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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
NASA NTRS1990

Characterization of welded HP 9-4-30 steel for the advanced solid rocket motor

Solid rocket motor case materials must be high-strength, high-toughness, weldable alloys. The Advanced Solid Rocket Motor (ASRM) cases currently being developed will be made from a 9Ni-4Co quench and temper steel called HP 9-4-30. These ultra high-strength steels must be carefully processed to give a very clean material and a fine grained microstructure, which insures excellent ductility and toughness. The HP 9-4-30 steels are vacuum arc remelted and carbon deoxidized to give the cleanliness required. The ASRM case material will be formed into rings and then welded together to form the case segments. Welding is the desired joining technique because it results in a lower weight than other joining techniques. The mechanical and corrosion properties of the weld region material were fully studied.

Watt, George William↗
DOE OSTI2026

Physicochemical evolution of uranium nitride kernel microstructure with varying carbon distribution for advanced TRISO fuel forms

Uranium nitride (UN) has emerged as a fuel candidate for advanced nuclear reactor concepts due to its superior uranium density, thermal conductivity, and high melting temperature. However, the fabrication route for converting UO 2 to UN is complex and difficult to standardize. Although the chemistry of this conversion process is well-studied, more insight into the physicochemical dynamics of this conversion using advanced characterization techniques can help further our understanding of this material system. This work leveraged thermogravimetric analysis (TGA), X-ray diffraction (XRD), and nondestructive 3D X-ray computed tomography (XCT) to characterize dynamic microstructural changes in the UO 2 → UCO → UN fabrication pathway for two kernels with a varying carbon distribution in the starting composition. TGA and XRD were used to quantify changes in the mass, density, and chemical composition of the two kernels, while three-dimensional image processing and segmentation of XCT data were used to quantify the volume, surface area, and spatial distribution of features within each kernel for multiple steps along the fabrication pathway. The analysis indicates distinct differences between the two kernels that are correlated to downstream conversion efficiency. In conclusion, this work is among the first to perform 3D quantification of physicochemical evolution during UN conversion, providing quantitative correlation between processing, properties, and expected fuel performance.

Nuclear fuel↗
DOE OSTI2026

Comparison of automated chemical-guided segmentation and human annotation of soil organic matter in X-ray microcomputed tomography imaging in contrasted soil types

Soil organic matter (OM) formation and persistence is strongly influenced by the spatial distribution of organic substrates and microscale soil heterogeneity by dictating OM accessibility to microorganisms. However, traditional size and/or density fractionation techniques disrupt aggregate architecture, eliminating spatial information needed to fully understand intra-aggregate OM distribution. To quantify three-dimensional OM spatial distribution and automate segmentation in X-ray microcomputed tomography (µCT) imaging without human annotation bias, we developed an iodine gas vapor (I2) based staining workflow that eliminates labor-intensive manual annotation while maintaining segmentation accuracy, using aggregates from four taxonomically diverse soils (Xerofluvent, Haploxeroll Sphagnofibrist, Palehumult) with an 8-fold range of soil organic carbon. Human annotation of 10 µCT slices by the experienced and inexperienced annotators resulted in variations up to 3% in the Dice similarity coefficient (DSC), reflecting a degree of inherent subjectivity of manual labeling. Such inconsistencies are expected to compound as the number of manually annotated slices increases. Dual-energy µCT imaging at 33.1 keV (below the iodine (I) K-edge) and 33.2 keV (above the I K-edge) was used to resolve aggregate microstructure following I2 staining. The automated image subtraction pipeline identified OM regions by the I Kedge induced brightness increases, achieving DSC values of 0.58–0.83 relative to an experienced annotator. Sensitivity analyses revealed that the reconstruction alpha value—optimized via the open-source tool TomocuPy—and the 3D registration slice count were the primary determinants of accuracy, providing a novel benchmark for dual-energy soil imaging. The pipeline without GPU acceleration achieved 9.6 to 43.2 times faster than manual annotation. Using GPU-accelerated image post-processing and affine transformation matrices, the pipeline successfully segmented OM elements for large-scale datasets (3232×3232 pixel, 2048 slices) within ~5200 s from raw file acquisition to segmented output. The high-throughput approach enables the quantification of OM spatial distribution across diverse and heterogeneous soil.

Soil microbial biomass↗
NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗
DOE OSTI2023

Porosity evolution in proton irradiated microfine-grained POCO graphite

This work investigated the porosity evolution of POCO ZXF-5Q graphite that has been irradiated by 340 kW, 120 GeV protons inside NT02 target system in Fermilab's NuMI beamline. This POCO graphite has undergone direct bulk dimensional swelling at low dose irradiation and its local microstructural change is still not well-understood during this process. In this work, the (sub-) micrometre scale porosity from six locations across proton beam fluence and temperature gradients have been studied using focused ion beam-scanning electron microscopy (FIB-SEM) tomography. Here, a deep learning-based tomographic image segmentation technique has been established and implemented for porosity segmentation and quantification. It has been found that there is a decrease in the total volumetric percentage of the porosity at proton beam centre (~ 8 – 8.4 vol.%), by comparing to un-irradiated POCO (~ 12 – 13vol.%) and to beam 2σ and 5σ radii (~ 12vol.%). This decrease in porosity volume percentage was found to be caused by the reduction in pores with volumes > 0.1 μm 3 induced by material bulk dimensional swelling at proton beam centre area. The porosity reduction in relation to dimensional change and irradiation creep was discussed among with other contributing factors, and further investigations through well-controlled irradiation experiment are still needed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗
DOE OSTI2023

A Technique for the Quantitative Characterization of Weld Microstructure and Application to Mo Welds

The choice of weld parameters determines the size, shape, and curvature of grains in the fusion zone (FZ) and heat-affected zone (HAZ) of welds while the mechanical properties of the welds are correlated to this microstructure. Here, a new technique to quantitatively evaluate these microstructural characteristics in both zones of welds has been applied to molybdenum gas tungsten arc welds fabricated using different weld parameters. Trends in microstructural characteristics in the FZ and HAZ were evaluated and correlated with changes to heat input, weld speed, and weld technique. The use of this approach showed that a 20 pct decrease in heat input caused a 20 pct decrease in the number of FZ grains with aspect ratios ≥ 4. The orientations of the FZ grain segments as a function of distance from the FZ centerline were significantly affected by the weld speed and its effect on weld pool shape. A 50 pct increase in weld speed caused a 20 pct decrease in grain segments orientated 60 to 90 deg from the normal to the direction of welding. This technique also captured differences in grain sizes and grain size anisotropy in the FZ between welds made with a constant current, pulsed current, and use of a 4-pole-magnetic oscillator.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Evaluation of Stereology for Snow Microstructure Measurement and Microwave Emission Modeling: A Case Study

Reliable microstructure measurement of snow is a requirement for microwave radiative transfer model validation. Snow specific surface area (SSA) can be measured using stereological methods, in which snow samples are cast in the field and photographed in the laboratory. Processing stereology photographs manually by counting intersections of test cycloids with air–ice boundaries reduces the problems in binary segmentation. This paper is a case study to evaluate the repeatability of the manually stereology interpretation by two independent research groups. We further assessed how uncertainty in snow SSA influences simulated brightness temperature(TB) driven by the Microwave Emission Model of Layered Snowpacks (MEMLS), and how stereology compares to Near Infrared (NIR) camera and hand lens. Data was obtained from two alpine snow profiles from Steamboat Springs, Colorado. Results showed that stereological SSA values measured by two groups are highly consistent, and the ground radiometer measured TBat 19 and 37 GHz was successfully predicted (RMSE<3.8 K);simulations using NIR SSA and hand-lens geometric grain size (Dg)measurements have larger errors. This conclusion was not sensitive to uncertainty in the free parameters of TB modeling.

Microwave radiometry↗
NASA NTRS1977

M551 metals melting experiment

Electron beam welding studies were conducted in the Skylab M551 metals melting experiment, on three different materials; namely 2219-T87 aluminum alloy, 304L stainless steel, and commercially pure tantalum (0.5 wt % columbium). Welds were made in both one gravity and zero gravity (Skylab) environments. Segments from each of the welds were investigated by microhardness, optical microscopy, scanning microscopy, and electron probe techniques. In the 2219-T87 aluminum alloy samples, macroscopic banding and the presence of an eutectic phase in the grain boundaries of the heat affected zone were observed. The stainless steel samples exhibited a sharp weld interface and macroscopic bands. The primary microstructural features found in the tantalum were the presence of either columnar grains (ground base) or equiaxed grains (Skylab). The factors contributing to these effects are discussed and the role of reduced gravity in welding is considered.

Busch, G.↗
DOE OSTI2025

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Unveiling the interaction of nanopatterned void superlattices with irradiation cascades

Nanopatterned microstructures in materials can have a profound impact on materials’ physical and chemical properties. While voids are typically considered as detrimental defects in irradiated materials, the patterning of nanoscale voids causes the formation of void superlattices and provides a highly efficient mechanism for gas storage. Despite the important applications of nanopatterned defect superlattices, how they degrade under irradiation remains unclear. Here we provide direct observation of the evolution of void superlattices under irradiation and elucidate the interaction of void superlattices with irradiation cascades. We reveal that the instability of void superlattices under irradiation is caused by heterogenous void shrinkage and demonstrate the imperative role of mixed 1D/3D diffusion of self-interstitial atoms and injected inert gas atoms on void shrinkage and void superlattice instability. Understanding the degradation mechanisms of nanopatterned microstructures is essential to designing damage-tolerant materials and broadening their applications in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite

Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young’s modulus of the three graphite grades and display the same trends as IBMs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

Developing A Contoured Deposition Head for In-Situ Tape Laying and Fiber Placement

A conformable compaction system employing three individual compactors has been designed for integration into fiber placement and tape laying deposition heads for out-of-autoclave fabrication of thermoplastic contoured parts. The compactors are intended to perform against two geometry specifications: (1) a general minimum radius of curvature limit of 180cm (71-in), and (2) a pad-up specification with a maximum height of 2.5mm (0.1-in) and a minimum ramp of 2.5mm (1-in). The mirrored specification is applicable to a pan-down. The three designs include a hot line compactor capable of a 1000N (400-lb) force at 450C over a 114mm (4.5-in) width, a hot area compactor capable of a 400N (100-lb) force at 450C over a 114mm width by 76mm length (4.5-in by 3-in), and a cold compactor that combines the features of a line and an area compactor. The cold compactor s line segments act with a 2800N (700-lb) force across a 127mm (5-in) width, while the cold compactor's area segments act with a 1000N (250-lb) force over a 127mm by 102mm (5-in by 4-in) area. Two of the designs, the hot line and hot area compactors, have been constructed, developed, and proven out in hot mode to compact actual thermoplastic composite plies over undulating geometry. IM-7PEEK [0/90/0/90]s pan-down and IM-7PEEK [0/-45/90/45]2s pad-up laminates have been fabricated and photomicrographs show good microstructure.

Lamontia, Mark A.↗
DOE OSTI2022

Controlled compositional gradients of electroformed gold and silver

Motivated by an interest in high-pressure research, thick (>1 mm) compositionally graded gold/silver (Au/Ag) films were electroformed. Systematic studies were performed to understand the role of processing temperature on the nucleation and growth kinetics and associated microstructure. Furthermore, as the electrolyte composition is continuously changing during the experiment, systematic studies were performed to correlate electrochemical parameters with film morphology and composition. In this work, the results showed that the nucleation pathways and relative deposition rate of Au and Ag are heavily dependent on the processing temperature. A procedure to ramp the temperature while continuously pumping an Au electrolyte into an initial Ag electrolyte to produce the graded film is presented. The obtained film is comprised of a segment of pure Au followed by a complete compositional gradient and ending with a segment of pure Ag across 1.5 mm. The results presented here describe a general framework to fabricate gradients of other materials through electrodeposition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mechanical Test Results and Microstructural Characterization of the Harvested and Baseline Archival Zion RPV Materials

The decommissioning of the Zion Units 1 and 2 Nuclear Generating Station in Zion, Illinois, presented a unique opportunity for developing a better understanding of materials degradation and other issues associated with extending the lifetime of existing nuclear power plants (NPPs) beyond 60 years of service. In support of extended service and current operations of the US nuclear reactor fleet, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Office of Nuclear Energy, Light Water Reactor Sustainability (LWRS) Program, coordinated with Zion Solutions, LLC, a subsidiary of Energy Solutions (ES), the selective procurement of materials, structures, and components, from the decommissioned reactors including multiple segments of the Zion Unit 1 Reactor Pressure Vessel (RPV).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

In-situ Imaging of Pyrolyzing Aerospace Materials

Tracking morphological changes of materials during heating is crucial to understand its response in fire protection, biofuel production, thermal protection systems (TPS) for hypersonic flight. As materials are heated, they undergo physical and chemical changes due to water loss, stretching or shrinking, pyrolysis and chemical reactions in the ambient environment. The effects of these changes can have a profound impact on the material’s performance, indicated by changes in on the porosity and volume. While materials such as wood shrink as they pyrolyze and lose mass, others swell due to their inherent characteristics when exposed to heat [1]. This study focuses on experiments conducted at the Advanced Light Source (ALS) beamline 8.3.2, where in situ micro-computed tomography (µ-CT) is performed on materials as they are being pyrolyzed. Through in situ µ-CT, the change in total volume and porosity can be obtained in real-time, allowing for better understanding of the underlying thermophysical and chemical processes as a function of temperature. This study also focuses on the implementation of the Porous Microstructure Analysis software (PuMA) [2] to obtain thermal conductivity, permeability, and other properties of the material from the 3D tomographies. The information gained from these tomographies will supplement microscale model development of material morphological change and will aid macroscale modeling for high-temperature applications. For this study, Room Temperature Vulcanizing silicone (RTV) [3-5] is heated from room temperature to 1000°C using an infrared lamp heating system, and tomographies are continuously collected as the sample is heated. The tomographies are then segmented to obtain solid and void phases, from which estimates of pore size, porosity and total volume are extracted as a function of temperature. PuMA is deployed on the segmented tomographies to obtain thermal conductivity, permeability, and other properties as a function of temperature. Preliminary results show that RTV first intumesces (swells) as pyrolysis begins, due to build-up of pyrolysis gases in closed pores, and then shrinks significantly as more open pores are formed and the pyrolysis gases outgas. Pore network visualization of the tomographies using OpenPNM [6] showed the increase in pore connectivity with increase in temperature. Future work will focus on using PuMA to obtain macroscopic properties of RTV as a function of temperature.

Tomography↗