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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

EDS-PhaSe: Phase Segmentation and Analysis from EDS Elemental Map Images Using Markers of Elemental Segregation

Scanning electron microscopy (SEM), combined with energy-dispersive spectroscopy (EDS), is an extensively used technique for in-depth microstructural analysis. Here, we present the EDS-Phase Segmentation (EDS-PhaSe) tool that enables phase segmentation and phase analysis using the EDS elemental map images. Importantly, it converts the EDS map images into estimated composition maps for calculating markers of selective elemental redistribution in the scanned area and creates a phase-segmented micrograph while providing approximate fraction and composition of each identified phase. EDS-PhaSe offers two unique advantages. Firstly, it enables the direct processing of EDS elemental map images without requiring any raw or proprietary data/software, thereby allowing the analysis of EDS results available in the published literature as images. Secondly, it enables segmentation and analysis of phases even when the phase contrast is missing in backscattered micrographs, assisting in correlating the XRD and SEM-EDS data as shown in this work for a AlCoCrFeNi high-entropy alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Characterization and Quantification of Radiation-Induced Clusters/Precipitates in RPV Steels Using STEM-EDS and Machine Learning

Over the operational lifespan of a nuclear reactor, reactor pressure vessel (RPV) steels are subjected to significant neutron irradiation, resulting in complex microstructural changes and the consequent degradation of mechanical properties. Various physically motivated correlation models have been developed to predict neutron irradiation-induced embrittlement of RPVs under different irradiation conditions. However, the efficient and accurate characterizations and quantification of radiation-induced clusters in RPVs are still challenging, which will affect the precision of the predictive models for embrittlement of RPV components. In the DOE Visiting Faculty Program (VFP) research work at Oak Ridge National Lab (ORNL), I integrate machine learning to aid Scanning Transmission Electron Microscopy – Energy Dispersive X-ray Spectroscopy (STEM-EDS) analyses, which improve the characterization and quantification of radiation-induced clusters in RPV steels, thereby enabling more accurate predictions of material behavior under irradiation. The surveillance base- and welded- RPV steels were annealed at various temperatures of 340 °C, 450 °C and 500 °C for up to 168 hours, respectively. Afterwards, I have characterized radiation-induced clusters using advanced STEM-EDS techniques and subsequently applying machine learning algorithms to analyze and refine STEM-EDS datasets, enhancing the quantification of clusters compositions and distributions. In the end, an efficient workflow for integrating STEM-EDS data analysis with machine learning to address challenges including noise reduction has been developed. The completion of this VFP work will support bridge critical gaps in the accurate quantification of radiation-induced clusters in RPV steels using STEM-EDS and support the development of more precise models for predicting RPV embrittlement in the Light Water Reactor Sustainability program supported by Department of Energy and enhancing the collaboration between ORNL and Alred University. The outcome of the VFP project will leverage a few research papers submission to peer-reviewed journals in the relevant scientific field and a few oral presentations at national and international conferences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cluster Analysis of Combined EDS and EBSD Data to Solve Ambiguous Phase Identifications

A common problem in analytical scanning electron microscopy (SEM) using electron backscatter diffraction (EBSD) is the differentiation of phases with distinct chemistry but the same or very similar crystal structure. X-ray energy dispersive spectroscopy (EDS) is useful to help differentiate these phases of similar crystal structures but different elemental makeups. However, open, automated, and unbiased methods of differentiating phases of similar EBSD responses based on their EDS response are lacking. This paper describes a simple data analytics-based method, using a combination of singular value decomposition and cluster analysis, to merge simultaneously acquired EDS + EBSD information and automatically determine phases from both their crystal and elemental data. I use hexagonal TiB 2 ceramic contaminated with multiple crystallographically ambiguous but chemically distinct cubic phases to illustrate the method. Code, in the form of a Python 3 Jupyter Notebook, and the necessary data to replicate the analysis are provided as Supplementary material.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Myco-Ed: Mycological curriculum for education and discovery

Fungi are important and hyperdiverse organisms, yet chronically understudied. Most fungal clades have no reference genomes, impeding our understanding of their ecosystem functions and use as solutions in health and biotechnology. Also, opportunities for training in fungal biology and genomics are lacking, creating a bottleneck that hinders the recruitment and cultivation of a talented future mycological workforce. To address these issues, we developed Myco-Ed, an educational program offering training and scientific contributions through genome sequencing and analysis. Myco-Ed empowers students to pursue careers in fungal biology while improving fungal resources. Myco-Ed has been piloted at 12 institutions (15 classrooms) ranging from online e-Campuses to R1 universities, resulting in hundreds of fungal observations and many new high-quality reference genomes.

Branco, Sara↗
DOE OSTI2024

Report of Viscosity Measurements on Reaction Simulant and 2-(methylamino) ethanol carbamate (NMEA carbamate) for the Explosives Destruction System (EDS) P3 System

The reaction products for the proposed chemistry for phosgene treatment in the Explosive Destruction System (EDS) are viscous. This will affect the time required to drain the EDS vessel. Viscosity measurements were made on two samples and the results for one sample have been fit to curves.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Investigation of Anomalous Thread Wear in EDS Vessels

Potential causes of anomalous thread wear observed on EDS system fasteners were investigated using the V25 two-piece clamped vessel as a test bed. Thread wear and metal particulate were analyzed across operational conditions. Despite intensive testing, galling wear was not triggered, reducing uncertainty about design tolerances, material selection, and environmental factors. Minimum service life benchmarks were established for two-piece clamp fasteners under normal EDS conditions.

42 ENGINEERING↗
DOE OSTI2024

Atomic-Scale Characterization of Dilute Dopants in Topological Insulators via STEM–EDS Using Registration and Cell Averaging Techniques

Magnetic dopants in three-dimensional topological insulators (TIs) offer a promising avenue for realizing the quantum anomalous Hall effect (QAHE) without the necessity for an external magnetic field. Understanding the relationship between site occupancy of magnetic dopant elements and their effect on macroscopic property is crucial for controlling the QAHE. By combining atomic-scale energy-dispersive X-ray spectroscopy (EDS) maps obtained by aberration-corrected scanning transmission electron microscopy (AC-STEM) and novel data processing methodologies, including semi-automatic lattice averaging and frame registration, we have determined the substitutional sites of Mn atoms within the 1.2% Mn-doped Sb 2 Te 3 crystal. More importantly, the methodology developed in this study extends beyond Mn-doped Sb 2 Te 3 to other quantum materials, traditional semiconductors, and even electron irradiation sensitive materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The effect of temperature and burnup on U-10Zr metallic fuel chemical interaction with HT-9: A SEM-EDS study

The fuel cladding chemical interaction (FCCI) between Uranium-Zirconium-based metallic fuel and cladding materials during in-pile service is one of the most constraining phenomena affecting the performance of this fuel system. In this study, we investigated the effect of temperature and burnup on the FCCI development in two U-10 wt.% Zr (U-10Zr) fuel samples with HT-9 cladding irradiated as part of the MFF-3 irradiation test in the Fast Flux Test Facility (FFTF). One sample achieved a burnup of 13.1 at.% and operated with an average inner cladding temperature of 530°C, while the other achieved a burnup of 8.5 at.% and was subjected to an average inner cladding temperature of 615°C. Automated scanning electron microscopy (SEM) back-scattered electron (BSE) imaging of entire fuel cross-sections and SEM energy dispersive x-ray spectroscopy (EDS) analysis on specific fuel-cladding interface regions successfully provided a comprehensive characterization of the depth and type of interaction happening under different irradiation conditions. Further, our analysis shows that FCCI development on both fuel and cladding side is strongly influenced by the inner cladding temperature and, to some extent, the formation and integrity of Zr-rich layers between the fuel and cladding, while the impact of burnup and power is negligible. Measured FCCI thicknesses were compared to BISON simulations using both an empirical model based upon legacy data from the Experimental Breeder Reactor II (EBR II) irradiations and a mechanistic model currently under development for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, showing satisfactory agreement. Nonetheless, this comparison supports the need for additional microstructural characterization in intermediate ranges of temperature, power, and burnups in prototypic-length pins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Correlated 4D-STEM and EDS for the classification of fine Beta-precipitates in aluminum alloy AA 6063-T6

Tuning the properties of aluminum alloys AA 6063-T6 involves artificial aging to induce precipitate formation, particularly β’’ and β’ phases. Previous characterization challenges due to their similar appearance are addressed here by correlating 4D scanning transmission electron microscopy (4DSTEM) and energy-dispersive spectroscopy (EDS) mapping. This approach allows us to analyze the structure and composition of precipitates individually, overcoming limitations of conventional imaging and structural analysis techniques when the precipitates appear simultaneously, as is often the case. We present detailed characterizations of needle-shaped Beta precipitates, revealing distinct diffraction patterns (DPs) and compositional differences. The method's applicability extends beyond aluminum alloys, offering a promising strategy for complex composite material characterization with multimodal scanning transmission electron microscopy (STEM) techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗
DOE OSTI2026

Inter-year Variability in EDS Standards

This report provides a deep dive into how the stability of energy dispersive spectroscopy (EDS) standards yielded insight into the shortfalls of using software to randomly select points for spectral acquisition when using heterogeneous standards. Some procedural recommendations are included which are meant to minimize the impact of anomalous reference standard spectra by detecting them before the standard is implemented into data processing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

EDS Analysis of FCCI in AFC-FAST Fuel Pins

The Advanced Fuel Campaign’s Fission Accelerated Steady-state Testing (FAST) program uses metallic fuel pins with small diameters to reach a desired burnup more quickly. This enables accelerated testing of advanced fuel designs and decreases the time between idea conception and commercial usage. Post-irradiation examination is critical in this process, especially with respect to the fuel-cladding chemical interactions (FCCI). In this work, energy dispersive X-ray spectroscopy (EDS) is used to track how elements from the fuel and fission products have diffused through the cladding. Elemental redistribution along the fuel-cladding interface is mapped and FCCI region thicknesses are measured. The correlations between geometry, temperature, burnup, and FCCI thickness are presented.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Cross-section SEM-EDS Analysis of Corroded 316 Steel Samples Using JEOL 6610 SEM

Comparison of SEM images obtained for samples 316H-1, 5, 7, and 10 revealed that samples 1 and 5 were subjected to more corrosion than the other two samples. Pores of an average of 1µm size were also observed scattered near the edge of each sample. Corrosion layer thickness was measured from edge of the corroded surface to the pore region. It was found that 316H-1 and 316H-5 had more corrosion damage with 82.40µm and 100µm respectively. Sample 316H-5 posed a challenge in measuring the corrosion layer thickness due to it breaking off from the parent sample during polishing. Samples 316H-7 and 316H-10 are less corroded with 26.57µm and 39.94µm thickness respectively.

36 - MATERIALS SCIENCE↗