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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cyclotron production of a 204 Bi/ 204m Pb generator by 24 MeV proton irradiation of natural Pb foil targets

This work focuses on the formation of a generator of 204 Bi/ 204m Pb for future applications in perturbed angular correlation spectroscopy and biological radiotracing with lead and bismuth isotopes. Generators were formed from the irradiation of natural Pb targets with 24 MeV protons producing 203,204,205,206,207 Bi that were rapidly dissolved in 3 M HNO 3 and 30 % H 2 O 2 and exchanged into a 0.1 M HCl matrix. Use of 100 mg anion exchange resin (AG 1-x8) allowed 203,204m Pb to be eluted in 600 μL of 0.1 M HCl. Furthermore, the longer-lived 205,206 Bi were eluted in 5 mL or 3 mL of either 0.25 M sodium acetate buffer pH 4.4 or 1.0 M H 2 SO 4 . Initial radiolabeling was conducted with eluted 206 Bi using DTPA and DOTA and 203 Pb using TCMC-Azide.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Bacterial microcompartment architectures as biomaterials for conversion of gaseous substrates

Bacterial microcompartments (BMCs) are protein shells encapsulating multiple enzymes of a metabolic pathway. Interpretations of early experiments on carboxysomes led to the narrative that transport of small gases (CO 2 , O 2 ) across the shell membrane is restricted. Since then, this notion has been largely contradicted by studies of engineered shells, although these shell constructs lack important proteins present in the native BMCs, altering the synthetic shells’ topology, surface and mechanical properties. Here, we discuss here an updated model of gas permeability that informs the design of engineered shells for catalysis on gas substrates and outline how nonshell suprastructures of BMC shell proteins could be used in formulating sustainable biomaterials for hydrogen generation via methane pyrolysis and for other greenhouse gas mitigations.

Bacterial microcompartment↗
DOE OSTI2025

JuTrack: A Julia package for auto-differentiable accelerator modeling and particle tracking

Efficient accelerator modeling and particle tracking are key for the design and configuration of modern particle accelerators. In this work, we present JuTrack, a nested accelerator modeling package developed in the Julia programming language and enhanced with compiler-level automatic differentiation (AD). With the aid of AD, JuTrack enables rapid derivative calculations in accelerator modeling, facilitating sensitivity analyses and optimization tasks. Here we demonstrate the effectiveness of AD-derived derivatives through several practical applications, including sensitivity analysis of space-charge-induced emittance growth, nonlinear beam dynamics analysis for a synchrotron light source, and lattice parameter tuning of the future Electron-Ion Collider (EIC). Through the incorporation of automatic differentiation, this package opens up new possibilities for accelerator physicists in beam physics studies and accelerator design optimization.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Operation of helium sub-atmospheric multistage cryogenic centrifugal compressor trains: Part 1 – Steady state modeling and speed ratio selection

Helium cryogenic systems which can provide cooling below the normal boiling point of helium (approximately 4.2 K) are often required by superconducting radio-frequency niobium resonators utilized in modern high-energy particle accelerators. Achieving temperatures below 4.2 K generally involves operating a cryogenic vessel with liquid helium under sub-atmospheric conditions, thereby lowering the saturation pressure and corresponding saturation temperature. Over the last several decades, multi-stage cryogenic centrifugal compressor trains (CC’s) have been operated efficiently and reliably within large-scale cryogenic systems to continuously evacuate helium vapor generated by a device within the vessel, maintaining sub-atmospheric conditions in the vessel while pressurizing the return vapor to above atmospheric conditions. Traditionally, these CC systems have been operated using empirically derived control philosophies and insight gathered from previous operational experience. Recent efforts at the Facility for Rare Isotope Beams (FRIB) have been aimed at the development of a theoretical basis to characterize the operation of multi-stage cryogenic centrifugal compressor train and utilizing predictive model results to generate control parameters. The objective of this research was identifying operational points which adequately balance cryogenic system efficiency, stability, and overall ease of operation. Furthermore, this manuscript provides an overview of the predictive model development, characterization of the FRIB cryogenic centrifugal compressors and implementation of the predicted performance results during steady-state system operation.

Compressor train control↗
DOE OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2024

What to expect when you're expecting engagement: Delivering procedural justice in large-scale solar energy deployment

Community engagement in the planning process to build large-scale solar (LSS) projects can win local support and advance procedural justice. However, an understanding of community engagement in current LSS development is lacking. Using responses from a U.S. nationwide survey (n = 979) of residential neighbors living within 3 miles (4.8 km) of completed LSS projects (i.e. “solar neighbors”) and project details from the U.S. Large-Scale Solar Photovoltaic Database (USPVDB), this study seeks to answer the following questions: How are solar neighbors' perceptions of community engagement associated with their attitudes toward their LSS projects? How do solar neighbors' perceptions of community engagement compare to their expectations? And, how do neighbors explain what they perceived about the planning process? We answer these questions using mixed methods, including regression modeling, a new gap analysis technique, and qualitative coding. We find that higher perceived engagement is associated with more positive attitudes toward the project, even when controlling for respondents who acted in opposition. Supporters and opponents alike expect more engagement than they perceived and information about projects both before construction and after operation is lacking. Awareness and engagement expectations increase at certain project size and proximity thresholds. However, most neighbors expect the public to offer input during engagement, but not make decisions. We contextualize these findings with explanatory comments from respondents.

14 SOLAR ENERGY↗
DOE OSTI2024

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗
DOE OSTI2025

ER stress and viral defense: Advances and future perspectives on plant unfolded protein response in pathogenesis

Viral infections pose significant threats to crop productivity and agricultural sustainability. The frequency and severity of these infections are increasing, and pathogens are evolving rapidly under the influence of climate change. This underscores the importance of exploring the fundamental mechanisms by which plants defend themselves against dynamic viral threats. One such mechanism is the unfolded protein response (UPR), which is activated when the protein folding demand exceeds the capacity of the endoplasmic reticulum, particularly under adverse environmental conditions. While the key regulators of the UPR in response to viral infections have been identified, our understanding of how they modulate the UPR to suppress plant viral infections at the molecular and genetic levels is still in its infancy. Recent findings have shown that, in response to plant viral infections, the UPR swiftly reprograms transcriptional changes to support cellular, metabolic, and physiological processes associated with cell viability. However, the underlying mechanisms and functional outcomes of these changes remain largely unexplored. Here, we highlight recent advances in plant UPR research and summarize key findings related to viral infection–induced UPR, focusing on the balance between prosurvival and prodeath strategies. We also discuss the potential of systems-level approaches to uncover the full extent of the functional link between the UPR and plant responses to viral infections.

ER stress↗
DOE OSTI2025

Upcycling of post-consumer mixed polyolefin feedstock: An economic and technical evaluation

Here, this study reports techno-economic and life cycle analyses to evaluate the economic and environmental impacts of mechanically recycled PE/PP blends in the presence of rheology modifiers. Additionally, fiber-reinforced composites derived from the compatibilized blends were prepared and evaluated for their performance compared with virgin plastics. Results suggest that compatibilized PE/PP blends exhibit a 70% lower selling price compared to virgin PE. Furthermore, these blends achieved a 74% reduction in greenhouse gas emissions or climate change impact compared to the virgin counterpart. Fiber-reinforced composites from compatibilized PE/PP blends demonstrated improved or comparable mechanical properties relative to composites made from virgin PE/PP blends. Based on their favorable cost and environmental impact, along with performance comparable to virgin composites, compatibilized PP/PE composites made from post-consumer plastics can find applications in large-scale composite manufacturing.

Fiber reinforced plastics (FRP)↗
DOE OSTI2025

Experimental characterization and atomistic simulation of grain boundary segregation in Mg-Y alloys

As a rare earth solute element in Mg alloys, Y has the beneficial effects of increasing both the strength and the ductility as well as weakening the crystallographic texture. To achieve a more fundamental understanding on how Y addition affects the microstructural evolution and mechanical properties, the Y segregation behavior at grain boundaries was investigated in Mg-1wt.%Y and Mg-7wt.%Y alloys at different conditions. The segregation intensity and its dependence on the grain boundary misorientation angle were experimentally characterized and computationally predicted. Strong segregation at grain boundaries was observed in both low and high Y-containing alloys. Y segregation was found to remain in alloy Mg-7Y after high-temperature annealing heat treatment at 540 °C. No direct correlation between the Y segregation intensity and the grain boundary misorientation angle could be established based on either the experimental characterization or the atomistic simulation with a spectral model. We thus conclude that grain boundary segregation of Y is independent of grain boundary misorientation angle.

Grain boundary↗
DOE OSTI2026

Multi-material additive manufacturing of aluminum 6061-T6 alloy with stainless steel 304: Suppression of intermetallic compounds and interface growth mechanism

Fabricating integrated aluminum-steel structures is difficult because of metallurgical incompatibilities that promote intermetallic compound (IMC) formation at their interfaces. This work introduces a practical route for additively manufacturing 6061-T6 aluminum alloy (AA6061-T6) directly onto 304 stainless steel (SS304) using a high shear strain rate-assisted interfacial bonding mechanism. Through the friction extrusion deposition-based additive manufacturing method, both single- and multi-layer deposits of AA6061-T6 were successfully fabricated on SS304, yielding a robust hybrid multi-material structure. Comprehensive analyses of deposition quality, interface porosity, and bonding performance showed that the interface achieved a tensile strength exceeding 154 MPa under quasi-static loading. Microstructural observations revealed that the deposited aluminum layers experienced severe plastic deformation, resulting in pronounced grain refinement. Importantly, the interfacial zone was found to be free of brittle IMCs, instead containing a thin amorphous layer that evolved through a non-linear reaction-zone growth law. This solid-state additive strategy establishes a promising pathway for lightweight structural systems, nuclear energy component cladding, and multifunctional engineering components, redefining how dissimilar metals can be integrated for advanced applications.

Aluminum alloy↗
DOE OSTI2025

Inference of phase field fracture models

The phase field approach to modeling fracture uses a diffuse damage field to represent cracks. This representation mollifies singularities that arise in computations with sharp interface models and some of the resultant difficulties in the mathematical and numerical treatment of fracture. Phase field fracture models have proven effective at representing crack propagation, branching, and merging. Specific formulations, beginning with brittle fracture, have also been shown to converge to classical solutions. Extensions to cover the range of material failure, including ductile and cohesive fracture, lead to an array of possible models. There exists a large body of literature focusing on this class of models and on the impact of model form on the predicted crack evolution. However, there have not been systematic studies into how optimal models may be chosen. Here, we take a first step in this direction by developing formal methods for identification of the best parsimonious model of phase field fracture given full-field data on the damage and deformation fields. We consider some of the main models that have been used for the degradation of elastic response due to damage and its propagation. Our approach builds upon Variational System Identification (VSI), a weak form variant of the Sparse Identification of Nonlinear Dynamics (SINDy). Furthermore, in this first communication we focus on synthetically generated data but we also consider central issues associated with the use of experimental full-field data, such as data sparsity and noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Helium co-implantation effects on dislocation loop evolution during in situ ion irradiations of a novel additive-manufactured Fe-9Cr steel alloy

This study examines the impact of helium injection rate on dislocation loop evolution during ion irradiation of a novel, additively manufactured (AM) 9Cr reduced-activation ferritic/martensitic (RAFM) steel. Through in situ transmission electron microscopy ion irradiations and post-irradiation characterization, the effects of simultaneous 1 MeV Kr²⁺ and 12 keV He⁺ ion irradiation at 400°C to 5 dpa with varying helium levels were examined. The findings reveal that helium co-injection significantly increases dislocation loop density, primarily through the formation of small defect features exhibiting contrast and projected morphologies consistent with a⟨100⟩ loops (∼1 nm), while suppressing larger a/2⟨111⟩ loops. The findings underscore the complex interplay among continuously increasing helium content, temperature, and alloy composition in the evolution of dislocation loops under irradiation in RAFM steels. The study highlights the need for further investigation into helium-mediated mechanisms, such as proposed interactions between self-interstitial atoms and helium atoms, to enhance the performance of RAFM steels in advanced nuclear reactors.

ANA2↗
DOE OSTI2026

Tetrahedral Zn 2+ doping LiNi 0.6 Mn 0.2 Co 0.2 O 2 improves discharge capacity retention by altering surface Ni valence during cycling and preventing oxygen evolution

5 mol-% Zn 2+ was added to the co-precipitation synthesis of LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) to understand Zn's effect on the structural and electronic properties of NMC622. Zn is determined to successfully dope into the NMC crystal lattice as there is an increase in d-spacing along the [003], [104], and [110] directions and an increase in molar volume (100.75 cm 3 mol -1 for NMC622 and 101.00 cm 3 mol -1 for Zn-NMC). Through XPS, Zn is determined to dope on the tetrahedral 6c Wyckoff site in the NMC structure and TEM-EDS reveals that despite a slight ZnO impurity phase, 1.4 mol-% Zn successfully dopes into the crystal structure. Furthermore, cyclic voltammetry shows a suppressed anodic wave associated with oxygen evolution and EIS demonstrates that Zn-doped NMC decreases charge transfer resistance and increases Li diffusion by an order of magnitude. After the formation cycles, NMC has a higher 1 C accessible capacity, 141 mAh/g, over Zn-NMC (132 mAh/g), but after long term cycling Zn-NMC has a higher accessible capacity (117 mAh/g compared to 96 mAh/g for NMC) and increases discharge capacity retention by 18% leading to longer cycle life.

Electrochemistry↗
DOE OSTI2026

The Primary Interaction Compton Couple algorithm for sorting GRETINA/GRETA interaction points

The Primary Interaction Compton Couple (PICC) algorithm is presented in this work. The algorithm is used to determine the first-interaction-point position for $γ$-ray events in GRETINA. The first-interaction-point position is crucial for in-beam $γ$-ray spectroscopy experiments with fast beams due to the effect of Doppler broadening on the in-beam energy resolution. The development of the algorithm and its performance compared to a tracking algorithm and the Main Interaction assumption is presented. The PICC algorithm is demonstrated with real data to outperform the $γ$-ray energy tracking algorithm used for comparison here and the Main Interaction assumption in first-interaction-point determinations.

GRETINA↗
DOE OSTI2025

Determination of the nat Ti(d,x) 49 V excitation function by liquid scintillation analysis

Here, the experimental cross-sections for deuteron-induced nuclear reactions on natural titanium were measured using the stacked-foil method. Deuteron beams were provided by a Pelletron tandem accelerator at incident energies up to 8 MeV. The cross-sections for the production of 49 V were determined by liquid scintillation analysis, with the highest measured value of 522(32) mb occurring at 5.59(9) MeV. Additionally, the cross-sections for the production of 44m,46,47,48 Sc and 48 V were evaluated using gamma-ray spectroscopy and compared to some available literature.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Surrogate modeling of Monte Carlo radiation transport with convolutional neural networks for shielding optimization

Here, we present a machine learning (ML)-based surrogate model using convolutional neural networks (CNN) designed to emulate the attenuation of neutron fields as they pass through various shielding materials. This model can compute the outgoing neutron flux almost instantaneously and achieves reasonable accuracy compared to traditional Monte Carlo (MC)-based codes, which are computationally intensive. This emulator alleviates the complexity of neutron radiation transport through shielding materials by reducing the dimensionality and enables shielding optimization for a known radiation environment. This optimization process, which would have taken an unrealistic timeline due to several complex radiation transport simulations, can now be achieved in minutes, thus increasing computational capabilities in radiation shielding assessment. We demonstrate the applications of this emulator in computing effective dose rates and optimizing shielding solutions for a heavy-ion accelerator facility, such as the Facility for Rare Isotope Beams, where secondary neutrons produced via beam interactions dominate the radiation environment.

accelerator shielding↗
DOE OSTI2025

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗