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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Ultrasonic NDE Simulation for Composite Manufacturing Defects

The increased use of composites in aerospace components is expected to continue into the future. The large scale use of composites in aerospace necessitates the development of composite-appropriate nondestructive evaluation (NDE) methods to quantitatively characterize defects in as-manufactured parts and damage incurred during or post manufacturing. Ultrasonic techniques are one of the most common approaches for defect/damage detection in composite materials. One key technical challenge area included in NASA's Advanced Composite's Project is to develop optimized rapid inspection methods for composite materials. Common manufacturing defects in carbon fiber reinforced polymer (CFRP) composites include fiber waviness (in-plane and out-of-plane), porosity, and disbonds; among others. This paper is an overview of ongoing work to develop ultrasonic wavefield based methods for characterizing manufacturing waviness defects. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with in-plane fiber waviness (also known as marcelling). Wavefield data processing methods are applied to the simulation data to explore possible routes for quantitative defect characterization.

Leckey, Cara A. C.↗
NASA NTRS2019

Complex Intergrowths of Non-Stoichiometric Defect-Structured Hibonite and Al-Rich Spinel in an Allende Ca-Al-Rich Inclusion

Hibonite is a primary ultra-refractory mineral occurring in many Ca-Al-rich inclusions (CAIs) and is predicted to condense as the second major phase from a cooling gas of solar composition. Our previous microstructural studies of hibonite in carbonaceous chondrites revealed its unique microstructures consisting of numerous defects that contain Mg-enriched, wider spinel blocks in stoichiometric hibonite. Han, J. et al. [2 items] demonstrated experimentally that defect-structured hibonites can grow easily in the presence of minor Mg and are kinetically more stable than equilibrium assemblages predicted by thermodynamic calculations. However, a thermo-dynamic vs. structural stability of defect-structured hibonite relative to other early-condensed Al-rich phases such as corundum, grossite, and spinel remains poorly constrained. Here, we present the results of atomic resolution TEM (Transmission Electron Microscopy) imaging of hibonite in a compact Type A CAI in the Allende CV3 chondrite in order to better understand the crystal structure and chemistry of defect-structured hibonite and its associated Al-rich phases, especially non-stoichiometric, Al-rich spinel, in the context of the formation of first refractory solids in the early solar nebula.

Han, J.↗
NASA NTRS2018

Experimental Calibration of a Numerical Model of Prepreg Tack for Predicting AFP Process Related Defects

Wrinkles, puckers, and fiber bridging are among the major defects encountered in the Automated Fiber Placement (AFP) process, and are all different manifestations of fiber misalignment. The main driver for these defects are the residual stresses introduced in the tow during the deposition stage by the AFP head. In contrast, the tack between the deposited tape and the substrate is the resisting force against the formation of such defects. Tack may be defined as the ability of a material to form a bond immediately on contact with another surface. Tack is a very complex phenomenon that is influenced by a variety of process parameters including temperature, head pressure and speed, as well as degree of cure, moisture content, and surface roughness A physics-based modeling framework for simulation of tack was developed in this study that allows for prediction of tack response. The developed tack model is incorporated in the AFP placement modelling framework developed to simulate AFP defects.

Forghani, Alireza↗
NASA NTRS2023

Automated Fiber Placement Through Thickness Defect Stacking Optimization

In its 2022 commercial market outlook, Boeing forecasted an 80% increase in the global fleet through 2041 compared to 2019 pre-pandemic levels. This sharp rise in demand will drive pressure onto airframe manufacturers to ramp up production and find more efficient ways to design and manufacture airplanes. Complicating this challenge is the industry’s recent transformation from traditional metal-based airframes towards hybrid composite-metal aircraft. While composites have been used in aviation for decades, aircraft manufacturers are still struggling to design and manufacture quality parts at a high rate. Automated Fiber Placement (AFP) is one of the main manufacturing techniques used to produce large-scale composite parts. After a design has been created, a manufacturing strategy has to be developed based on the working material, part geometry, and machine capabilities. This process planning stage is essential to the AFP workflow and currently requires a high level of manual input from an experienced process planner. In an effort to automate and optimize this stage, the Computer Aided Process Planning (CAPP) module was developed. CAPP assists process planners in identifying optimal starting point location and layup strategy for each ply of a laminate. This Ply-Level Optimization (PLO) phase operates on the quantification of ply quality through predictable geometry-based defects such as gaps, overlaps, angle deviation, and steering. As you move from PLO to Laminate-Level Optimization (LLO) the design space grows exponentially, emphasizing the need for automated optimization. The work presented in this thesis expands CAPP’s functionality by comparing the planned fiber paths through the thickness of the laminate to mitigate stacked area defects and achieve an optimal laminate-level manufacturing strategy. Within CAPP, predicted gap and overlap defects are imported from Vericut Composites Programming (VCP) and then discretized to streamline the through-thickness comparison. Two objective functions are used to score different combinations of ply layup strategies based on defect stacking both globally and locally. Four combinatorial optimization algorithms were coupled with these objective functions to investigate the laminate-level manufacturing strategy design space and converge on the optimal plan. These algorithms were evaluated based on accuracy and efficiency through virtual testing on a complex tool surface. A separate LLO approach was developed to achieve near-optimal laminates in significantly less time. The end result is a software package which greatly reduces the required input from process planners, shortening the design-build cycle time and improving part quality.

AFP↗
DOE OSTI2015

CASTING DEFECT MODELING IN AN INTEGRATED COMPUTATIONAL MATERIALS ENGINEERING APPROACH

To accelerate the introduction of new cast alloys, the simultaneous modeling and simulation of multiphysical phenomena needs to be considered in the design and optimization of mechanical properties of cast components. The required models related to casting defects, such as microporosity and hot tears, are reviewed. Three aluminum alloys are considered A356, 356 and 319. The data on calculated solidification shrinkage is presented and its effects on microporosity levels discussed. Examples are given for predicting microporosity defects and microstructure distribution for a plate casting. Models to predict fatigue life and yield stress are briefly highlighted here for the sake of completion and to illustrate how the length scales of the microstructure features as well as porosity defects are taken into account for modeling the mechanical properties. Thus, the data on casting defects, including microstructure features, is crucial for evaluating the final performance-related properties of the component. ACKNOWLEDGEMENTS This work was performed under a Cooperative Research and Development Agreement (CRADA) with the Nemak Inc., and Chrysler Co. for the project "High Performance Cast Aluminum Alloys for Next Generation Passenger Vehicle Engines. The author would also like to thank Amit Shyam for reviewing the paper and Andres Rodriguez of Nemak Inc. Research sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, as part of the Propulsion Materials Program under contract DE-AC05-00OR22725 with UT-Battelle, LLC. Part of this research was conducted through the Oak Ridge National Laboratory's High Temperature Materials Laboratory User Program, which is sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program.

Sabau, Adrian S↗
DOE OSTI2016

Mitigating Structural Defects in Droop-Minimizing InGaN/GaN Quantum Well Heterostructures

Modern commercial InGaN/GaN blue LEDs continue to suffer from efficiency droop, a reduction in efficiency with increasing drive current. External quantum efficiency (EQE) typically peaks at low drive currents (< 10 A cm 2 ) and drops monotonically at higher current densities, falling to <85% of the peak EQE at a drive current of 100 A cm 2 . Mitigating droop-related losses will yield tremendous gains in both luminous efficacy (lumens/W) and cost (lumens/$). Such improvements are critical for continued large-scale market penetration of LED technologies, particularly in high-power and high flux per unit area applications. However, device structures that reduce droop typically require higher indium content and are accompanied by a corresponding degradation in material quality which negates the droop improvement via enhanced Shockley-Read-Hall (SRH) recombination. In this work, we use advanced characterization techniques to identify and classify structural defects in InGaN/GaN quantum well (QW) heterostructures that share features with low-droop designs. Using aberration-corrected scanning transmission electron microscopy (C s -STEM), we find the presence of severe well width fluctuations (WWFs) in a number of low droop device architectures. However, the presence of WWFs does not correlate strongly with external quantum efficiency nor defect densities measured via deep level optical spectroscopy (DLOS). Hence, performance losses in the heterostructures of interest are likely dominated by nanoscale point or interfacial defects rather than large-scale extended defects.

36 MATERIALS SCIENCE↗
DOE OSTI2019

AUTOMATING SPENT FUEL DEFECT DETECTION WITH FUSED DCVD AND GET DATA

Within the safeguards regime, spent fuel monitoring has long been implemented to verify facility declarations. As the number and size of facilities under safeguards increase, so does time spent on highly repetitive spent fuel monitoring, making it an area ripe for automation. However, due to international proliferation concerns, automation must be robust and provide estimates of confidence in the results. Cerenkov Viewing Devices (CVDs) are widely implemented for spent fuel monitoring, but their single defect detection ability is limited. In this research, we augment CVD measurements with Gamma Emission Tomographer (GET) data in order to increase defect detection above the level of either detector method individually. Here we present the development and implementation of a Bayesian data fusion algorithm for classification of individual fuel rods as defects or nondefects across two burn-up and cooling time scenarios. Results show a nearly 75% single defect detection capability with a 10% false positive rate for 17x17 PWR fuel assemblies. The Bayesian framework also enables calculation of uncertainties associated with each classification. These results also show a moderate ability to generalize across both high burn-up and short cooling times as well as low burn-up and long cooling times.

Safeguards, image analysis, metric learning, Data ↗
DOE OSTI2022

Frequency domain assurance criterion for defect detection in additively manufactured parts

Additive manufacturing (AM) is a very desirable manufacturing method for industries such as aerospace and automotive due to its ability to create internal features and complex geometries, however, these characteristics also present challenges for nondestructive evaluation (NDE) and defect detection. Dynamic analysis and modal analysis have shown promise for NDE and identifying flaws in AM parts. Frequency Domain Assurance Criterion (FDAC) is a method of dynamic evaluation that represents the degree of correlation between two sets of operational deflection shapes (ODS) at each spectral line. Using colormaps to display the results allows for quick and easy interpretation of parts’ similarities and differences. This method appears to show promise in identifying parts with minor defects and can be used to differentiate nominal and defective parts. This paper explores the use of FDAC on various AM parts with and without intentional defects.

Deonarain, G↗
DOE OSTI2016

Multiscale real-space quantum-mechanical tight-binding calculations of electronic structure in crystals with defects using perfectly matched layers

Graphical abstract: - Abstract: We consider the scattering of incident plane-wave electrons from a defect in a crystal modeled by the time-harmonic Schrödinger equation. While the defect potential is localized, the far-field potential is periodic, unlike standard free-space scattering problems. Previous work on the Schrödinger equation has been almost entirely in free-space conditions; a few works on crystals have been in one-dimension. We construct absorbing boundary conditions for this problem using perfectly matched layers in a tight-binding formulation. Using the example of a point defect in graphene, we examine the efficiency and convergence of the proposed absorbing boundary condition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Mechanism of Metal Intercalation under Graphene through Small Vacancy Defects

Metal intercalation under graphene has attracted extensive experimental and theoretical research because of its capability to manipulate the electronic structure and properties of graphene. However, the pathways and mechanisms of intercalation are still not well understood. Here, we systematically investigate the intercalation process of metal atoms through graphene vacancies using first-principles calculations. We show that the energy barrier for metal atom penetration through the vacancies in graphene is small as long as the size of the vacancy is larger than a mono-vacancy. However, metal atoms are strongly bonded to the vacancy so that the detachment energy of a metal atom from the vacancy is extremely high. This inhibits the diffusion of the metal atom into the gallery beneath the surface to complete the intercalation process. On the other hand, our calculation results show that the detachment energy of a metal atom from a metal dimer at small vacancy defects is significantly reduced, making intercalation much easier. Therefore, the key step limiting the intercalation process is the detachment of the metal atoms from vacancy defects. This finding from our study provides useful insight into the defect-assisted intercalation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Plasmonic Energetic Electrons Drive CO 2 Reduction on Defective Cu 2 O

Plasmonic photoreduction of CO 2 is valuable for decarbonization and producing value-added chemicals. However, insights into the mechanisms of this reaction remain elusive, particularly regarding the roles of structural defects and their interplay with the nonequilibrium charge carriers. Here, we report density functional theory calculations on Cu 2 O, a prototype photocatalyst, through which we investigate CO 2 reduction over three defected facets to reveal the interfacial charge transfer and bond dynamics under plasmonic excitation. We find that the activation barrier of C–O bond cleavage decreases from 3.2 to about 1 eV, assisted by oxygen vacancies, and that the remaining barrier can be further reduced or eliminated at the plasmon-excited states when Cu 2 O is integrated with plasmonic metals. The regeneration of oxygen vacancies (by H 2 to form water) on Cu 2 O to complete the catalysis cycle is feasible and not affected by the energetic electrons. Furthermore, our calculations thus show the important synergistic effect of energetic electrons and point defects to promote CO 2 reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Defect Tolerance in Methylammonium Lead Triiodide Perovskite

Photovoltaic applications of perovskite semiconductor material systems have generated considerable interest in part because of predictions that primary defect energy levels reside outside the bandgap. We present experimental evidence that this enabling material property is present in the halide-lead perovskite, CH3NH3PbI3 (MAPbI3), consistent with theoretical predictions. By performing X-ray photoemission spectroscopy, we induce and track dynamic chemical and electronic transformations in the perovskite. These data show compositional changes that begin immediately with exposure to X-ray irradiation, whereas the predominant electronic structure of the thin film on compact TiO2 appears tolerant to the formation of compensating defect pairs of VI and VMA and for a large range of I/Pb ratios. Changing film composition is correlated with a shift of the valence-band maximum only as the halide-lead ratio drops below 2.5. This delay is attributed to the invariance of MAPbI3 electronic structure to distributed defects that can significantly transform the electronic density of states only when in high concentrations.

14 SOLAR ENERGY↗
DOE OSTI2014

Kinetic model for electric-field induced point defect redistribution near semiconductor surfaces

The spatial distribution of point defects near semiconductor surfaces affects the efficiency of devices. Near-surface band bending generates electric fields that influence the spatial redistribution of charged mobile defects that exchange infrequently with the lattice, as recently demonstrated for pile-up of isotopic oxygen near rutile TiO{sub 2} (110). The present work derives a mathematical model to describe such redistribution and establishes its temporal dependence on defect injection rate and band bending. The model shows that band bending of only a few meV induces significant redistribution, and that the direction of the electric field governs formation of either a valley or a pile-up.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Comparative study of defect levels in GaInNAs, GaNAsSb, and GaInNAsSb for high-efficiency solar cells

Background doping and defect levels in GaInNAs, GaNAsSb, and GaInNAsSb solar cells with 1 eV band-gap are reported. Localized point defect induced traps were observed showing broadest defect distribution in GaInNAsSb. Incorporation of Sb reduced the unintentional p-type background doping by an order of magnitude, but increased the capture cross sections of deep levels by three orders of magnitude. The thermal activation energy of the dominating hole trap was increased from 350 meV for GaInNAs to 560 meV for GaNAsSb. Annealing of GaNAsSb solar cells improved the open circuit voltage from 280 mV to 415 mV, owing to the reduction in trap density.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Ion velocity effect governs damage annealing process in defective KTaO 3

Effects of electronic to nuclear energy losses (S e /S n ) ratio on damage evolution in defective KTaO 3 have been investigated by irradiating pre-damaged single crystal KTaO 3 with intermediate energy O ions (6 MeV, 8 MeV and 12 MeV) at 300 K. By exploring these processes in pre-damaged KTaO 3 containing a fractional disorder level of 0.35, the results demonstrate the occurrence of a precursory stage of damage production before the onset of damage annealing process in defective KTaO 3 that decreases with O ion energy. The observed ionization-induced annealing process by ion channeling analysis has been further mirrored by high resolution transmission electron microscopy analysis. In addition, the reduction of disorder level is accompanied by the broadening of the disorder profiles to greater depth with increasing ion fluence, and enhanced migration is observed with decreasing O ion energy. Since S e (~3.0 keV nm –1 ) is nearly constant for all 3 ion energies across the pre-damaged depth, the difference in behavior is due to the so-called 'velocity effect': the lower ion velocity below the Bragg peak yields a confined spread of the electron cascade and hence an increased energy deposition density. Here, the inelastic thermal spike calculation has further confirmed the existence of a velocity effect, not previously reported in KTaO 3 or very scarcely reported in other materials for which the existence of ionization-induced annealing has been reported. In other words, understanding of ionization-induced annealing has been advanced by pointing out that ion velocity effect governs the healing of pre-existing defects, which may have significant implication for the creation of new functionalities in KTaO 3 through atomic-level control of microstructural modifications, but may not be limited to KTaO 3 .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Interaction Rates of Group-III and Group-V Impurities with Intrinsic Point Defects in Irradiated Si and Ge

A comparative study of interactions of shallow impurities with primary defects in oxygen- and carbon-lean moderately doped Si and Ge subjected to irradiation with 0.9 MeV electrons, {sup 60}Co gamma-rays, and 15 MeV protons at room temperature is presented and discussed. For the quantitative characterization of such interactions, changes in the total concentration of the original shallow group-V donor or group-III acceptor impurities in the irradiated materials are determined by Hall effect measurements over a wide temperature range. Losses of the shallow donor or acceptor states in the irradiated Si and Ge are indicative of their removal rates that can be used for estimation of production rates of primary defects interacting with the dopants. Some important factors affecting the interactions between primary defects and shallow impurities in Si and Ge are highlighted.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Suppressed Lone Pair Electrons Explain Unconventional Rise of Lattice Thermal Conductivity in Defective Crystalline Solids

Manipulating thermal properties of materials can be interpreted as the control of how vibrations of atoms (known as phonons) scatter in a crystal lattice. Compared to a perfect crystal, crystalline solids with defects are expected to have shorter phonon mean free paths caused by point defect scattering, leading to lower lattice thermal conductivities than those without defects. While this is true in many cases, alloying can increase the phonon mean free path in the Cd-doped AgSnSbSe 3 system to increase the lattice thermal conductivity from 0.65 to 1.05 W m –1 K –1 by replacing 18% of the Sb sites with Cd. It is found that the presence of lone pair electrons leads to the off-centering of cations from the centrosymmetric position of a cubic lattice. X-ray pair distribution function analysis reveals that this structural distortion is relieved when the electronic configuration of the dopant element cannot produce lone pair electrons. Furthermore, a decrease in the Grüneisen parameter with doping is experimentally confirmed, establishing a relationship between the stereochemical activity of lone pair electrons and the lattice anharmonicity. The observed “harmonic” behavior with doping suggests that lone pair electrons must be preserved to effectively suppress phonon transport in these systems.

36 MATERIALS SCIENCE↗