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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Behavior of thermally quenched topological defects in quasicrystal artificial spin ices

We report that understanding the formation of topological defects in connected magnetic nanowires such as in artificial spin ices (ASIs) is critical to controlling their behavior. Moreover, emergent frustration behavior of these defects can be expected due to complex underlying lattice geometry of the ASIs. We have explored in situ thermalization and quenching of quasicrystalline ASIs, which exhibit additional frustration due to aperiodicity from near the Curie temperature, and we observe the formation of two sets of topological vortex defects: within the magnetic bars and within the vertices at which the bars meet. By varying the laser fluence, we show that the number of defects in the vertices varies as the quenching rate changes following a power law relation, which we interpret as being related to the ferromagnetic-to-paramagnetic phase transition. Conversely, the defects formed within the bars are metastable states related to the spontaneous magnetization reversal of the magnetic bars and are therefore strongly dependent on underlying lattice geometry. These results provide insight into the emergence and control of topological defects in confined frustrated magnetic systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Exotic Non-Abelian Topological Defects in Lattice Fractional Quantum Hall States

We investigate extrinsic wormholelike twist defects that effectively increase the genus of space in lattice versions of multicomponent fractional quantum Hall systems. Although the original band structure is distorted by these defects, leading to localized midgap states, we find that a new lowest flat band representing a higher genus system can be engineered by tuning local single-particle potentials. Remarkably, once local many-body interactions in this new band are switched on, we identify various Abelian and non-Abelian fractional quantum Hall states, whose ground-state degeneracy increases with the number of defects, i.e, with the genus of space. This sensitivity of topological degeneracy to defects provides a “proof of concept” demonstration that genons, predicted by topological field theory as exotic non-Abelian defects tied to a varying topology of space, do exist in realistic microscopic models. Specifically, our results indicate that genons could be created in the laboratory by combining the physics of artificial gauge fields in cold atom systems with already existing holographic beam shaping methods for creating twist defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Large spin-orbit splitting of deep in-gap defect states of engineered sulfur vacancies in monolayer WS 2

Structural defects in 2D materials offer an effective way to engineer new material functionalities beyond conventional doping in semiconductors. Specifically, deep in-gap defect states of chalcogen vacancies have been associated with intriguing phenomena in monolayer transition metal dichalcogenides (TMDs). Here, we report the direct experimental correlation of the atomic and electronic structure of a sulfur vacancy in monolayer WS 2 by a combination of CO-tip non-contact atomic force microscopy (nc-AFM) and scanning tunneling microscopy (STM). Sulfur vacancies, which are absent in as-grown samples, were deliberately created by annealing in vacuum. Two energetically narrow unoccupied defect states of the vacancy provide a unique fingerprint of this defect. Direct imaging of the defect orbitals by STM and state-of-the-art GW calculations reveal that the large splitting of 252 meV between these defect states is induced by spin-orbit coupling. The controllable incorporation and potential decoration of chalcogen vacancies provide a new route to tailor the optical, catalytic and magnetic properties of TMDs.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Energy transfer networks: Quasicontinuum photoluminescence linked to high densities of defects

In a series of studies related to laser-induced damage of optical materials and deposition of plastics, we discovered a broadly emitting photoluminescence with fast lifetimes that we termed quasicontinuum photoluminescence (QC-PL). Here in this paper, we suggest that a high density of optically active defects leads to QC-PL, where interactions between defects affect the temporal and spectral characteristics of both excitation and emission. We develop a model that predicts the temporal characteristics of QC-PL, based on energy transfer interactions between high densities of defects. Our model does not explain all spectral broadening and redshifts found in QC-PL, since we do not model spectral changes in defects due to proximity to other defects. However, we do provide an example of a well-defined system that exhibits the QC-PL characteristics of a distribution in shortened lifetimes and broadened, redshifted energy levels: an organic chromophore (fluorescein) that has been dried rapidly on a fused silica surface. Recently, we showed that regions of fused silica exposed to up to 1 billion high-fluence laser shots at 351 rm nm at subdamage fluences exhibit significant transmission losses at the surface. Here, we find that these laser-exposed regions also exhibit QC-PL. Increases in the density of induced defects on these laser-exposed surfaces, as measured by the local transmission loss, lead to decreases in the observed lifetime and redshifts in the spectrum of the QC-PL, consistent with our explanation for QC-PL. In conclusion, we have found QC-PL in an increasing variety of situations and materials, and we believe it is a phenomenon commonly found on surfaces and nanostructured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dynamics of interaction between dislocations and point defects in bcc iron

The interaction between dislocations and point defects is crucial for many physical properties and phenomena in materials, such as strengthening mechanisms, dislocation bias and void swelling, creep, and impurity segregation around dislocations. Conventional dislocation-point defect interaction models use approximations based on elasticity theory and/or based on assumptions that transition states energies can be deduced from the binding energies of the defects. In this paper, we present the transport properties of point defects near dislocations based on the actual saddle-point configuration of vacancies and self-interstitial atoms as a function of position with respect to screw and edge dislocations in a model system (bcc iron) using the self-evolving atomistic kinetic Monte Carlo. Here, KMC simulations reveal defect dynamics near dislocations are highly anisotropic and correlated, particularly for dumbbells in the compressive field of the edge dislocation, which could result in zones near dislocation cores where dumbbells are less efficiently absorbed compared with vacancies. This study provides accurate saddle-point configurations and energies required to properly describe the dynamics of point defects around dislocations, allowing fundamental insights on the transport mechanisms which are essential for understanding microstructural evolution and mechanical properties of metallic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗
DOE OSTI2017

Defects in Na-, K-, and Cd-Doped CuInSe$_2$ : Canonical Thermodynamics Based on Ab Initio Calculations

In this work. we extend a canonical-thermodynamic method for computing intrinsic point defect concentrations as a function of chemical stoichiometry and temperature to include extrinsic defect contributions, while applying this method to study defects in CuInSe 2 . This technique relies on a large set of defect formation energies calculated from first principles, which require corrections for known errors arising from spurious interactions. Guided by recent experimental work exhibiting the complex interplay between Na, K, and Cd incorporation, we examine the behavior of dominant defects as the material composition varies under experimentally relevant conditions. In addition to identifying the regions of composition-parameter space relevant to the incorporation of impurities Na, K, and Cd, and stable against the formation of secondary compounds, we further study defect kinetics susceptible to the presence of these impurities. From this analysis, we propose a simple model for the enhanced diffusion of Cu-vacancies mediated by K, which could lead to the enhanced incorporation of Cd observed experimentally.

42 ENGINEERING↗
DOE OSTI2021

Metallic line defect in wide-bandgap transparent perovskite BaSnO 3

A line defect with metallic characteristics has been found in optically transparent BaSnO 3 perovskite thin films. The distinct atomic structure of the defect core, composed of Sn and O atoms, was visualized by atomic-resolution scanning transmission electron microscopy (STEM). When doped with La, dopants that replace Ba atoms preferentially segregate to specific crystallographic sites adjacent to the line defect. The electronic structure of the line defect probed in STEM with electron energy-loss spectroscopy was supported by ab initio theory, which indicates the presence of Fermi level–crossing electronic bands that originate from defect core atoms. These metallic line defects also act as electron sinks attracting additional negative charges in these wide-bandgap BaSnO 3 films.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ab Initio Insights to Metal Passivation: Diffusion and Defect Formation in Amorphous Zirconia and Alumina

Metal passivation refers to the formation of protective oxide films on metals, which shield them from further corrosion and oxidation, playing a crucial role in maintaining their stability. The mesoscopic Point Defect Model has successfully predicted passivity as a steady state process where oxide growth from oxygen vacancies at the metal/film interface competes with oxide dissolution at the film/environment interface. In this work, informed by the Point Defect Model parameters, we use first-principles calculations to calculate defect formation and atomic diffusion in amorphous materials and correlate these descriptors with the behavior and growth of the oxide film. Focusing on amorphous zirconia and alumina, we demonstrate that defect formation energies exhibit significant variability in amorphous systems. In alumina, vacancies dominate, with cation and anion vacancies occurring at comparable concentrations. Diffusion calculations for stoichiometric amorphous alumina and zirconia, as well as oxygen-deficient zirconia, reveal faster diffusion in the oxygen-deficient case, highlighting the impact of defects on transport. Comparison of calculated self-diffusion coefficients for the dominant defect species with experimentally measured oxide thicknesses shows a clear correlation, suggesting that first-principles-derived diffusivity information can serve as a key descriptor for surface passivation film growth.

Farnell, Mackinzie S. [University of California, B↗
DOE OSTI2023

Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) v.0

SAND2024-08598O The Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) characterizes nitrogen-vacancy centers in diamond and other defects. It does this by using a radio frequency system-on-a-chip (RFSoC) field programmable gate array (FPGA). QICKDAWG synthesizes microwave pulses from the RFSoC to change the spin state of the defects. The software also allows for laser control using the RFSoC, which optically pumps defects. Ultimately, QICKDAWG supports the implementation of RFSoC FPGAs in defect characterization. This replaces the slow, expensive, traditional hardware, thus lowering the cost and time for defect characterization. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2022

Irradiation-Induced Defect Evolution in Nuclear Graphite

Graphite has historically been used as a moderator material in nuclear reactor designs dating back to the first man-made nuclear reactor to achieve criticality (Chicago Pile 1) in 1942. Additionally, graphite is a candidate material for use in the future envisioned next-generation nuclear reactors (Gen IV); specifically, the molten-salt-cooled (MSR) and very-high-temperature reactor (VHTR) concepts. Gen IV reactor concepts will introduce material challenges as temperature regimes and reactor lifetimes are anticipated to far exceed those of earlier reactors. Irradiation-induced defect evolution is a fundamental response in nuclear graphite subjected to irradiation. These defects directly influence the many property changes of nuclear graphite subjected to displacing radiation; however, a comprehensive explanation for irradiation-induced dimensional change remains elusive. The objectives of this project were focused on the characterization of irradiation-induced defect evolution in nuclear graphite via transmission electron microscopy (TEM). With the use of novel TEM specimen preparation techniques, high-temperature electron-irradiation and characterization of high-temperature neutron-irradiated nuclear graphite, novel fullerene-like defects are shown to be a dominant defect type, especially at higher temperatures. These results contradict the historical models of defect evolution and provide valuable insight into the macroscopically observed property changes in irradiated nuclear graphite.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Report on PTT Imaging of Defects in AM Metallic Materials-Part 2

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An Analytical Tool to Evaluate Defect Thermodynamics of (La,Ba)Fe1-xMxO3-δ Perovskites for Solid-Oxide Cell Applications

A modeling tool of the defect thermodynamics of (La,Ba)Fe1-xMxO3-δ perovskites which includes energetic information about oxygen vacancy formation, hydration, hydride formation, and charge disproportionation reactions has been developed1. This tool incorporates defect energies and entropies expressed as sixth order polynomial functions to allow refinements of the defect reaction equilibrium constants in the thermodynamic analysis. Calculation of (La,Ba)Fe1-xMxO3-δ Brouwer diagrams as a function of pO2/pH2O and pH2/H2O in a range of temperatures of interest is facilitated by this modeling tool. The results obtained can provide direct guidance how the electronic and ionic defect concentrations of the triple conducting perovskite materials can be used to optimize performance of solid oxide cells for energy applications. The impact of magnetic and electronic structures of the perovskites on the defect reaction energies and entropies as obtained from density function theory modeling and the role played by hydride defect species will also be discussed.

Lee, Yueh-Lin↗
DOE OSTI2022

Towards Quantitative Inference of Nanoscale Defects in Irradiated Metals and Alloys

Quantifying the population of nanoscale defects that are formed in metals and alloys exposed to extreme radiation environments remains a pressing challenge in materials science. These defects both fundamentally alter material properties and seed long-timescale performance degradation, which often limits the lifespan of engineering systems. Unlike ceramic and semiconducting materials, these defects in metals and alloys are not spectroscopically active, forcing characterization to rely on indirect measurements from which the distribution of nanoscale defects may be inferred. In this mini-review, different experimental methodologies which have been employed for defect inference are highlighted to capture the current state of the art. Future directions in this area are proposed, which, by combining data streams from multiple and complementary characterization methods in concert with multi-scale modeling and simulation, will enable the ultimate goal of quantifying the full spectrum of defects in irradiated metals and alloys.

Hirst, Charles A.↗
DOE OSTI2025

Intrinsic Defect-Induced Local Semiconducting-to-Metallic Regions Within Monolayer 1T-TiS2 Displayed by First-Principles Calculations and Scanning Tunneling Microscopy

Using density functional theory (DFT) and scanning tunneling microscopy (STM), the intrinsic point defects, formation energy, and electronic structure of 1T-TiS2 were investigated. Defect systems include single-atom vacancies, interstitial and adatom additions, and direct atomic substitution. Using a collective approach for analyzing realistic systems for point defect investigation, we provide a more straightforward comparison to the experimental measurements, reproducing more realistic environmental conditions related to thin film growth. STM images are compared to computationally simulated electron density images to identify specific geometries that result from favorable point defects. DFT suggests that titanium interstitials are the most energetically favorable intrinsic defect, and sulfur vacancies are more likely to form than titanium vacancies within this realistic analysis, which is in agreement with STM data. A pristine, stoichiometric monolayer system is calculated to have a direct band gap of 0.422 eV, which varies based on local point defects. Local semiconducting-to-metallic electronic transitions are predicted to occur based on the presence of Ti interstitials.

Keeney, P. J.↗
NASA NTRS1992

Eddy current inspection of weld defects in tubing

An approach using differential probes for the inspection of weld defects in tubing is studied. Finite element analysis is used to model the weld regions and defects. Impedance plane signals are predicted for different weld defect types and compared wherever possible with signals from actual welds in tubing. Results show that detection and sizing of defects in tubing is possible using differential eddy current techniques. The phase angle of the impedance plane trajectory gives a good indication of the sizing of the crack. Data on the type of defect can be obtained from the shape of the impedance plane trajectory and the phase. Depending on the skin depth, detection of outer wall, inner wall, and subsurface defects is possible.

Katragadda, G.↗
NASA NTRS1993

Electronic characterization of defects in narrow gap semiconductors

The study of point defects in semiconductors has a long and honorable history. In particular, the detailed understanding of shallow defects in common semiconductors traces back to the classic work of Kohn and Luttinger. However, the study of defects in narrow gap semiconductors represents a much less clear story. Here, both shallow defects (caused by long range potentials) and deep defects (from short range potentials) are far from being completely understood. In this study, all results are calculational and our focus is on the chemical trend of deep levels in narrow gap semiconductors. We study substitutional (including antisite), interstitial and ideal vacancy defects. For substitutional and interstitial impurities, the efects of relaxation are included. For materials like Hg(1-x)Cd(x)Te, we study how the deep levels vary with x, of particular interest is what substitutional and interstitial atoms yield energy levels in the gap i.e. actually produce deep ionized levels. Also, since the main technique utilized is Green's functions, we include some summary of that method.

Patterson, James D.↗