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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Characterization of dangling bond defects at the crystalline Si/SiO x interface in a polycrystalline Si passivating contact solar cell at room temperature with electrically detected magnetic resonance spectroscopy

Monocrystalline silicon solar cells can achieve photoconversion efficiencies exceeding 26%; however, performance-limiting defects that trap carriers continue to be a challenge. In this work, we have characterized Si solar cells with tunneling SiO x /polycrystalline-Si (poly-Si) passivating contacts (TOPCon) on As-doped Czochralski Si wafers with electrically detected magnetic resonance (EDMR) spectroscopy. We fabricated 2 × 20 mm 2 TOPCon-like mini solar cells with edge passivation alongside larger 4 cm 2 sister cells and obtained similar device characteristics. We performed EDMR spectroscopy at 300 K on two minicells with different degrees of surface passivation based on the recombination parameter, J o , values of 40 and 310 fA/cm2. We optimized the resolution and the signal-to-noise ratio of the EDMR response of the minicells by varying the forward bias voltage and the magnetic field modulation amplitude. We detect two distinct signals with EDMR spectroscopy, an axial-like signal at g = 2.009, 2.0087, and 2.0015, and an isotropic signal at g = 2.0024, which we attribute to Si dangling bonds (P b0 and P b centers) and boron–oxygen related defects, respectively, at or near the c-Si/SiO x interface. The EDMR signals were lower for the cell with a lower value of J o , while the ratio of the two defect populations was very similar. The EDMR signal increases with forward bias but drops to zero at bias voltages >0.5 V, consistent with interface defects within or near the boron-doped emitter depletion region. Our study demonstrates a method to fabricate minicells that can be characterized with EDMR spectroscopy to detect industrially relevant defects in TOPCon cells.

14 SOLAR ENERGY↗
DOE OSTI2025

Review of radiation-induced defects in GaAs

Radiation-resilient optoelectronic materials are highly desired in space and nuclear applications, and understanding the relevant defects and electronic processes in those materials is crucial for both current and next-generation applications. GaAs is a prototypical semiconductor that serves as a foundational system for describing and understanding optoelectronic devices. In this review, both experimental studies and molecular dynamics (MD) simulations of irradiated GaAs are reviewed, with particular emphasis on the deep-level transient spectroscopy, irradiation-induced amorphization zones, and MD predictions of damage structures. The MD results are also compared to predictions of the non-ionized energy-loss model. Recent theoretical studies, in particular, density functional theory based calculations on the simple intrinsic defects and defect clusters in GaAs, are also reviewed. These defects have an important role in dictating the evolution of GaAs in radiation damage environments, as they impact the coupled dynamics of charge carriers. Finally, possible gaps and challenges toward the general understanding of defect evolution in GaAs are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Skyrmions Near Defects

We study the impact of an exchange-reducing defect on a skyrmion for a thin film of finite thickness. Attraction of the skyrmion to a defect is demonstrated in a lattice model by computing the micromagnetic energy accounting for the exchange, Dzyaloshinskii-Moriya interaction, magnetic anisotropy, and dipole-dipole coupling. The spiraling dynamics of the skyrmion towards the defect is illustrated by solving numerically the full Landau-Lifshitz-Gilbert equations on a lattice and, independently, the Thiele equation, with the two methods in agreement with each other. We find that the skyrmion deforms when approaching the defect. Here, deformation is small in the parameter space far from the phase boundary that determines stability of skyrmions. It increases dramatically near the phase boundary, leading to the transformation of the skyrmion by the defect into a snake-like magnetic domain.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The role of defect charge, crystal chemistry, and crystal structure on positron lifetimes of vacancies in oxides

Density functional theory based positron lifetime (PL) calculations for cation and oxygen monovacancies in a range of oxides—hematite, magnetite, hercynite, and alumina—have been conducted to compare the impact of defect chemistry and crystal structure on the predicted lifetimes. The role of defect charge state has also been examined. A comparison across the same type of crystalline structure but different composition shows that oxygen vacancies only induce a slight increase in the positron-electron overlap and thus barely modify the PL as compared to the bulk. A much more substantial increase of PL is observed for cation monovacancies, regardless of crystal structure or the elemental nature of the vacancy, which we ascribe to an enhanced localization of charge density around the vacant site. The structural and compositional richness of the oxide leads to longer defect PLs, with defected hercynite exhibiting the longest PLs. The charge state of cation monovacancies modifies only by a small percentage the positron localization, relegating to secondary importance the metal defect's oxidation state in modifying the lifetime of positrons within vacancy traps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Deterministic nanoscale quantum spin-defect implantation and diffraction strain imaging

Abstract Local crystallographic features negatively affect quantum spin defects by changing the local electrostatic environment, often resulting in degraded or varied qubit optical and coherence properties. Few tools exist that enable the deterministic synthesis and study of such intricate systems on the nano-scale, making defect-to-defect strain environment quantification difficult. In this paper, we highlight state-of-the-art capabilities from the U.S. Department of Energy’s Nanoscale Science Research Centers that directly address these shortcomings. Specifically, we demonstrate how complementary capabilities of nano-implantation and nano-diffraction can be used to demonstrate the quantum relevant, spatially deterministic creation of neutral divacancy centers in 4H silicon carbide, while investigating and characterizing these systems on the ≤ 25 nm scale with strain sensitivities on the order of 1 × 10 − 6 , relevant to defect formation dynamics. This work lays the foundation for ongoing studies into the dynamics and deterministic formation of low strain homogeneous quantum relevant spin defects in the solid state.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Thermokinetics of point defects in α-Fe 2 O 3

Abstract Point defect formation and migration in oxides governs a wide range of phenomena from corrosion kinetics and radiation damage evolution to electronic properties. In this study, we examine the thermodynamics and kinetics of anion and cation point defects using density functional theory in hematite ( α -Fe 2 O 3 ), an important iron oxide highly relevant in both corrosion of steels and water-splitting applications. These calculations indicate that the migration barriers for point defects can vary significantly with charge state, particularly for cation interstitials. Additionally, we find multiple possible migration pathways for many of the point defects in this material, related to the low symmetry of the corundum crystal structure. The possible percolation paths are examined, using the barriers to determine the magnitude and anisotropy of long-range diffusion. Our findings suggest highly anisotropic mass transport in hematite, favoring diffusion along the c -axis of the crystal. In addition, we have considered the point defect formation energetics using the largest Fe 2 O 3 supercell reported to date.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗
DOE OSTI2026

Defect in diamond with millisecond-scale spin relaxation time at room temperature

Spin defects in diamond are promising platforms for quantum sensing. The longest electron spin relaxation times (T1) at room temperature for solid-state defects are observed in nitrogen vacancy centers in diamond, which can reach 6.67 ms [1], and substitutional nitrogen (“P1 centers”) in diamond, which exhibit a T1 of 2 ms [2]. No other solid-state defect has exhibited millisecond-scale spin relaxation times at room temperature thus far. Here, we characterize the spin properties of the WAR5 defect in diamond [3] with pulsed electron spin resonance. The observed T1 is one of the longest for solid-state spin defects: 0.97(27) ms at room temperature and 14.38(19) min at 4 K. The observed coherence time (T2) is 246(7) µs, which can be extended to 6.49(34) ms at 4 K with dynamical decoupling. Finally, we demonstrate optical spin polarization with a range of wavelengths from 405 nm to 500 nm and propose potential zero-phonon line candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Point defect induced incommensurate dipole moments in the K Ca 2 Nb 3 O 10 Dion-Jacobson layered perovskite

Local structural distortions due to isolated atomic defects and defect complexes strongly affect the macroscopic properties of oxide ceramics. While the characterization of local defect structures is more common in simple AB O 3 perovskites, unambiguous determination of the same in layered perovskites is more difficult due to their complex crystal structures. In this study, we combined x-ray pair distribution function and density functional theory calculations to characterize the structure of cation-oxygen divacancy pairs in a Dion-Jacobson (D-J) layered perovskite. Our results indicate that local incommensurate dipole moments with polarization density in the range of ~ 0.1–17μC/cm 2 are created due to divacancy-induced structural distortions in the D-J phase K Ca 2 Nb 3 O 10 . This is comparable with defect dipole moments observed in well-known perovskite ferroelectrics. The current results imply that controlling the atomic defects can potentially lead to significant control of dielectric properties in D-J layered perovskites.

3-dimensional systems↗
DOE OSTI2022

Humble planar defects in SiGe nanopillars

We report a {001} planar defect found in SiGe nanopillars. The defect structure, determined by atomic-resolution electron microscopy, matches the Humble defect model proposed for diamond. We also investigate several possible variants of the Humble structure using first-principles calculations and find that the one lowest in energy is in agreement with the scanning transmission electron microscope images. The pillar composition has been analyzed with electron energy loss spectroscopy, which hints at how the defect is formed. Our results show that the structure and formation process of defects in nanostructured group IV semiconductors can be different from their bulk counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theory of topological defects and textures in two-dimensional quantum orders with spontaneous symmetry breaking

In this article, we consider two-dimensional (2d) quantum many-body systems with long-range orders, where the only gapless excitations in the spectrum are Goldstone modes of spontaneously broken continuous symmetries. To understand the interplay between classical long-range order of local order parameters and quantum order of long-range entanglement in the ground states, we study the topological point defects and textures of order parameters in such systems. We show that the universal properties of point defects and textures are determined by the remnant symmetry enriched topological order in the symmetry-breaking ground states with a nonfluctuating order parameter, and provide a classification for their properties based on the inflation-restriction exact sequence. We highlight a few phenomena revealed by our theory framework. First, in the absence of intrinsic topological orders, we show a connection between the symmetry properties of point defects and textures to deconfined quantum criticality. Second, when the symmetry-breaking ground state has intrinsic topological orders, we show that the point defects can permute different anyons when braided around. They can also obey projective fusion rules in the sense that multiple vortices can fuse into an Abelian anyon, a phenomenon for which we coin “defect fractionalization.” Finally, we provide a formula to compute the fractional statistics and fractional quantum numbers carried by textures (skyrmions) in Abelian topological orders.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Localized excitons in defective monolayer germanium selenide

Germanium selenide (GeSe) is a van der Waals–bonded layered material with promising optoelectronic properties, which has been experimentally synthesized for two-dimensional (2D) semiconductor applications. In the monolayer, due to reduced dimensionality and, thus, screening environment, perturbations such as the presence of defects have a significant impact on its properties. We apply density functional theory and many-body perturbation theory to understand the electronic and optical properties of GeSe containing a single selenium vacancy in the –2 charge state. We predict that the vacancy results in midgap “trap states” that strongly localize the electron and hole density and lead to sharp, low-energy optical absorption peaks below the predicted pristine optical gap. Analysis of the exciton wave function reveals that the 2D Wannier-Mott exciton of the pristine material monolayer is strongly modified by the presence of the defect. The lowest-energy exciton wave function is highly localized around the defect, with the Bohr radius reduced by a factor of 4 when compared to the pristine material and a dipole moment along the out-of-plane axis due to the defect-induced symmetry breaking. Altogether, these results suggest that the vacancy significantly modifies the excitonic properties of the system, demonstrating the importance of considering defects in the context of material design.

2-dimensional systems↗
DOE OSTI2024

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗
DOE OSTI2024

Coupled Process/Device Modeling and Point Defect Engineering of Cu(In,Ga)Se 2 Solar Cells

Point defects directly impact solar cell device performance by limiting the carrier lifetime. In this work, density functional theory calculations are first used to determine the formation energy and diffusion energy barriers of dominant defects in Cu(In,Ga)Se 2 . Next, continuum reaction–diffusion models are developed to analyze the redistribution of defects during manufacturing processes. We estimate defect capture cross sections using a first-principles-based approach. Here, these cross sections are combined with our calculated defect profiles and trap energy levels to parameterize a Shockley–Read–Hall recombination model, which we implement into a device simulator to predict carrier lifetimes and device performance. In that way, a predictive technology computer aided design model is built to predict and optimize the performance of Cu(In,Ga)Se 2 solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

High-fidelity micromechanical modeling of the effects of defects on damage and creep behavior in single tow ceramic matrix composite

Despite the superior properties of ceramic matrix composites (CMCs), their fabrication process generates inevitable defects with high density that significantly influence material integrity and residual useful life. Recent efforts have focused on CMC property prediction and investigation of their different inelastic mechanisms, but very limited work exists on understanding the influence of defects on inelastic responses of CMCs. Here, we introduce a three-dimensional micromechanics computational framework that includes experimentally informed material microstructure and architectural variabilities to investigate CMC response in the presence of manufacturing-induced defects. A developed microstructure generation algorithm is used to generate the representative volume elements in the micromechanics models from complex material morphology information obtained from extensive characterization studies of C/SiNC and SiC/SiNC CMCs. A fracture mechanics-informed matrix damage model is reformulated, in which the model considers the growth of porosity and microcracks in the as-received material. A progressive fiber damage model as well as Orthotropic viscoplasticity creep formulation are also utilized for the study. This methodology is implemented within the micromechanics framework to investigate the complex temperature- and time-dependent load transfer and damage mechanisms of CMCs under operation loading conditions. The developed framework explores the influence of as-received defects on the damage and creep behavior in service conditions. It also provides new insights into the effect of size, shape, distribution, and location of these defects on material response. The framework is then calibrated with unidirectional CMC minicomposite results available in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of a MOOSE-based crystal plasticity model with irradiation defect evolution for irradiation creep in 316

Irradiation creep and irradiation swelling are two of the lifetime limiting factors for structural materials in nuclear reactors. These mechanical effects are driven by irradiation defect evolution and the interaction of those defects with dislocations in the microstructure. We present here a coupled cluster dynamics – crystal plasticity approach to model irradiation swelling and creep behavior in 316 SS. The time-dependent evolution of irradiation defects is calculated with a cluster dynamics approach and passed to the crystal plasticity model to compute the dislocation evolution. We show the impact of the irradiation defect evolution on the stress state in the material, which drives inelastic deformation through dislocation motion. The inelastic deformation in the 316 SS is dependent on the dose rate, where the inelastic deformation driven by the early-stage irradiation defect evolution determines the mechanical behavior of the 316 SS.

316 Stainless Steels↗
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗
DOE OSTI2020

Characterizing Dislocation Defects in Dark Field X-ray Microscopy Images of Bulk Aluminum

Material defects play a large role in material response under shock loading, yet the process of how these defects initiate, propagate, and annihilate is not well understood. Using a newly developed diagnostic, dark field X-ray microscopy (DFXM), we can now visualize the behavior of dislocation defects in materials at the mesoscale under varying conditions. Using data from the European Synchrotron Radiation Facility, we apply a variety of image processing techniques to capture relevant features to locate and characterize size and orientation of dislocation defects in bulk aluminum DFXM images. Beyond simple visualization, this analysis drives statistical characterization of the defects and their dynamic response to further improve the relevant physics models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗