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Results for “Defect modelling”

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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Oxygen point defect accumulation in single-phase U O 2 + x

UO 2.07 was characterized using neutron total scattering in order to elucidate defect morphology in the low oxygen-to-metal regime (x < 0.125 for UO 2+x ). Data were collected at temperatures (600 and 1000 °C) coinciding with the single-phase UO 2+x region of the established phase diagram, and results were compared with data of stoichiometric UO 2 collected at near-identical temperatures. Experimental data were modeled and interpreted using a holistic approach employing a combination of analyses that characterized multiple spatial length scales. Preferential modeling of long-range atomic arrangements with Rietveld refinement suggests the existence of primarily monointerstitials in UO 2.07 , whereas preferential modeling of short-range atomic structures with small-box pair distribution function (PDF) refinement indicates the presence of defect clusters in UO 2.07 . Simultaneous modeling of multiple length scales using complementary reverse Monte Carlo (RMC) and molecular dynamics (MD) methods confirms that excess oxygen atoms in UO 2.07 exist as small defects, such as monointerstitials and di-interstitials. RMC and MD results agree with diffraction analysis but differ significantly from small-box PDF refinements, which may be related to a lack of intermediate- and long-range structural information gained from the small-box PDF refinement procedure. Employing a combination of analysis methods with varying length-scale sensitivities enabled more accurate assessment of the UO 2+x defect structure. Furthermore, our findings provide experimental support for previously predicted di-interstitial defect morphologies in UO 2+x that highly influence the accurate prediction of bulk physiochemical properties of UO 2+x , such as oxygen diffusivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1982

Calcium transport from the intestine and into bone in a rat model simulating weightlessness

The objective of this study was to determine whether a defect in transport of calcium in the duodenum was related to decreased bone formation in the suspended rat. Rats were suspended by the tail at a 40 deg angle for up to 15 days. Ca-45 was injected into the ligated duodenum in situ 15 minutes prior to sacrific. Blood, tibia, vertebra and humerus were obtained for total calcium and Ca-45 analyses. Intestinal calcium transport did not appear to be significantly altered by suspension. However, by 5 days of suspension a significant decrease in accumulation of Ca-45 into tibia and vertebra was observed. A trend of decreasing bone mineral and mass was established in tibia and vertebra by the fifth day of suspension. The humerus failed to demonstrate a significant weight decrease or change in Ca-45 accumulation after 15 days of suspension. Results from this simulated weightlessness model suggest that transport of calcium from intestine into bone is decreased within 5 days of suspension. This deficiency appears to be associated with a progressive decrease in total mass of non-weightbearing bones.

Bikle, D. D.↗
NASA NTRS1993

Self-ordering physics in an open universe

This Letter presents an analytical model for the generation of density fluctuations likely to be appropriate for defects such as gauged and global strings, global monopoles, and textures, as well as for nontopological textures in an open or flat universe. For a reasonable range of parameters, these models in an open universe are compatible with both the level of MW fluctuations detected by COBE and with the fluctuations observed in the galaxy counts.

Spergel, David N.↗
DOE OSTI2023

Plasticity in irradiated FeCrAl nanopillars investigated using discrete dislocation dynamics

Here, in this paper, we investigate plasticity in irradiated FeCrAl nanopillars using discrete dislocation dynamics simulations (DDD), with comparisons to transmission electron microscopic (TEM) in situ tensile tests of ion- and neutron-irradiated commercial C35M FeCrAl alloy. The effects of irradiation-induced defects, such as a/2<111> and a<100> type loops and composition fluctuations representative of phase separation in irradiated FeCrAl alloys, are investigated separately as well as superposed together in simulations. We explore the effects of defects on the stress-strain behavior, specifically yield strength and hardening response, of FeCrAl nanopillars. Our simulations confirm the widely accepted fact that irradiated alloys exhibit a stress-strain response with higher yield strength as compared to unirradiated alloys. However, our DDD calculations reveal an atypical superposition of the hardening contributions due to composition inhomogeneity and irradiation loops wherein composition inhomogeneity annihilates the hardening due to irradiation loops at small scales. As a result, we observe that the yield strength in irradiated alloys, after taking into consideration the effects of both composition inhomogeneity and irradiation loops, is smaller than the yield strength of the alloys with only irradiation loops and is approximately same for the alloy with composition inhomogeneity alone. This is referred to as “destructive interference” between the hardening contributions due to composition fluctuations and irradiation loops in the paper. We also identify this destructive interference in the superposition in our parallel TEM in situ tensile tests on unirradiated, ion-irradiated, and neutron-irradiated C35M FeCrAl alloy. This destructive interference in the hardening contributions contrasts with the dispersed barrier hardening (DBH) models widely utilized by the experimental community to model the hardening contributions due to different irradiation induced defects. The effects of the loading orientations on the yield strength and hardening are investigated and the mechanisms for the hardening in irradiated FeCrAl alloys are also reported.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the Equilibrium Electrostatic Potential and Light-Induced Charge Redistribution in Halide Perovskite Structures

Lead halide perovskites are semiconductor materials which are employed as nonintentionally doped absorbers inserted between two selective carrier transport layers (SCTL), realizing a p-i-n or n-i-p heterojunction. In our study, we have developed and investigated a lateral device, based on methylammonium lead iodide (MAPbI3) in which the p-i-n heterojunction develops in the horizontal direction. Our research suggests that the effective doping level in the MAPbI3 film should be very low, below 1012 cm-3. Along the vertical direction, this doping level is not enough to screen the electric field of the buried heterojunction with the SCTL. The perovskite work function is therefore affected by the work function of the SCTL underneath. From drift-diffusion simulations, we show that intrinsic perovskite-SCTL structures develop mV range surface photovoltages (SPVs) under continuous illumination. However, perovskite-SCTL structures can develop SPVs of hundreds of mV, as confirmed by our measurements. We therefore analyzed the compatibility between low doping and low defect densities in the perovskite layer and such high SPV values using numerical modeling. It is shown that these high SPV values could originate from electronic processes due to large band offsets in the buried perovskite-SCTL heterojunctions, or at the SCTL-transparent conductive oxide (TCO) buried heterojunction. However, such electronic processes can hardly explain the long SPV persistence after switching off the illumination.

defects↗
DOE OSTI2020

Defect-Enhanced Polarization Switching in the Improper Ferroelectric LuFeO 3

Results of switching behavior of the improper ferroelectric LuFeO 3 are presented. Here, using a model set of films prepared under controlled chemical and growth-rate conditions, it is shown that defects can reduce the quasi-static switching voltage by up to 40% in qualitative agreement with first-principles calculations. Switching studies show that the coercive field has a stronger frequency dispersion for the improper ferroelectrics compared to a proper ferroelectric such as PbTiO 3 . It is concluded that the primary structural order parameter controls the switching dynamics of such improper ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Efficiency and Forward Voltage of Blue and Green Lateral LEDs with V-shaped Defects and Random Alloy Fluctuation in Quantum Wells

For nitride-based blue and green light-emitting diodes (LEDs), the forward voltage V for is larger than expected, especially for green LEDs. This is mainly due to the large barriers to vertical carrier transport caused by the total polarization discontinuity at multiple quantum well and quantum barrier interfaces. The natural random alloy fluctuation in quantum wells has proven to be an important factor reducing V for . However, this does not suffice in the case of green LEDs because of their larger polarization-induced barrier. V-shaped defects (V-defects) have been proposed as another key factor in reducing V for to allow lateral injection into multiple quantum wells, thus bypassing the multiple energy barriers incurred by vertical transport. In this paper, to model carrier transport in the whole LED, we consider both random-alloy and V-defect effects. A fully two-dimensional drift-diffusion charge-control solver is used to model both effects. The results indicate that the turn-on voltages for blue and green LEDs are both affected by random alloy fluctuations and the V-defect density. For green LEDs, V for decreases more due to V-defects, where the smaller polarization barrier at the V-defect sidewall is the major path for lateral carrier injection. Then, we discuss how the V-defect density and size affects the results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2022

Assurance Equations: A Cost and Criticality Model for Optimizing Quality Assurance Surveillance

The cost of quality vs cost of failure correction has been a long-running topic of discussion within the Aerospace community. It leads directly to concepts of “risk tolerance”, and risk-based decision-making. It would be valuable if there was a way to compute the optimal investment in customer-executed quality assurance activities using defect significance with respect to performance objectives, the activities’ defect detection effectiveness, and the cost-penalty for late discovery of impactful defects. This optimization is particularly of interest to projects whose budget constraints significantly limit their risk management options.The cost to fix defects (i.e., failure correction) escalates as the project matures. There have been studies attempting to determine the relative cost of fixing defects discovered during various phases of a project life cycle with important implications, all of which suggest growth factors are large. The commonly referred to 1:10:100 rule represents a cost multiplier for repair/rework across the Design to Fab to Test hardware development phases. Cost premiums for QA activities also accumulate when they are treated as mandatory (due to schedule drag) or are performed later than their assigned phase.This paper describes the modeling of development phase -dependencies in the conduct of typical customer-executed quality assurance activities. Our initial modeling encompasses:• Distinct phases of the production lifecycle• Multiple kinds of Defects, each with some a-priori likelihood of being present• Each defect’s impact on performance Objectives for a type of hardware• The cost and efficacy of assurance techniques at detecting such Defects• The costs of fixing those Defects detected in a given phase of the production lifecycleThe model captures assurance activities’ abilities to Detect defects. Upon detection it is assumed that the Defect is immediately fixed. Defects that “escape” detection by some activity may thereafter be detected by a later activity, but by then the cost of fixing the Defect may have escalated. Defects are related to the performance Objectives they would detract from, were those Defects to remain present in the operating system.We have constructed and are exploring, a model that relates the importance of hardware system elements to mission objectives, the impact of types of Defects on those hardware types, the cost of customer-executed assurance activities (i.e., supplier controls) and their effectiveness towards reducing an impactful quality escape, and the cost of Defect correction across production phase. We describe the approach taken to select the key model aspects, why they are relevant to our NASA mission, and our efforts to populate it with relevant and contemporary data. We use a notional example to illustrate model design and function.

Plante, Jeannette↗
NASA NTRS2016

Topic Modeling of NASA Space System Problem Reports: Research in Practice

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

Data Mining↗
NASA NTRS1972

Cardiovascular system simulation in biomedical engineering education.

Use of complex cardiovascular system models, in conjunction with a large hybrid computer, in biomedical engineering courses. A cardiovascular blood pressure-flow model, driving a compartment model for the study of dye transport, was set up on the computer for use as a laboratory exercise by students who did not have the computer experience or skill to be able to easily set up such a simulation involving some 27 differential equations running at 'real time' rate. The students were given detailed instructions regarding the model, and were then able to study effects such as those due to septal and valve defects upon the pressure, flow, and dye dilution curves. The success of this experiment in the use of involved models in engineering courses was such that it seems that this type of laboratory exercise might be considered for use in physiology courses as an adjunct to animal experiments.

Rideout, V. C.↗
DOE OSTI2026

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗
DOE OSTI2022

Searching for axion-like particles through CMB birefringence from string-wall networks

Axion-like particles (ALPs) can form a network of cosmic strings and domain walls that survives after recombination and leads to anisotropic birefringence of the cosmic microwave background (CMB). In addition to studying cosmic strings, we clarify and emphasize how the formation of ALP-field domain walls impacts the cosmic birefringence signal; these observations provide a unique way of probing ALPs with masses in the range 3H 0 ≲ m a ≲ 3H cmb . Using measurements of CMB birefringence from several telescopes, we find no evidence for axion-defect-induced anisotropic birefringence of the CMB. We extract constraints on the model parameters that include the ALP mass ma, ALP-photon coupling Script A ∝ g aγγ f a , the domain wall number N dw , and parameters characterizing the abundance and size of defects in the string-wall network. Considering also recent evidence for isotropic CMB birefringence, we find it difficult to accommodate this with the non-detection of anisotropic birefringence under the assumption that the signal is generated by an ALP defect network.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

SAGA1 and MITH1 produce matrix-traversing membranes in the CO2-fixing pyrenoid

Abstract Approximately one-third of global CO 2 assimilation is performed by the pyrenoid, a liquid-like organelle found in most algae and some plants. Specialized pyrenoid-traversing membranes are hypothesized to drive CO 2 assimilation in the pyrenoid by delivering concentrated CO 2 , but how these membranes are made to traverse the pyrenoid matrix remains unknown. Here we show that proteins SAGA1 and MITH1 cause membranes to traverse the pyrenoid matrix in the model alga Chlamydomonas reinhardtii . Mutants deficient in SAGA1 or MITH1 lack matrix-traversing membranes and exhibit growth defects under CO 2 -limiting conditions. Expression of SAGA1 and MITH1 together in a heterologous system, the model plant Arabidopsis thaliana , produces matrix-traversing membranes. Both proteins localize to matrix-traversing membranes. SAGA1 binds to the major matrix component, Rubisco, and is necessary to initiate matrix-traversing membranes. MITH1 binds to SAGA1 and is necessary for extension of membranes through the matrix. Our data suggest that SAGA1 and MITH1 cause membranes to traverse the matrix by creating an adhesive interaction between the membrane and matrix. Our study identifies and characterizes key factors in the biogenesis of pyrenoid matrix-traversing membranes, demonstrates the importance of these membranes to pyrenoid function and marks a key milestone toward pyrenoid engineering into crops for improving yields.

Hennacy, Jessica H.↗
DOE OSTI2020

Direct Observation of Electron Beam-Induced Phase Transition in MgCrMnO 4

Irreversible structural transformation in intercalation-type cathode materials, which has been frequently observed, has been perceived as a principal cause of capacity fading and voltage decay in (uni) multivalent batteries. Herein, we explored the electron beam-induced spinel to defective rocksalt phase transitions in MgCrMnO 4 , a potential multivalent cation intercalation cathode, using atomic-resolution imaging and spectroscopy in an aberration-corrected scanning transmission electron microscope. This dynamic electron beam irradiation study of specific structural transformations provides an atomistic understanding of the structural evolution observed in transition-metal oxide spinels during electrochemical cycling using multivalent cations, such as Mg 2+ . By combining an imaging study with first-principles modeling, we demonstrate that the mechanism of the spinel to defective rocksalt transformation in MgCrMnO 4 nanostructures is enabled by the presence of oxygen vacancies and is, therefore, very similar to that observed in transition-metal oxide spinels upon Li intercalation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Twisting and Rippling of a Two-Dimensional Kagome Lattice: Silica on Au(111)

We report the intrinsic properties of two-dimensional (2D) SiO 2 were revealed by forming the material on inert Au(111). Growth by SiO deposition enabled formation of a crystalline phase consisting of two linked sheets of six-membered rings of tetrahedral [SiO 4 ] building units. The bases of the tetrahedra form an isostatic 2D kagome lattice. The weak interaction with Au allowed a new corrugation of the 2D material to be detected: ripples with a ~ 4 nm periodicity that help stabilize the 2D crystalline layer. On the atomic scale, substantial distortions from ideal hexagonal rings were observed even though crystalline defects were extremely rare. The ring distortions were reproduced in theoretical models that showed that they were associated with a twisting of the 2D kagome lattice, which stabilizes the material when subjected to disturbances. The twisting and rippling impart 2D silica with the flexibility to adapt to strain and changes in the crystallographic direction without introducing defects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Grain boundary metastability controls irradiation resistance in nanocrystalline metals

Grain boundaries (GBs) in polycrystalline materials are powerful sinks for irradiation defects. While standard theories assume that a GB’s efficiency as a sink is defined solely by its character before irradiation, recent evidence conclusively shows that the irradiation sink efficiency is a highly dynamic property controlled by the intrinsic metastability of GBs under far-from-equilibrium irradiation conditions. In this paper, we reveal that the denuded (i.e., defect-free) zone, typically the signature of a strong sink, can collapse as irradiation damage accumulates. We propose a radiation damage evolution model that captures this behavior based on the emergence of a series of irradiation defect-enabled metastable GB microstate changes that dynamically alter the ability of the GB to absorb further damage. We show that these microstate changes control further defect absorption and give rise to the formation of a defect network that manifests itself as a net Nye-tensor signal detectable via lattice curvature experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effective parameterization of phase-field models of fission gas bubble growth

Fission gas bubbles are one of the most important microstructural features of ceramic nuclear fuels. As gas bubbles grow and interconnect, they allow release of gases, with important consequences for fuel performance. Phase-field modeling has been increasingly used to simulate the evolution of fission gas bubble microstructural because of its capability to capture complex microstructural features. However, computational performance limitations have made it difficult to simulate all the defects present in fuels during operation. For this reason, phase-field models have often simulated only vacancies and used multiple approaches to include the effect of vacancy-interstitial recombination and sinks in a simplified way. Here, we compare some of the most prevalent approaches, including source-only and source/sink. The kinetics of bubble growth using these approaches are analyzed analytically, and simulations with these approaches are compared to a full vacancy-interstitial model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗