

Benign termination, in which magnetohydrodynamic (MHD) instabilities deconfine runaway electrons (REs) following hydrogenic injections, is a promising strategy for mitigating dangerous RE loads after disruptions. Recent experiments on the Joint European Torus (JET) have explored this scenario at higher pre-disruptive plasma currents than are achievable on other devices, revealing challenges in obtaining benign terminations at I p ≥2.5 MA. This work analyzes the evolution of these high-current RE beams and their terminating MHD events using fast magnetic sensor measurements and EFIT equilibrium reconstructions for approximately 40 JET and 20 DIII-D tokamak discharges. On JET, unsuccessful non-benign terminations occur at low edge safety factor (q edge ≈ 2), and are preceded by intermittent, non-terminating MHD events at higher rational qedge. Trends in the internal inductance I i indicate more peaked RE current profiles in the high-I p non-benign population, which may hinder successful recombination through re-ionization of the companion plasma. In contrast, benign terminations on JET typically occur at higher q edge ≥3 and exhibit less peaked RE current profiles. DIII-D displays a broader range of terminating edge safety factors, again correlated with the measured values. Across both tokamaks, the RE current peaking is therefore found to determine which MHD instability boundary is encountered, a result confirmed by linear resistive MHD modeling with the CASTOR3D code. Measured growth rates are similar for benign and non-benign cases, indicating that ideal MHD timescales at low density after hydrogenic injection do not alone explain efficient RE deconfinement. Instead, non-benign cases are most readily characterized by their comparably lower overall MHD perturbation amplitudes δB. These observations suggest that the interplay between ideal and resistive dynamics governs the termination process, with implications for extrapolating benign RE termination to high-I p reactor scenarios.

MHD instabilities↗
DOE OSTI2025

On the effectiveness of neural operators at zero-shot weather downscaling

Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

17 WIND ENERGY↗
DOE OSTI2025

Quasielastic and Inelastic Neutron Scattering Study of Ultraconfined Water in Natural Mordenite ((Ca,Na 2 ,K 2 )Al 2 Si 10 O 24 ·7H 2 O)

Mordenite ((Ca,Na 2 ,K 2 )Al 2 Si 10 O 24 ·7H 2 O) is a natural and synthetic nanoporous zeolite containing several channels of different sizes in its structure. Because of this, its structure provides an important opportunity to study the relationship between confined and ultraconfined water as these channels have sizes between those typical of these water environments. In this study, the properties of water molecules in these environments were analyzed using inelastic and quasielastic neutron spectroscopy of a natural mordenite. The quasielastic spectra showed the presence of nonfreezing, mobile water molecules through the entire temperature range of the measurements, but very little anisotropy of the dynamics measured along and perpendicular to the channels. Faster and slower quasi-elastic neutron scattering (QENS) components may be consistent with the presence of two separate classes of water molecules in mordenite. Inelastic neutron spectroscopy also found no evidence of directional anisotropy. In conclusion, the strong intensity characteristic of neutron recoil on protons from highly mobile water molecules at low temperature (5 K), along with a significant shift of water librational band to lower energies and the O–H stretching modes to high energies, indicate that the hydrogen bonds acting on these water molecules in mordenite resemble those in liquid water rather than ice.

Crystal structure↗
DOE OSTI2025

Dimensional Control in Phase-Pure Coevaporated Quasi-2D Ruddlesden–Popper Structures

Fast, uncontrolled crystallization with several competing pathways makes solution-processing of phase-pure quasi-two-dimensional (quasi-2D) metal halide Ruddlesden–Popper thin films challenging. Typically, solution-processing results in the formation of different structural phases with varying dimensionality ranging from 2D, to quasi-2D, and 3D, introducing bandgap disorder and inhibiting charge transport. In this work, we eliminate interactions between precursor salts and solvents by using controlled thermal coevaporation to grow quasi-2D thin films that show high phase purity and narrow phase distribution. We study the structural landscape using synchrotron-based X-ray scattering and charge-carrier dynamics using ultrafast pump–probe spectroscopy. We then demonstrate a strategy to control the crystallographic phase of the film through phosphonic acid-based surface modification. We use density functional theory to study the interactions between propylphosphonic acid and the organic precursors and find that the interactions of loosely bound phosphonic acid molecules with evaporated precursors, followed by the migration of phosphonic acids through the deposited thin film, dictate the film structure between 2D and quasi-2D phases. These findings introduce new solvent-free methods for the fabrication of phase-pure quasi-2D Ruddlesden–Popper thin films and control phase selectivity across different dimensional (2D and quasi-2D) structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Responses of Marginal and Intrinsic Water-Use Efficiency to Changing Aridity Using FLUXNET Observations

According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water-use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non-linear mWUE-VPD relationship at a sub-daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid-range of VPD. Despite the highly non-linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem-level inherent water-use efficiency (IWUE) and mWUE using the slope, m *. We further identify site-specific m * and its variability with changing site-level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Role of effective mass and long-range interactions in the band-gap renormalization of photoexcited semiconductors

Understanding how to control changes in the electronic structure and related dynamical renormalizations by external driving fields is the key for understanding ultrafast spectroscopy and applications in electronics. Here, we focus on the band gap's modulation by external electric fields and uncover the effect of band dispersion on the gap renormalization. We employ the Green's function formalism using the real-time Dyson expansion to account for dynamical correlations induced by photodoping. The many-body formalism captures the dynamics of systems with long-range interactions, carrier mobility, and variable electron and hole effective mass. We also demonstrate that mean-field simulations based on the Hartree-Fock Hamiltonian, which lacks dynamical correlations, yields a qualitatively incorrect picture of band-gap renormalization. We find the trend that increasing effective mass, thus decreasing mobility, leads to as much as a 6% enhancement in band-gap renormalization. Further, the renormalization is strongly dependent on the degree of photodoping. As the screening induced by free electrons and holes effectively reduces any long-range and interband interactions for highly excited systems, we show that there is a specific turnover point with a minimal band gap. Here, we further demonstrate that the optical gap renormalization follows the same trend though its magnitude is altered by the Moss-Burstein effect.

Approximation methods for many-body systems↗
DOE OSTI2026

Unitary Qubit Lattice Algorithms for Plasma Physics

This final technical report summarizes research conducted under DOE Award DE-SC0021653 to develop unitary Quantum Lattice Algorithms for modeling electromagnetic wave propagation and scattering in complex media, including plasmas. The project developed and validated quantum-inspired formulations of Maxwell's equations that preserve unitary evolution and can be evaluated on classical high-performance computing systems while providing a foundation for future quantum-computing implementations. Major accomplishments include the development of two- and three-dimensional algorithms for electromagnetic scattering; scalable, distributed-memory implementations demonstrated on the Perlmutter supercomputer; formulations for nonlinear lossless fluid dynamics and cold, lossless, inhomogeneous magnetized plasmas; and an explicit quantum algorithm for a time-discretized Lorenz model. Simulations reproduced a range of characteristic wave phenomena, including transient effects that are not readily apparent in conventional frequency-domain studies, demonstrating the effectiveness of the proposed approach for modeling complex electromagnetic and plasma systems. The work establishes a unified theoretical and computational framework for quantum and quantum-inspired simulation and provides a foundation for future implementation on fault-tolerant quantum systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

In-situ kinetic study of irradiation induced crystallization in amorphous Al 2 O 3

In the last ten years amorphous alumina coatings, deposited by Pulsed Laser Deposition, emerged as potential key enabling technology in the fields of heavy liquid metal fast reactors (lead and lead-bismuth) and fusion. In the former, as coating of the steel fuel cladding and in the latter as multifunctional coating providing a barrier against tritium permeation, steel corrosion and electrical insulation. Nevertheless, a detailed knowledge of the behavior of this thermodynamically metastable material at high temperatures and under neutron irradiation is still unknown. A knowledge gap that is mandatory to fill up for the deployment of this barrier technology. In the present work, we present a first step towards this goal, by the in-situ dynamic observation of the radiation induced crystallization processes of thin films of amorphous Al 2 O 3 , induced by ion-irradiation over an extensive range of temperatures (400-800 °C). The study was performed at the Intermediate Voltage Electron Microscope (IVEM)-Tandem Facility at Argonne National Laboratory. The experimental findings allow to elucidate the dependence of the grain growth on ion dose and temperature. A kinetic approach has been used to derive the process activation energies and other important parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗
DOE OSTI2024

Defect-induced formation and frustration-driven multiple magnetic transitions in Gd 2 Co 0.90 Si 2.90

A new ternary compound, Gd 2 Co 0.90 Si 2.90 , has been synthesized in a chemically single phase by deliberately introducing lattice vacancies in the Co and Si sites. The system is characterized by DC magnetization, heat capacity, resistivity and density functional theory (DFT) calculations. Here, a detailed experimental study reveals that the system exhibits an antiferromagnetic transition below T N = 11.3 K followed by spin freezing behaviour below T B ~ 4.8 K. An additional high-temperature magnetic transition could also be detected at T H ~ 150 K, which is short range in character and is associated with defect-induced polarization of the conduction electrons. The spin-glass-like state formation in the system is additionally bolstered by the observation of magnetic relaxation and associated aging phenomena as well as the magnetic memory effect. On the basis of non-equilibrium dynamical behaviour, we argue that the glassy state in this compound favours the hierarchical model over the droplet model. DFT calculations and experimental outcomes establish that the ground state is magnetically frustrated due to the small energy difference between distinct spin configurations having closely spaced ground-state energies.

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

Active Learning of Microgrid Frequency Dynamics Using Neural Ordinary Differential Equations

Accurate frequency modelling of inverter‐based resource (IBR)‐dominated power systems is crucial for ensuring stable, reliable and resilient operations, particularly given their inherent low‐inertia characteristics and fast dynamics that traditional swing equation‐based models inadequately capture. This paper explores neural ordinary differential equations (Neural ODEs) as a computationally efficient, data‐driven framework for modelling power system frequency dynamics, specifically within microgrids integrating high penetrations of distributed energy resources (DERs). The developed neural ODEs framework incorporates a neural network architecture designed to capture input dynamics. By actively perturbing the system with a known signal, the Python‐based neural ODEs framework was trained using measured system states and inputs, without the need for detailed system information. The framework, tested on a model of the Cordova, AK, microgrid, achieved a goodness of fit ranging from 60% to 99% across different state variables and maintained a mean square error in the 10 -6 p.u. range under square and step excitation signals. The proposed approach demonstrated robustness to measurement noise and initial condition variations while maintaining low computational complexity suitable for real‐time power system control applications. Furthermore, transfer learning enabled the neural ODEs model to adapt to the following changes in system topology or generator dispatch, highlighting its effectiveness for dynamic microgrids with frequently evolving configurations and diverse DERs.

Aryal, Tara [South Dakota State Univ., Brookings, ↗
DOE OSTI2025

Laser-driven flash x-ray radiography of a shocked metallic foil

Characterizing hydrodynamic instability evolution in millimeter-scale, high-Z foils is crucial for understanding complex phenomena in high-energy-density physics. Here, we demonstrate a proof-of-concept, laser-driven flash x-ray radiography platform tailored for two-dimensional linear density mapping in shocked high-Z foils. Using chromium (Cr) foils with internal shockwaves (∼100 μm width), our platform achieves a spatial resolution of 59.8 ± 1.4 μm by employing a broadband x-ray source extending into the hundreds of keV range. The setup combines a compound parabolic concentrator cone with a tantalum wire target, a magnetic field to deflect residual transmitted electrons, and a copper casing to shield the sides and rear of the image plate pack. By varying the delay of the short-pulse beam driving the flash x-ray source, we resolve shockwave dynamics, specifically the velocity, position, width, and density profile, within the Cr foil. Reported experimental results are consistent with the corresponding hydrodynamics and radiation transport simulations, which accurately reproduce the measured electron and x-ray source terms. These developments enable the conversion of shockwave radiographs into two-dimensional density maps, enhancing interpretability for hydrodynamic instability evolution applications and validating the simulation approach.

36 MATERIALS SCIENCE↗