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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Defect specific luminescence dead layers in CdS and CdSe

CdS and CdSe are often used in optoelectronic devices whose effectiveness is may be dictated by defects in the near surface region. Luminescence is one of the main tools for studying such defects. The energy dependence of the x-ray excited optical luminescence (XEOL) spectra of these materials enables the extraction of the depth dependence of the defect distribution. Normal and time-gated XEOL spectra were obtained from these materials in the energy range 600 to 1500 eV. Here, we find that the results can best be understood in terms of a luminescence dead layer whose width depends on the position of the defect level in the band gap.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of as-received defects on ceramic matrix composites properties using high-fidelity microstructures with periodic boundary conditions

The presence of microstructural defects in as-received specimens of ceramic matrix composites (CMCs) significantly influences their constitutive response and damage, highlighting the importance of characterization and quantification of these defects for accurate assessment of damage and failure in the service environment. In a recent effort, the authors developed an algorithm to generate stochastic representative volume elements (SRVEs) of Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs based on extensive multiscale material and defect characterization data. This paper implements this algorithm within a commercial finite element solver with periodic boundary conditions (PBCs) for high-fidelity micromechanics analysis and investigation of macroscopic material behavior of C/SiNC composites. Different loading directions are used to predict the global mechanical properties, and the results are in excellent agreement with theoretical (rule of mixture) predictions. Subsequently, the effects of as-received defects on the global and local responses are investigated. The results show that intratow porosity has pronounced degradation effects on the global elastic properties and results in complex stress localization patterns, which can be attributed to potential damage initiation sites.

Khafagy, Khaled H.↗
DOE OSTI2017

The role of defects in laser-induced modifications of silica coatings and fused silica using picosecond pulses at 1053 nm: I Damage morphology

Laser-induced damage with ps pulse widths straddles the transition from intrinsic, multi-photon ionization and avalanche ionization-based ablation with fs pulses to defect-dominated, thermal-based damage with ns pulses. We investigated the morphology of damage for fused silica and silica coatings between 1 ps and 60 ps at 1053 nm. Using calibrated laser-induced damage experiments, in situ imaging, and high-resolution optical microscopy, atomic force microscopy, and scanning electron microscopy, we show that defects play an important role in laser-induced damage down to 1 ps. Three types of damage are observed: ablation craters, ultra-high density pits, and smooth, circular depressions with central pits. For 10 ps and longer, the smooth, circular depressions limit the damage performance of fused silica and silica coatings. The observed high-density pits and material removal down to 3 ps indicate that variations in surface properties limit the laser-induced damage onset to a greater extent than expected below 60 ps. Below 3 ps, damage craters are smoother although there is still evidence as seen by AFM of inhomogeneous laser-induced damage response very near the damage onset. These results show that modeling the damage onset only as a function of pulse width does not capture the convoluted processes leading to laser induced damage with ps pulses. It is necessary to account for the effects of defects on the processes leading to laser-induced damage. In conclusion, the effects of isolated defects or inhomogeneities are most pronounced above 3 ps but are still discernible and possibly important down to the shortest pulse width investigated here.

42 ENGINEERING↗
DOE OSTI2023

High external quantum efficiency (6.5%) InGaN V-defect LEDs at 600 nm on patterned sapphire substrates

Highly efficient long-wavelength InGaN LEDs have been a research focus in nitride LEDs for their potential applications in displays and solid-state lighting. A key breakthrough has been the use of laterally injected quantum wells via naturally occurring V-defects which promote hole injection through semipolar sidewalls and help to overcome the barriers to carrier injection that plague long wavelength nitride LEDs. In this article, we study V-defect engineered LEDs on (0001) patterned sapphire substrates (PSS) and GaN on (111) Si. V-defects were formed using a 40-period InGaN/GaN superlattice and we report a packaged external quantum efficiency (EQE) of 6.5% for standard 0.1 mm 2 . LEDs on PSS at 600 nm. We attribute the high EQE in these LEDs to lateral injection via V-defects.

Ewing, Jacob J.↗
DOE OSTI2026

Optical suppression of defect-related photoluminescence in GeSn

Reports of photoluminescence from GeSn grown on Ge substrates by molecular beam epitaxy have been limited. We find that one limiting factor to observing photoluminescence is due to localized defect states marked by photoluminescence at 2400 nm and originating from the Ge substrate and buffer layer. In this study, we report on an optical study utilizing doped Ge(001) substrates to effectively suppress defect-related photoluminescence in GeSn layers by filling localized defect trap states. For this experiment, a GeSn layer with Sn content up to 10.5 ± 0.5% was grown on a doped Ge(001) substrate. Analysis of the physics of the photoluminescence spectrum collected from the GeSn thin film shows an emission at the expected wavelength of 2300 nm for 10.5 ± 0.5% Sn content and the absence of the typically observed defect-related signal at 2400 nm. This understanding is further confirmed using short-pulse optical excitation of the GeSn grown on undoped Ge substrates.

Chemical vapor deposition↗
DOE OSTI2015

Nitrogen and silicon defect incorporation during homoepitaxial CVD diamond growth on (111) surfaces

Chemical Vapor Deposited (CVD) diamond growth on (111)-diamond surfaces has received increased attention lately because of the use of N-V related centers in quantum computing as well as application of these defect centers in sensing nano-Tesla strength magnetic fields. We have carried out a detailed study of homoepitaxial diamond deposition on (111)-single crystal diamond (SCD) surfaces using a 1.2 kW microwave plasma CVD (MPCVD) system employing methane/hydrogen/nitrogen/oxygen gas phase chemistry. We have utilized Type Ib (111)-oriented single crystal diamonds as seed crystals in our study. The homoepitaxially grown diamond films were analyzed by Raman spectroscopy, Photoluminescence Spectroscopy (PL), X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). The nitrogen concentration in the plasma was carefully varied between 0 and 1500 ppm while a ppm level of silicon impurity is present in the plasma from the quartz bell jar. The concentration of N-V defect centers with PL zero phonon lines (ZPL) at 575nm and 637nm and the Si-defect center with a ZPL at 737nm were experimentally detected from a variation in CVD growth conditions and were quantitatively studied. As a result, altering nitrogen and oxygen concentration in the plasma was observed to directly affect N-V and Si-defect incorporation into the (111)-oriented diamond lattice and these findings are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Point defects in semiconductors: Friends and foes for quantum technologies

Point defects in semiconductors are both a curse and a blessing in microelectronics: they enable the control of electrical conductivity through doping, yet can also act as trapping and recombination centers that degrade device performance. In quantum information science, defects play a similarly dual role. They can be harnessed as spin–photon interfaces enabling the coupling of electronic and nuclear spins to light and the creation of distributed entanglement for quantum networks or used as atomistic scale sensors for quantum sensing. At the same time, defects are a major source of decoherence for superconducting qubits, one of the leading quantum computing platforms. This article discusses how a deeper materials-level understanding of defects can guide the design of improved quantum devices for communication, sensing, and computation.

Zhu, Yizhi [Rice University, Houston, TX (United S↗
DOE OSTI2023

Charged point defect benchmark of Hybrid and GGA-PBE

Data used by the publication "High-throughput calculations of charged point defect properties with semi-local density functional theory - performance benchmarks for materials screening applications." This work presented an in-depth benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We considered three different a-posteriori correction sets for semi-local calculations, implemented in a fully automated workflow, and consider the qualitative and quantitative differences for four different categories of defect information: thermodynamic transition levels, formation energies, fermi levels, and dopability limits. We highlighted the type of qualitative information about point defect properties that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy that can be achieved by these approaches.

Broberg, Danny↗
DOE OSTI2018

Modelling Charged Defects in Non-Cubic Semiconductors for Radiation Effects Studies in Next Generation Materials

This final report summarizes the results of the Laboratory Directed Research and Development (LDRD) Project Number 212587 entitled "Modeling Charged Defects in Non-Cubic Semiconductors for Radiation Effects Studies in Next Generation Electronic Materials" . The goal of this project was to extend a predictive capability for modeling defect level energies using first principle density functional theory methods (e.g., for radiation effects assessments) to semiconductors with non-cubic crystal structures. Computational methods that proved accurate for predicting defect levels in standard cubic semiconductors, were found to have shortcomings when applied to the lowered symmetry structures prevalent in next generation electronic materials such as SiC, GaN, and Ga 2 0 3 , stemming from an error in the treatment of the electrostatic boundary conditions. I describe methods to generalized the local moment countercharge (LMCC) scheme to position a charge in bulk supercell calculations of charged defects, circumventing the problem of measuring a dipole in a periodically replicated bulk calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Structure and Voltage Recovery Driven by Defects Elimination in Li-Rich Layered Oxide Cathode Materials

Lithium-ion batteries (LIBs) are ubiquitous in a wide range of technologies, including cell phones, electric vehicles, and energy grid, and are indispensable in the transition toward sustainable energy technology. The battery performance is inherently connected to the capability of lithium ions to reversibly intercalate with the electrodes. The capacity of classical layered transition metal (TM) oxides, the primary commercial cathode materials, is limited to cationic redox activity. Anionic redox has thus emerged as a new paradigm for designing novel cathodes for next generation LIBs. It is recently confirmed oxygen redox in lithium-rich layered oxides (LRLO) with composition xLi 2 MnO 3 ∙(1-x)LiTMO 2 , which enables this group of materials exhibit reversible capacities exceeding 280 mAh g -1 . Unfortunately, this material undergoes voltage fading and instability that is rooted in irreversible structural transformation in terms of defects formation including lithium and oxygen vacancies, lithium tetrahedron, TM migration, edge dislocations, stacking fault, and local strain. Modification methods including morphology control, composition gradient, surface treatment, foreign elements doping, etc., have been proposed in the literatures to mitigate the defects formation and maintain the structure reversibility. Despite their improvement, the intrinsic voltage fading is still inevitable and remains a challenge that will require considerable effort to overcome. In this work, we demonstrate a path to recover the layer structure and working voltage through high-temperature annealing. The treatment at high temperature recovers the local Li-excess environments around oxygen, oxygen stacking sequence, and eliminates microstrain associated with different defects. As a result, the voltage profile once more shows plateau region during charge and the average discharge voltage is restored of the cycled cathode after heat treatment. Both theoretical calculations and experimental characterizations illustrate the mechanisms underlying the heating induced recovery. The structure metastability and defects removal are decisive in structure and voltage recovery of LRLO cathode material.

Zhang, Minghao↗
DOE OSTI2022

Ellipsoidal Fitting Methodology for Defect Clusters in Gallium Arsenide

In assessing the initial spatial distribution of defects from neutron or heavy ion irradiation, it is useful to have a reliable, automated, and fast-running tool to evaluate characteristic metrics such as the number of sub-clusters or the overall cluster volume. The latter metric, for instance, can be utilized to estimate a reference neutron fluence level at which inter-cluster interaction effects begin to become significant. This paper details a methodology to fit an arbitrarily complex defect map with a set of ellipsoids (one per identified sub-cluster) in which the constituent defects of a sub-cluster are determined using fuzzy degree-of-membership analysis. Specifically, a parameterized model is developed for point defects in gallium arsenide. Cluster volume calculations based on the model are compared against convex hull and single- ellipsoid representations. Results show that the parameterized sub-cluster model begins to deviate from the two reference models at a recoil energy of about 100 keV in GaAs, with the convex hull and single-ellipsoid representations increasingly overestimating the volume thereafter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Automatic Detection of Defects in High-Reliability Components

Disastrous consequences can result from defects in manufactured parts—particularly the high consequence parts developed at Sandia. Identifying flaws in as-built parts can be done with nondestructive means, such as X-ray Computed Tomography (CT). However, due to artifacts and complex imagery, the task of analyzing the CT images falls to humans. Human analysis is inherently unreproducible, unscalable, and can easily miss subtle flaws. We hypothesized that deep learning methods could improve defect identification, increase the number of parts that can effectively be analyzed, and do it in a reproducible manner. We pursued two methods: 1) generating a defect-free version of a scan and looking for differences (PandaNet), and 2) using pre-trained models to develop a statistical model of normality (Feature-based Anomaly Detection System: FADS). Both PandaNet and FADS provide good results, are scalable, and can identify anomalies in imagery. In particular, FADS enables zero-shot (training-free) identification of defects for minimal computational cost and expert time. It significantly outperforms prior approaches in computational cost while achieving comparable results. FADS’ core concept has also shown utility beyond anomaly detection by providing feature extraction for downstream tasks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Generalized kinetic model for defect evolution in irradiated materials

A fundamental and open problem in materials science is to determine how the structural properties of irradiated and self-irradiated materials evolve in time. Structural defects generated by irradiation lead to changes in a material’s macroscopic properties, and these macroscopic changes, such as volumetric swelling, can in turn give rise significant alterations of the functionality of a material. Here, we develop a unified analytical model to understand the complex interplay between aggregation, fragmentation, and recombination processes involving mobile clusters of defects such as bubbles, voids, and interstitial atoms in materials subject to radiative sources. Specifically, we employ a mean field approach to derive a system of coupled kinetic equations that describes both the time evolution of the density of each type of defect and how clusters of each defect form and grow as the material ages.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Approach and rotation of reconnecting topological defect lines in liquid crystal

Topological defects are a universal concept across many disciplines, such as crystallography, liquid-crystalline physics, low-temperature physics, cosmology, and even biology. In nematic liquid crystals, topological defects called disclinations have been widely studied. For their three-dimensional (3D) dynamics, however, only recently have theoretical approaches dealing with fully 3D configurations been reported. Further, recent experiments have observed 3D disclination line reconnections, a phenomenon characteristic of defect line dynamics, but detailed discussions were limited to the case of approximately parallel defects. In this paper, we focus on the case of two disclination lines that approach at finite angles and lie in separate planes, a more fundamentally 3D reconnection configuration. Observing and analyzing such reconnection events, we find the square-root law of the distance between disclinations and the decrease of the interdisclination angle over time. We compare the experimental results with theory and find qualitative agreement on the scaling of distance and angle with time, but quantitative disagreement on distance and angle relative mobilities. To probe this disagreement, we derive the equations of motion for systems with reduced twist constant and also carry out simulations for this case. These, together with the experimental results, suggest that deformations of disclinations may be responsible for the disagreement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Defect Detection Model Development for Large Scale Thermoplastic Printing

Large-format additive manufacturing (LFAM) offers several advantages, including high throughput, cost-effective pellet-fed extrusion, and the capability to produce large-scale structures. The main pain points of LFAM include start and stops during the printing process, warpage, long layer times that lead to bead freezing, and bead separation due to shrinkage. These issues can lead to overfill, underfill and buildup of material in different sections of a print. This can lead to hidden defects embedded within the printed layers, or even ultimate failure of the printed structure. This ensures these defects can only be identified through nondestructive testing (NDT) inspection methods after printing, which can be timely and costly. Aligned Vision work specializes in 2D projectors with visual inspection systems and machine learning. Traditionally system is used for composite layup and layup inspections. In this work we used the LFAM system at Oak Ridge National Laboratory to create defect rich samples. The Aligned Vision inspection system then performed in-situ monitoring of the print process after each part was printed. This in-situ vision inspection system was used to develop a layer-by-layer inspection model that looks for overfill, underfill, and the buildup of defects using only a camera-based vision system. This leads to the assurance of high-quality production components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Establishing defect-property relationships for 2D-nanomaterials (Final technical report)

Studies of new families of two-dimensional nanomaterials (2DNMs) have established that they possess unique properties that diverge from those of their bulk counterparts. This project aimed to determine how tolerant 2DNMs are to extreme photon and particle fluxes and to identify the mechanisms governing their radiation response. Early work indicated that graphene is not as representative of other 2DNMs as previously assumed; however, the origin of this difference remained unclear. To address these knowledge gaps, this project investigated the physical processes occurring at multiple length scales in transition metal dichalcogenides (TMDs) and quantified their structural stability and property evolution under far-from-equilibrium conditions. In-situ and ex-situ ion and electron irradiations were performed to directly control and monitor defect formation in TMDs. Complementary density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate the mechanisms of defect generation and evolution. The outcomes of this work established mechanistic understanding of irradiation-induced defect formation in 2DNMs, quantified the radiation tolerance of TMDs, and built a fundamental knowledge base for correlating defect structures with material properties. Collectively, these results provide new insights into the stability of low-dimensional materials in extreme environments and enable the predictive design of radiation-tolerant 2DNMs.

2D materials↗
DOE OSTI2025

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms​ ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗