SEARCH · Search NASA

Results for “Embedded”

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.

SourceResearch connectionFrom yearThrough year

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

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Mechanical properties, strain hardening, and fracture behavior of ultrasonic additively manufactured Zircaloy-4 after low-temperature neutron irradiation

Ultrasonic additive manufacturing (UAM) is a solid-state, layer-by-layer advanced manufacturing process that has the potential to create custom spatially controlled composites with embedded wires and sensors for nuclear component manufacture. For this work, to assess the feasibility of using UAM for nuclear-relevant materials research, the technique was used to produce a 3.5-mm-thick Zircaloy-4 plate for irradiation testing. The UAM Zircaloy-4 specimens were irradiated in the High Flux Isotope Reactor at a target irradiation temperature of 117 °C to 2.9 displacements per atom (dpa) to assess differences in irradiation-hardening behavior as a function of alloy processing path. The UAM and reference baseplate (BP) materials increased in yield strength by 372±27 MPa and 346±21 MPa, respectively, and both suffered significant reductions in uniform and total elongation attributed to irradiation hardening at low-temperature. Although the materials had similar nanoscale defect structures, including nanoscale black dot/loop features and strain-induced dislocation channels, the UAM material’s processing-related defects resulted in accelerated strain localization and failure as demonstrated by lower post-irradiation uniform elongation of UAM specimens (0.5 %) compared to BP (1.5 %) material. The UAM material also showed considerable anisotropy in mechanical response due to crack propagation along weld boundaries, resulting in differences in strength & ductility when tested parallel and perpendicular to the prior UAM build orientation. Therefore, although the fundamental irradiation response of UAM-processed Zircaloy-4 was phenomenologically comparable to that of BP reference material, additional optimization of the UAM processing is needed to produce irradiation-resistant and nuclear-relevant materials.

Digital image correlation↗

DOE OSTI2025

Effects of ZrN coating and heat treatment on U-Mo dispersion fuel systems under irradiation

The stability of U-Mo fuel particles embedded in an Al matrix under irradiation can be enhanced through ZrN coatings and/or heat treatment. Here, the present study investigates the irradiation behavior of fuel plates containing U-Mo fuel particles fabricated under various heat-treatment conditions and ZrN coating thicknesses. Different fission densities were also applied to each fuel plate to evaluate the effects of these variables. Results indicate that higher fission densities lead to more grain recrystallization and high burnup structure (HBS) development in the fuel particles. Heat treatment was found to mitigate the accumulation of fission gas bubbles in fuel particles at low fission densities by coarsening their grains. Fuel particles with ZrN coatings of a 1.2 μm thickness or above exhibited reduced formation of U-Mo/Al interaction layers, suggesting the existence of a critical ZrN coating thickness that minimizes the development of these layers. Fission gas bubbles were predominantly observed at grain boundaries of U-Mo fuel particles irradiated at low fission densities. Subgrain boundaries, which appeared to originate from the original grain boundaries containing fission gas bubbles or HBSs, were also observed, indicating the early stage of HBS propagation in the fuel particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

A Kinetic Model of the Long-Term Corrosion of Glass-Ceramic Materials

Multiphase waste forms show promise for increased waste loading and for the ability to dispose of contaminated solid and particulate waste through direct densification. However, achieving predictive capability for long-term durability of multiphase waste forms, and thus assessing their possible deployment, requires expanding the current, limited knowledge base. Here, we describe the development of a corrosion model of a two-phase waste form consisting of crystals of known volume fraction embedded in a glass matrix. This model accounts for the dissolution of both the crystalline and glass phases as well as the hydration of the glass phase through an ion exchange reaction. Because of the large difference in solubility between the two phases, the reactive surface of the crystalline phase is a function of the extent of dissolution of the glass phase in this model. Model parameterization was performed using corrosion data, such as from single-pass flow-through tests, for the individual phases. The parameterized corrosion model was evaluated against static dissolution test data for a glass-ceramic multiphase waste form. This evaluation demonstrated the model’s ability to reproduce the time-dependent release of key tracers of glass and crystalline phase dissolution. Hence, the development of a kinetic model provides a pathway for long-term durability predictions and thus the use of multiphase waste forms in nuclear cleanup missions.

Kerisit, Sebastien N.↗

DOE OSTI2026

Using X-ray spectrum imaging to quantify fission gas in high-burnup UO2 fuel

Analysis of fission gas bubbles (FGBs) in light-water reactor (LWR) fuel is needed to improve the understanding and predictive capability of fuel evolution under normal- and transient conditions. One of the most important parameters of a FGB is the pressure of the gas, primarily Xe, inside it. Bubble volume and location (inter- vs. intragranular) are important considerations as well. However, experimental analysis of such bubbles is challenging due to their small size and embedded nature, and usefulness of the data requires large numbers be analyzed. This paper proposes a method to measure the pressure of Xe bubbles using X-ray spectrum imaging (XSI) in scanning transmission electron microscopy (STEM). From X-ray generation and instrumental parameters, the number of Xe atoms yielding a given number of Xe L-series X-ray counts is estimated, and then from the estimated volume of the bubble the Xe density is estimated, which can then be converted to pressure via an equation-of-state. We apply the method to XSI datasets from high burnup (HBu) fuel from North Anna 1 reactor in as-irradiated and post-LOCA-test conditions and find Xe pressures in the FGBs clustered around 1 GPa.

Parish, Chad [ORNL] (ORCID:0000000312097439)↗

DOE OSTI2025

Comparison of Expert Vocabulary Usage Patterns Between Mental Health and Nonmental Health Clinicians When Diagnosing Pediatric Anxiety Disorders

Objective: To compare the utilization patterns of expert vocabulary (EVo) in diagnosing pediatric anxiety between mental health and non-mental health clinical notes from electronic health records to understand the role of Evo in informing classification and decision-making in anxiety diagnoses. Study design: We conducted a retrospective study using a cohort less than age 25 from Cincinnati Children's Hospital including 897 685 patients with 61 586 446 notes. We analyzed EVo, collected from mental health clinicians, in both mental and nonmental health notes. We compared classification accuracy using EVo-based patient-level embedding from all clinical notes, mental-health notes, and nonmental health notes for 2 tasks: 1) pre-vs postdiagnosis anxiety patients, and 2) prediagnosis anxiety vs nonanxiety patients. Results: EVo usage was highest in prediagnosis anxiety, lower in nonanxiety, and lowest in post-diagnosis. Classification models using EVo features from all, mental-health, and non-mental health notes showed similar F1 scores for prediagnosis anxiety (0.70 ± 0.2 for 2 categories). For anxiety vs nonanxiety classification, all clinical and nonmental health notes had better F1 scores than mental-health notes (above 0.90 for 3 categories). There was a notable difference in class-wise performance across both tasks. Conclusions: There are significant differences in anxiety EVo use between mental health and nonmental health clinicians. Despite less anxiety-specific terminology, non-mental health notes still captured key aspects of patient presentations, emphasizing the importance of including all clinicians' notes in analysis. EVo's utility for anxiety classification is most effective in prediagnostic phases, suggesting the need for a dedicated diagnostic lexicon and further study before incorporating EVo into classification models.

feature engineering↗

DOE OSTI2025

Wastepaper-derived porous carbon supported cobalt nanocomposites for all solid-state flexible supercapacitor

The conversion of wastepaper into high-value carbon materials has gained significant attention as a sustainable strategy for energy storage applications. Owing to its low cost, abundance, and intrinsic fibrous structure, wastepaper serves as an attractive precursor for carbon-based electrode materials. In this work, a novel electrode comprising cobalt nanoparticles and Co 3 O 4 embedded in wastepaper-derived porous carbon has been developed for use in a flexible all-solid-state asymmetric supercapacitor. The integration of cobalt nanoparticles and Co 3 O 4 introduces redox-active centres, which enhance the electrochemical activity of the carbon framework. Mean while, the interconnected porous and conductive carbon network enables rapid ion diffusion and efficient electron transport, synergistically improving the overall electrochemical performance. It delivers a high specific capacitance of 61.5 Fg -1 , a power density of 5143 W kg -1 , and an energy density of 9 Wh kg -1 at a current density of 2.5 A/ g. Furthermore, the device maintains outstanding cycling stability, retaining 82.86 % of its capacitance after 10,000 charge-discharge cycles. Practical applicability is confirmed through its ability to power

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Hierarchical low Pt-loading “core-shell” electrocatalysts for the oxygen reduction reaction in fuel cells

The sluggish kinetics of the oxygen reduction reaction (ORR) hinder cost-effective polymer electrolyte fuel cells (PEFCs), which rely on scarce, expensive platinum-based electrocatalysts (ECs). Here, we present a novel synthesis method for ORR ECs achieving exceptional platinum utilization. The design features a hierarchical “multi-carbon” support comprising carbon nanoparticles interacting with graphene nanoplatelets as the “core”, encapsulated by a porous carbon nitride (CN) “shell”. This configuration promotes strong core/shell interactions and a bimodal active site distribution, consisting of chemically dispersed Pt and Ni single-atom complexes and PtNix alloy nanoclusters embedded in the CN shell. These advantages enable high activity and durability, achieving an ORR activity of 1.6 A mgPt−1 at 0.9 V vs. RHE-an order of magnitude higher than Pt/C (0.17 A mgPt−1). A proof-of-concept PEFC demonstrates a specific power of 12.0 kW gPt−1 at 0.60 V. This approach offers a significant step toward more efficient and sustainable PEFC technologies.

Pagot, Gioele [University of Padova, Italy]↗

DOE OSTI2025

Experimental investigation of the dependence of void nucleation and growth on initial microstructure in high-purity titanium under tension

An experimental investigation of failure mechanisms in relation to the initial microstructure in high-purity titanium samples is presented. The initial microstructure of the specimens was measured in 3D using diffraction-contrast tomography (DCT). Ex-situ X-ray computed tomography (XCT) was used to visualize voids in specimens at various levels of deformation attained by interrupted tensile testing. Electron backscatter diffraction (EBSD) mapping was used to characterize the deformed microstructures per specimen. The investigation showed that the location of failures was unrelated to the formation of the first voids, but rather the nucleation and growth of cracks were from heavily deformed surface regions. The areas surrounding the failure-causing cracks had the highest propensity for void development of any area in the specimen. This facilitated crack propagation through the specimen via “linking up”. The failure of the specimens by microvoid coalescence was bolstered by “dimpled” fracture surfaces. Paint composed of gallium embedded in rubber was used to track the displacement of points along the loading direction of the specimens, to relate the location of failure to the material's initial microstructure. However, the correlation proved difficult, due to complex microstructural evolution involving voids, grain fragmentations, and profuse twinning. Nevertheless, it was shown that necking occurred near the largest grain in the gauge section of the specimens. This is likely caused by the decrease in strength of larger grains, causing strain to concentrate in their vicinity. Here, a comprehensive picture of the failure processes in high-purity titanium under axial loading is presented and discussed in the paper.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Linking microstructure to creep behavior in vertically and horizontally built LPBF Haynes 282 compared with wrought material via θ -projection

Laser Powder Bed Fusion (LPBF) has emerged as a promising route for fabricating intricate geometries in high-performance alloys. Haynes 282 (H282) is a strong candidate for applications such as heat exchangers or engines due to its excellent creep strength and thermal stability; however, the long-term creep behavior of LPBF-processed H282 remains poorly understood. In this study, the θ -projection method is used to analyze and extrapolate the creep behavior of vertically built LPBF, horizontally built LPBF, compared to wrought H282 tested at 816 °C. Vertically built LPBF H282 exhibits the lowest minimum creep rate (MCR), while the horizontally built condition shows a higher MCR comparable to that of wrought H282. Despite these differences, both LPBF conditions exhibit significantly shorter rupture life and reduced rupture strain than the wrought material, with the most severe degradation observed in the horizontal builds, consistent with an earlier onset of tertiary creep and accelerated strain-rate evolution. Microstructural characterization reveals that both LPBF and wrought H282 exhibit abundant twin-related boundary character; however, their grain boundary topologies differ markedly. The wrought alloy contains a higher fraction of low-angle grain boundaries and continuous twin lamellae, whereas the LPBF microstructure is characterized by a suppressed low-angle boundary population and fragmented twin-related boundaries embedded within irregular high-angle grain boundary networks. Fractographic analysis further reveals predominantly intergranular cracking in LPBF H282, accompanied by grain-boundary-decorated carbides, Al 2 O 3 inclusions, and high-aspect-ratio pores. These results demonstrate that grain boundary topology, rather than minimum creep rate alone, plays a critical role in governing creep damage accumulation and rupture behavior in LPBF and wrought H282.

Creep↗

DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Directly resolving surface vs. lattice self-diffusion in iron at the nanoscale using in situ atom probe capabilities

Surface self-diffusion studies on metals under elevated reaction conditions are limited, as it is inherently challenging to unambiguously follow atomic transport across highly-reactive surfaces. Here, quantitative and mechanistic insight into thermally induced atomic transport processes in bcc α-iron at the sub-nanometer level was achieved using isotopic tracer techniques coupled with in situ atom probe tomography (APT) capabilities. Specifically, using a reactor directly connected to the APT, needle-shaped specimens fabricated from epitaxial thin films with an embedded 57 Fe tracer layer were annealed in Ar at 500 °C and 350 °C for 1 hour. Furthermore, the tracer was positioned at various depths in the APT specimen by field evaporation, enabling targeted and simultaneous analysis of lattice and surface diffusion. 57 Fe concentration profiles reveal lattice self-diffusion occurs at 500 °C on the order of ~7 – 9 monolayers, while lattice diffusion is not resolvable at 350 °C. Considerable surface transport was, however, observed at both conditions, where atomic transport over the specimen surface led to the formation of a thin (≤1 nm), isotopically-intermixed layer at the surface. Further, the observed isotopic redistributions at 500 °C were convoluted by additional processes occurring in the subsurface, such as atomic intermixing in correlation with lattice diffusion. However, surface diffusion was determined to be the primary transport process at 350 °C and was thereby quantified. Ultimately, these results demonstrate the significance of surface self-diffusion as a short circuit pathway. More broadly, this approach has the potential to provide detailed insight into (self-)diffusion mechanisms across various materials while targeting site-specific reactions under elevated reaction conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Dual atom catalysts for rapid electrochemical reduction of CO to ethylene

Strong CO adsorption and facile CO dimerization are the key challenges in electrochemical CO2 reduction towards multi-carbon (C2+) products. We recently showed that CoPc immobilized on a single-walled carbon nanotube can selectively reduce CO2 to methanol. This is enabled through molecular strain, which dramatically improves the CO adsorption energy to CoPc, which in turn facilitates methanol formation. We now examine the extended Phthalocyanine (PcEx) dual atom catalyst (DAC), which is intrinsically strained and contains two catalyst centers, making it a candidate for reducing CO to C2+ products. Using Quantum Mechanics (QM), we screened 20 elements embedded in the PcEx, seeking catalysts with weak hydrogen binding, strong CO binding, and facile CO dimerization. We identi>ied Fe, Ru, Co, and Ir as the best performers and subsequently evaluated the entire CO to C2H4 mechanism (9 steps) using each of these elements as catalysts. In terms of limiting potential and overall exergonicity, we identi>ied CoPcEx as the best catalyst, followed by IrPcEx. We then examined the full CO to C2H4 mechanism on the bimetallic IrCoPcEx catalyst using grand canonical QM to obtain the reaction energetics as a function of applied potential. We conclude that the bimetallic IrCoPcEx is most promising for ef>iciently converting CO to ethylene.

Musgrave, Charles B.↗

DOE OSTI2025

Active-noise-induced dynamic clustering of passive colloidal particles

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

Brownian dynamics↗

DOE OSTI2024

Absolute decay counting of 146 Sm with 4π cryogenic microcalorimetry

We present a methodology for absolute activity counting of long-lived isotopes based on cryogenic Decay Energy Spectroscopy. A 146 Sm source was produced at the TRIUMF Laboratory and then processed and purified at Lawrence Livermore National Laboratory, yielding a pure sample. The source was embedded within a 4π thermal absorber coupled to a magnetic microcalorimeter achieving nearly 100% counting efficiency. Experimental uncertainties were studied and modeled, including thermal coupling of the source to the absorber, pulse pile-up, trigger, and event selection efficiencies. Here, the absolute activity of the pure 146 Sm source was measured to better than 1% uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

The fixed probe storage ring magnetometer for the Muon g-2 experiment at Fermi National Accelerator Laboratory

The goal of the FNAL E989 experiment is to measure the muon magnetic anomaly to unprecedented accuracy and precision at the Fermi National Accelerator Laboratory. To meet this goal, the time and space averaged magnetic environment in the muon storage volume must be known to better than 70 ppb. A new pulsed proton nuclear magnetic resonance (NMR) magnetometer was designed and built at the University of Washington, Seattle to track the temporal stability of the 1.45 T magnetic field in the muon storage ring at this precision. It consists of an array of 378 petroleum jelly based NMR probes that are embedded in the walls of muon storage ring vacuum chambers and custom electronics built with readily available modular radio frequency (RF) components. We give NMR probe construction details and describe the functions of the custom electronic subsystems. The excellent performance metrics of the magnetometer are discussed, where after 8 years of operation the median single shot resolution of the array of probes remains at 650 ppb.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗

DOE OSTI2025

Temperature-dependent calibration procedures for the silicon photomultiplier readout of the cosmic ray veto detector for the Mu2e experiment

The cosmic ray veto detector for the Mu2e experiment consists of scintillation bars embedded with wavelength-shifting fibers and read out by silicon photomultipliers (SiPMs). Here, in this manuscript, the calibration procedures of the SiPMs are described including corrections for the temperature dependence of their light yield. These corrections are needed as the SiPMs are not kept at a constant temperature due to the complexity and cost of implementing a cooling system on such a large detector. Rather, it was decided to monitor the temperature to allow the appropriate corrections to be made. The SiPM temperature dependence has been measured in a dedicated experiment and the calibration procedures were validated with data from production detectors awaiting installation at Fermilab.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗