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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Non-Gaussian photonic state engineering with the quantum frequency processor

Non-Gaussian quantum states of light are critical resources for optical quantum information processing, but methods to generate them efficiently remain challenging to implement. Here we introduce a generic approach for non-Gaussian state production from input states populating discrete frequency bins. Based on controllable unitary operations with a quantum frequency processor, followed by photon-number-resolved detection of ancilla modes, our method combines recent developments in both frequency-based quantum information and non-Gaussian state preparation. Leveraging and refining the K-function representation of quantum states in the coherent basis, we develop a theoretical model amenable to numerical optimization and, as specific examples, design quantum frequency processor circuits for the production of Schrödinger cat states, exploring the performance tradeoffs for several combinations of ancilla modes and circuit depth. Our scheme provides a valuable framework for producing complex quantum states in frequency bins, paving the way for single-spatial-mode, fiber-optic-compatible non-Gaussian resources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Seascape genomics of eastern oyster ( Crassostrea virginica ) along the Atlantic coast of Canada

Abstract Interactions between environmental factors and complex life‐history characteristics of marine organisms produce the genetic diversity and structure observed within species. Our main goal was to test for genetic differentiation among eastern oyster populations from the coastal region of Canadian Maritimes against expected genetic homogeneity caused by historical events, taking into account spatial and environmental (temperature, salinity, turbidity) variation. This was achieved by genotyping 486 individuals originating from 13 locations using RADSeq. A total of 11,321 filtered SNPs were used in a combination of population genomics and environmental association analyses. We revealed significant neutral genetic differentiation (mean F ST = 0.009) between sampling locations, and the occurrence of six major genetic clusters within the studied system. Redundancy analyses (RDAs) revealed that spatial and environmental variables explained 3.1% and 4.9% of the neutral genetic variation and 38.6% and 12.2% of the putatively adaptive genetic variation, respectively. These results indicate that these environmental factors play a role in the distribution of both neutral and putatively adaptive genetic diversity in the system. Moreover, polygenic selection was suggested by genotype–environment association analysis and significant correlations between additive polygenic scores and temperature and salinity. We discuss our results in the context of their conservation and management implications for the eastern oyster.

Bernatchez, Simon↗
DOE OSTI2021

Characteristics of thermospheric infrasound predicted using ray tracing and weakly non-linear waveform analyses

Infrasonic signals refracted by thermal gradients in the rarefied upper atmosphere are modeled using a combination of ray tracing and weak shock theory to develop an understanding of thermospheric infrasound signals produced by energetic, transient sources. Canonical arrival structures in the form of u-wave signatures are identified for returns refracted at lower altitudes within the thermosphere, and possible multi-pathing produced by effective sound speed inflections are investigated to elucidate more complex arrival structures, which are found to be spatially localized. Furthermore, variability in the source characteristics is investigated and it is found that whereas some waveform phase information is lost due to finite amplitude effects, arrival characteristics are strongly dependent on the peak overpressure near the source. Variability in the propagation path is considered using archived atmospheric specifications and implies that despite uncertainties related to the dynamic and sparsely sampled nature of the atmosphere, thermospheric signatures might be useful in estimating the yield for explosive sources. Last, thermospheric arrivals from a failed rocket launch, as well as those from several large chemical explosions, are analyzed and it is found that qualitative trends match those predicted, and analyses here provide additional insight into such signatures.

42 ENGINEERING↗
DOE OSTI2025

COBRA:COMPUTED-TOMOGRAPHY BASED RANDOM-FIELD APPROXIMATION

SF-25-115 COBRA (COmputed-tomography Based Random-field Approximation) is a Python application for generating statistically equivalent random fields from CT-scan imagery. It leverages Karhunen–Loève expansions to model microstructural variability, enabling users to: Preprocess CT scans (filtering and Gaussian transformation); Fit covariance kernels fromempirical data; Solve eigenproblems to obtain KL modes; Sample random fields onsistent with fitted statistics; Postprocess samples back into the physical domain.

Hu, Tianchen↗
DOE OSTI2019

Evaluating Large-Eddy Simulations of Boundary-Layer Cloud Response to Climate Change using MAGIC Observations

Over the cool waters off California, a persistent and extensive deck of low-lying clouds forms atop a shallow, turbulent layer of moist air extending 500-2000 meters above the ocean, above which the air is much warmer and drier. Its west edge varies with weather and season and is typically half way to Hawaii. This cloud deck and similar cloud decks elsewhere reflect sunlight back to space, cooling the underlying ocean and indeed the entire planet. They must be accurately represented by a climate model to correctly simulate our current climate or future global warming. Most climate models suggest these cloud decks will thin and break up in a warmer CO 2 -enriched climate, so extra sunlight would reach the ocean surface and amplify warming worldwide. But these models have difficulty accurately simulating the cloud thickness and extent because the turbulent cloud-forming air currents are much too small to be simulated by their coarse computational grid. In 2012-2013, the DOE Atmospheric Radiation Measurement MAGIC program instrumented a container ship transiting between California and Hawaii to observe clouds and rain, small particles (aerosols), and weather conditions. Data were obtained from 20 4-6 day cruises in each direction. This study tested whether a sophisticated ‘large-eddy simulation’ (LES) of the turbulent air motions that create the clouds in this region accurately predicts the variations in cloud properties seen across the different cruises. If so, that model is more believable for predicting cloud changes in this region in a future warmer climate. Our LES used a numerical mesh over a 6.4x6.4 km region with 50 m horizontal and 5 m vertical grid spacing to simulate the cloud-forming eddies and the sharp overlying transition between moist and dry air. To better compare with MAGIC observations, we configured our model to simulate a region that moved along with the ship. We used a weather forecast model to specify effects of the large-scale air flow. We compared our results with balloon ascents, a radar and other instruments pointed upward at the clouds, measurements of downward sunlight and infrared radiation, aerosols, and weather variables for all suitable cruise periods. Our LES was remarkably skillful in predicting the cloudiness variations measured by the ship. MAGIC also sampled mesoscale cells, regions of cloud thickening and thinning over distances of 10-50 km. An LES run over a larger region 100 km on a side shows these cells form spontaneously, enhanced by strong radiative heat loss at the cloud tops.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Elucidating Arsenic and Selenium Speciation in Coal Fly Ashes

Coal fly ash (CFA) is produced during the coal combustion process and contains trace elements (<100 ppm) including selenium (Se) and arsenic (As), both detrimental for environmental and human health. Existing management strategies for CFAs involve disposal in landfills and ash ponds, as well as beneficial usage in other applications such as in concrete. Both the direct disposal and beneficial usage of CFA raise concerns for environmental hazards due to the potential leaching of Se and As. CFAs were classified as reusable material by the U.S. Environmental Protection Agency (EPA) with the first federal regulation (Disposal of Coal Combustion Residuals from Electric Utilities, CCR) for its disposal established six years ago. During coal combustion process, parameters such as furnace firing type, emissions controls, coal rank, use of additives, and particulate matter controls, could contribute to significant variability in As/Se concentrations and their speciation. Although there have been a handful of studies on As/Se speciation on small sets of samples, they do not fully represent the current state of coal-fired electrical generating units. Little information exists on the detailed speciation (e.g. oxidation state, complexation state) of As/Se in large set of fly ash samples. To better investigate the role of the potential contributing parameters, a large-scale survey study with representative samples of typical coal source and combustion conditions is highly desired. The overall goal of this research is to systematically characterize As and Se speciation of representative coal fly ash samples using state-of-the-art synchrotron based spectroscopic and microscopic techniques, in order to develop a correlation between coal source/type, operation condition, As/Se speciation, and As/Se mobility. A detailed survey study was conducted documenting the current state-of-knowledge on fossil power generating units as a function of coal type/source, operating conditions, environmental control systems, additive use, and fly ash handling methods. Based on this survey, a matrix of fly ash samples representing a range of conditions were chosen and collected. The collected ash samples were analyzed for bulk characteristics such as elemental composition, microstructure, chemical and mineralogical composition, surface area, and particle size distribution. State-of-the-art synchrotron X-ray microscopy and spectroscopy techniques were applied to reveal the molecular scale speciation information of As and Se, such as oxidation state, association with other elements/minerals, and complexation states.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Rapid microbial growth in the early phase of plant litter decomposition is viewed as an important component of soil organic matter (SOM) formation. However, the microbial taxa and chemical substrates that correlate with carbon storage are not well resolved. The complexity of microbial communities and diverse substrate chemistries that occur in natural soils make it difficult to identify links between community membership and decomposition processes in the soil environment. To identify potential relationships between microbes, soil organic matter, and their impact on carbon storage, we used sand microcosms to control for external environmental factors such as changes in temperature and moisture as well as the variability in available carbon that exist in soil cores. Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase litter decomposition, we found that protein- and tannin-like compounds exhibited the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins correlated positively with DOC concentration, while tannins correlated negatively with DOC. Through random forest, neural network, and indicator species analyses, we identified 42 bacterial and 9 fungal taxa associated with DOC concentration. The majority of bacterial taxa (26 out of 42 taxa) belonged to the phylum Proteobacteria while all fungal taxa belonged to the phylum Ascomycota. Additionally, we identified significant connections between microorganisms and protein-like compounds and found that most taxa (12/14) correlated negatively with proteins indicating that microbial consumption of proteins is likely a significant driver of DOC concentration. This research links DOC concentration with microbial production and/or decomposition of specific metabolites to improve our understanding of microbial metabolism and carbon persistence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Environmental DNA Detection in Marine Macrophyte Ecosystems as a Potential Blue Carbon Source in Sediments

“Blue carbon” refers to the carbon sequestered by the world’s oceanic and coastal ecosystems, particularly through coastal vegetation such as mangroves, salt marshes, seagrasses, and marine macroalgae. These ecosystems play a crucial role in the global carbon cycle by serving as significant carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in biomass and sediments over long periods. This study explores the use of environmental DNA (eDNA) to detect marine macrophytes and microalgae assemblages contributing to blue carbon in sediments across various coastal ecosystems. The research addresses the challenges of traditional monitoring methods by utilizing high-throughput sequencing of the 18S-V9 region amplified using eDNA from sediment samples collected at eight locations in the United States and South Korea. The results reveal a diverse array of taxa, underscoring the variability in community composition across different conditions. Notably, sites with seagrass beds and Ulva blooms showed distinct patterns in microalgal community structure. This study underscores the potential of eDNA analysis in providing comprehensive insights into the biodiversity of marine macrophyte ecosystems, thus informing conservation efforts and enhancing the understanding of marine ecological dynamics.

Xing, Qikun (ORCID:0000000206179027)↗
DOE OSTI2019

Geometric Estimation of Multivariate Dependency

This paper proposes a geometric estimator of dependency between a pair of multivariate random variables. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate samples. This estimator converges to a quantity that we call the geometric mutual information (GMI), which is equivalent to the Henze–Penrose divergence. between the joint distribution of the multivariate samples and the product of the marginals. The GMI has many of the same properties as standard MI but can be estimated from empirical data without density estimation; making it scalable to large datasets. The proposed empirical estimator of GMI is simple to implement, involving the construction of an minimal spanning tree (MST) spanning over both the original data and a randomly permuted version of this data. We establish asymptotic convergence of the estimator and convergence rates of the bias and variance for smooth multivariate density functions belonging to a Hölder class. We demonstrate the advantages of our proposed geometric dependency estimator in a series of experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Probabilistic Evaluation of Geomechanical Risks in CO2 Storage: An Exploration of Caprock Integrity Metrics Using a Multilaminate Model

The probabilistic uncertainty assessment of geomechanical risk—specifically, caprock failure—attributable to CO2 injection, as presented in a simplified hypothetical geological model, was the focus of this study. Our approach amalgamates the implementation of a multilaminate model, the creation of a response surface model in conjunction with the Box–Behnken sampling design, the execution of associated numerical modeling experiments, and the utilization of Monte Carlo simulations. Probability distributions to encapsulate the inherent variability (elastic and mechanical properties of the caprock and reservoir) and uncertainty in prediction estimates (vertical displacement, total strain, and F value) were employed. Our findings reveal that the Young modulus of the caprock is a key factor controlling equivalent total strain but is insufficient as a stand-alone indicator of caprock integrity. It is confirmed that the caprock can accommodate significant deformation without failure, if it possesses a low Young’s modulus and high mechanical strength properties, such as the friction angle and uniaxial compressive strength. Similarly, vertical displacement was found to be an unreliable indicator for caprock integrity, as caprock failure can occur across a broad spectrum of vertical displacements, particularly when both the Young modulus and mechanical strength properties have wide ranges. This study introduces the F value as the most dependable indicator for caprock failure, although it is a theoretical attribute (the shortest distance between the Mohr circle and the nearest failure envelope used to measure the sensitivity to failure) and not physically measurable in the field. Deviatoric stress levels were found to vary based on stress regimes, with the maximum levels observed under extensive and compressive stress regimes. In conjunction with the use of the response surface method, this study demonstrates the efficacy of the multilaminate framework and the Mohr–Coulomb constitutive model in providing a simplified, yet effective, probabilistic model of the mechanical behavior of caprock failure, reducing mathematical and computational complexities.

Energy & Fuels↗
DOE OSTI2025

Modeling neutral defects in III-V ternary alloys with a special quasirandom structure: Analysis of As- and III-site point defects in InGaAs

While first-principles density functional theory modeling has become a vital tool to investigate defect properties in semiconductors, the lack of crystalline periodicity in pseudobinary random composition alloys, such as In 1−𝑥 ⁢Ga 𝑥 ⁢As, complicates such analyses. We present a simulation strategy to systematically take into account the variability in the local defect environment in order to predict statistical properties of neutral intrinsic defects in In 1−𝑥⁢ Ga 𝑥 ⁢As. We use a comprehensive sampling from a modest-sized 64-atom special quasirandom structure (SQS) to define a statistically representative set of defects, and use a 512-atom hypercell, a 2 × 2 × 2 supercell of SQS supercells, to achieve cell-size convergence. We articulate an equivalent site principle and describe how it constrains atomic chemical reference energies in computation of defect formation energies in pseudobinary alloys. A simple protocol for estimating reference energies for the Ga and In atoms sharing the III site succeeds in obtaining the equivalence of defects at Ga-sites and In sites in the SQS supercell, (<30 meV differences in average formation energies). For III-site defects, such as the As antisite As III , the statistical variability in formation energies is modest, ≈ 0.1–0.2 eV. The variability in formation energy at As-site defects, such as the As vacancy 𝑣 As , can be much larger, >1 eV. The As antisite is shown to be a low-energy defect and the most likely to be present in as-grown materials, just as in GaAs. All other defects are higher-energy defects unlikely to be important in native material, but potentially important in radiation-damaged material. With a strong variability in defect energies, especially on the As-site, explicit consideration of statistical variability due to compositional randomness will be imperative for meaningful and quantitative comparisons to experiment.

Density functional theory↗
DOE OSTI2025

Surface water and groundwater FTICR-MS, NPOC, and TN from nine wetlands and three upland wells at the Tanglewood Biological Station, Alabama

This dataset supports a broader study examining wetland hydrobiogeochemical responses to flood disturbance and the subsequent impacts on watershed nutrient export. The study was designed following ICON (integrated, coordinated, open, and networked) principles. Samples were collected from nine wetlands and three upland wells at the Tanglewood Biological Station, Alabama in August 2024 and February 2025, during the dry and wet season, respectively. The contents include geochemistry (dissolved organic carbon measured as non-purgeable organic carbon; total dissolved nitrogen) and organic matter characterization (FTICR-MS). Related water level data from the same locations can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253. Additional geochemistry will be published in a separate data package. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; (7) the field protocol; and (8) a subfolder with sample data. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total nitrogen data and averages; (3) methods codes; and (4) a subfolder of 12 Tesla (12T) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Characterized Variability of Biomass Feedstocks using The Idaho National Lab Bioenergy Feedstock Library

In order to achieve the Bioenergy Technology Office Goals of acquiring a billion tons of feedstock material that meets the physical, chemical, and cost requirements for conversion to fuel by 2030, research into understanding the overall causes of compositional, physical and conversion variability for the wide number of available biomass feedstock resources is necessary. One strategy for accomplishing this is the innovative knowledge-based management system currently being developed and maintained at Idaho National Laboratory (INL) known as the Bioenergy Feedstock Library (www.bioenergylibrary.inl.gov). The library currently has harvest, storage and logistic, analytical characterization, and/or conversion data for over 35,000 samples spanning 90 different feedstock types, 38 states, and 3 countries. These samples and data have been provided not only by the INL but from over 100 collaborating universities, feedstock supplier, national labs, and industrial partners. Of the 35,000 samples, 2300 have been characterized by one or more analytical processes including the compositional, proximate, ultimate, elemental ash, physical and conversion analyses. This presentation will demonstrate the significant research into the national understanding of biomass feedstock variability made possible by the continually updated contributions to the library that have historically only been available in the few published review papers regarding feedstock variability. Also, the benefits of contributing to this database, the analytical tools available, and the future prospects that this tool can provide research supporting sustainable and renewable energy will be presented.

09 BIOMASS FUELS↗
DOE OSTI2022

Sources and Variability of Nitrate on an Alaskan Hillslope Dominated by Alder Shrubs, Kougarok, Alaska, 2017 and 2018

Data provided include results of analyses of soil pore-water, soil moisture, and leaf litter samples collected at a Kougarok Hillslope site dominated by alder shrubs (KG_MM64) in the Seward Peninsula, Alaska during July and September 2017 and 2018. Samples were from surface soils in close proximity to 5 alder patches, collected upslope, within, and downslope of the alder patches. Pore water was analyzed for a comprehensive set of anions, cations, elemental analyses, and oxygen and nitrogen isotopes. Soil samples were collected for soil moisture determination. Leaf litter extracts were analyzed for carbon and nitrogen content and carbon and nitrogen isotopes. This dataset contains 3 *.csv files and 1 *.pdf file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Probing the Origin of Changing-look Quasar Transitions with Chandra

Extremely variable quasars can also show strong changes in broad-line emission strength and are known as changing-look quasars (CLQs). To study the CLQ transition mechanism, we present a pilot sample of CLQs with X-ray observations in both the bright and faint states. From a sample of quasars with bright-state archival SDSS spectra and (Chandra or XMM-Newton) X-ray data, we identified five new CLQs via optical spectroscopic follow-up and then obtained new target-of-opportunity X-ray observations with Chandra. No strong absorption is detected in either the bright- or the faint-state X-ray spectra. The intrinsic X-ray flux generally changes along with the optical variability, and the X-ray power-law slope becomes harder in the faint state. Large-amplitude mid-infrared variability is detected in all five CLQs, and it echoes the variability in the optical with a time lag expected from the light-crossing time of the dusty torus for CLQs with robust lag measurements. The changing-obscuration model is not consistent with the observed X-ray spectra and spectral energy distribution changes seen in these CLQs. It is highly likely that the observed changes are due to the changing accretion rate of the supermassive black hole, so the multiwavelength emission varies accordingly, with promising analogies to the accretion states of X-ray binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The evolution of the Milky Way’s thin disc radial metallicity gradient with K2 asteroseismic ages

ABSTRACT The radial metallicity distribution of the Milky Way’s disc is an important observational constraint for models of the formation and evolution of our Galaxy. It informs our understanding of the chemical enrichment of the Galactic disc and the dynamical processes therein, particularly radial migration. We investigate how the metallicity changes with guiding radius in the thin disc using a sample of red giant stars with robust astrometric, spectroscopic, and asteroseismic parameters. Our sample contains 668 stars with guiding radii 4 < Rg < 11 kpc and asteroseismic ages covering the whole history of the thin disc with precision ${\approx} 25 {{\, \rm per\ cent}}$. We use MCMC analysis to measure the gradient and its intrinsic spread in bins of age and construct a hierarchical Bayesian model to investigate the evolution of these parameters independently of the bins. We find a smooth evolution of the gradient from ≈−0.07 dex kpc−1 in the youngest stars to ≈−0.04 dex kpc−1 in stars older than 10 Gyr, with no break at intermediate ages. Our results are consistent with those based on asteroseismic ages from CoRoT, with that found in Cepheid variables for stars younger than 1 Gyr, and with open clusters for stars younger than 6 Gyr. For older stars we find a significantly lower metallicity in our sample than in the clusters, suggesting a survival bias favouring more metal-rich clusters. We also find that the chemical evolution model of Chiappini '09 is too metal poor in the early stages of disc formation. Our results provide strong new constraints for the growth and enrichment of the thin disc and radial migration, which will facilitate new tests of model conditions and physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Electron microscopy characterization of the fuel-cladding interaction in medium burnup annular fast reactor MOX

In this work, we present electron microscopy data focused on the fuel-cladding interaction layer in annular fast reactor MOX with HT-9 cladding at medium burnup. In agreement with previous literature data, the volatile fission products Cs, Te and I have migrated radially into the extreme fuel periphery and partially interacted with the cladding. The accumulation of Cs has occurred in the outermost rim of the fuel pellet, where grain recrystallization has also been observed. Significant amounts of Pd have been found in the interaction zone, particularly in the sample taken from the upper half of the fissile column where the cladding temperatures are higher. At this axial location, Cr has been enriched at the cladding inner surface and diffused into the fuel. Furthermore, chromium remains mainly in metallic form, but locally formed oxides. The fission products Cs, Te and I are found, with variable composition, in form of nanocrystalline regions dispersed in the metallic Cr-rich layer. The morphology and chemical characteristics of the layer suggest a non-oxidative corrosion mechanism as principal cladding degradation phenomenon occurring in this sample, with local onset of Cr oxidation within the nanocrystalline precipitates.

36 MATERIALS SCIENCE↗