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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Incorporating point defect generation due to jog formation into the vector density-based continuum dislocation dynamics approach

During plastic deformation of crystalline materials, point defects such as vacancies and interstitials are generated by jogs on moving dislocations. A detailed model for jog formation and transport during plastic deformation was developed within the vector density-based continuum dislocation dynamics framework. Here as a part of this model, point defect generation associated with jog transport was formulated in terms of the volume change due to the non-conservative motion of jogs. Balance equations for the vacancies and interstitials including their rate of generation due to jog transport were also formulated. A two-way coupling between point defects and dislocation dynamics was then completed by including the stress contributed by the eigen-strain of point defects. A jog drag stress was further introduced into the mobility law of dislocations to account for the energy dissipation during point defects generation. A number of test problems and a fully coupled simulation of dislocation dynamics and point defects generation and diffusion were performed. The results show that there is an asymmetry of vacancy and interstitial generation due to the different formation energies of the two types of defects. The results also show that a higher hardening rate and a higher dislocation density are obtained when the point defect generation mechanism is coupled to dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

First-principles determination of the phonon-point defect scattering and thermal transport due to fission products in ThO 2

This work presents the first-principles calculations of the lattice thermal conductivity degradation due to point defects in thorium dioxide using an iterative solution of the Pierels-Boltzmann transport equation. We have used the non perturbative Green’s function methodology to compute the phonon- point defect scattering rates that consider the local distortion around the point defect, including the mass difference changes, interatomic force constants, and structural relaxation near the point defects. The point defects considered in this work include the vacancy of thorium ($V$ $TH$ ) and oxygen ($V$ $O$ ), substitutions of helium ($He$ $Th$ ), krypton ($Kr$ $Th$ ), zirconium ($Zr$ $Th$ ), iodine ($I$ $Th$ ) and xenon ($Xe$ $Th$ ) in the thorium site, and the three different configurations of the Schottky defects. The results of the phonon-defect scattering rate reveal that, among all the considered intrinsic defects, the thorium vacancy and helium substitution in the thorium site scatter the phonon most due to the substantial changes in the force constant and structural distortions. The scattering of phonons due to the substitutional defects unveils that the zirconium atom scatters phonons the least, followed by xenon, iodine, krypton, and helium. This is contrary to the intuition that the scattering strength follows $He$ $Th$ > $Kr$ $Th$ > $Zr$ $Th$ > $I$ $Th$ > $Xe$ $Th$ based on the mass difference. This striking difference in the zirconium phonon scattering is due to the local chemical environment changes. Zirconium is an electropositive element with valency similar to thorium and, therefore, can bond with the oxygen atoms, thus creating less force constant variance compared to iodine, an electronegative element noble gas helium, xenon, and krypton. In conclusion, these results can serve as the benchmark for the analytical models and help the engineering-scale modeling effort for nuclear design.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Concentration of point defects in 4H-SiC characterized by a magnetic measurement

A magnetic method is presented to characterize the concentration of point defects in silicon carbide. In this method, the concentration of common charged point defects, which is related to the density of paramagnetic centers, is determined by fitting the paramagnetic component of the specimen to the Brillouin function. Several parameters in the Brillouin function can be measured such as: the g-factor can be obtained from electron spin resonance spectroscopy, and the magnetic moment of paramagnetic centers can be obtained from positron lifetime spectroscopy combined with a first-principles calculation. To evaluate the characterization method, silicon carbide specimens with different concentrations of point defects are prepared with aluminum ion implantation. The fitting results of the densities of paramagnetic centers for the implanted doses of 1 × 10{sup 14} cm{sup −2}, 1 × 10{sup 15} cm{sup −2} and 1 × 10{sup 16} cm{sup −2} are 6.52 × 10{sup 14}/g, 1.14 × 10{sup 15}/g and 9.45 × 10{sup 14}/g, respectively. The same trends are also observed for the S-parameters in the Doppler broadening spectra. It is shown that this method is an accurate and convenient way to obtain the concentration of point defects in 4H-SiC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Perspectives on deterministic control of quantum point defects by scanned probes

Control over individual point defects in solid-state systems is becoming increasingly important, not only for current semiconductor industries but also for next generation quantum information science and technologies. To realize the potential of these defects for scalable and high-performance quantum applications, precise placement of defects and defect clusters at the nanoscale is required, along with improved control over the nanoscale local environment to minimize decoherence. These requirements are met using scanned probe microscopy in silicon and III-V semiconductors, which suggests the extension to hosts for quantum point defects such as diamond, silicon carbide, and hexagonal boron nitride is feasible. Here we provide a perspective on the principal challenges toward this end, and new opportunities afforded by the integration of scanned probes with optical and magnetic resonance techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

In Situ Optical Absorption Studies of Point Defect Kinetics and Thermodynamics in Oxide Thin Films

The authors discuss the use of in situ optical absorption to probe point defect equilibria and kinetics in oxides, with particular attention to thin films and high-temperature measurements evaluating changes in oxygen content. The introduction notes the effect of point defects on oxide behavior, including differences in thin films versus bulk materials, and describes methods to evaluate point defect equilibria and kinetics; advantages of optical absorption among these methods are highlighted. Section 2 provides an overview of how optical absorption and point defect concentrations are related, including various possible structural and electronic origins of defect-mediated absorption changes corresponding to oxygen content changes. Section 3 traces the development of historical understanding of optical absorption in nonstoichiometric oxides and emergence of thin film applications and measurement approaches that resulted. Section 4 details the procedure for determining surface exchange coefficients from optical transmission relaxation measurements and provides specific examples of how this approach uniquely has enabled new insights into thin film surface exchange behavior with and without current collectors. Section 5 provides examples of optically derived diffusivity measurements and comparisons of bulk and thin film defect equilibria. Section 7 outlines potential opportunities and future developments in this area, and Section 7 concludes the manuscript.

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. 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 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

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. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗
DOE OSTI2018

First-Principles Study of Intrinsic and Extrinsic Point Defects in Lead-Based Hybrid Perovskites.

Intrinsic and extrinsic defects play a major role in determining solar cell efficiencies of lead halide hybrid perovskite absorbers. Here, we present the results of first-principles computations performed on MAPbBr3 (MA = methylammonium) to study the energetics and defect levels of intrinsic point defects, namely vacancy, self-interstitial and anti-site, and extrinsic Pb-substitution defects. While vacancies are the lowest formation energy intrinsic defects and create shallow transition levels, a number of extrinsic defects can have comparable formation energies under desirable chemical potential conditions. therefore, carrier concentrations may be tunable with these substituents. Further, some extrinsic defects create deeper transition levels which can potentially be exploited to enhance solar cell efficiencies via sub-gap absorption.

density functional theory↗
DOE OSTI2021

Tuning Point Defects by Elastic Strain Modulates Nanoparticle Exsolution on Perovskite Oxides

Exsolution generates stable and catalytically active metal nanoparticles via phase precipitation out of a host oxide. An ability to control the size and dispersion of the exsolution particles is desirable for design of nanostructured (electro)catalysts. In this work, we demonstrate that tuning point defects by lattice strain affects both the thermodynamics and the kinetics of iron (Fe 0 ) exsolution on La 0.6 Sr 0.4 FeO 3 (LSF) thin film model. By combining in situ surface characterization and ab initio defect modeling, we show oxygen vacancy and Schottky defects to be the primary point defects formed upon Fe0 exsolution. Lattice strain tunes the formation energy, and thus the abundance of these defects, and alters the amount and size of the resulting exsolution particles. In addition, we find that the density of exsolved nanoparticles matches the concentration of oxygen vacancy pairs, thus pointing to the surface oxygen vacancy pairs as preferential nucleation sites for exsolution. The tensile-strained LSF with a facile formation of these critical point defects results in a higher Fe 0 metal concentration, a larger density of nanoparticles, and a reduced particle size at its surfaces. These results provide important mechanistic insights and highlight the role of point-defect engineering in designing nanostructured catalysts in energy and fuel conversion technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A novel approach to quantifying the kinetics of point defect absorption at dislocations

We report that microstructure evolution under creep loading and/or irradiation is largely affected by the two-way coupling between dislocation induced plasticity and point defect diffusion as mediated by the internal elastic strain field within the medium. The magnitude of this effect has been quantified only in idealized, simplified environments such that estimates of absorption rates of point defects to dislocations ignore the collective effects on capture rates arising from particular distribution of dislocations in a given network, the interaction of point defects with the internal strain, or in many cases both. To quantify these effects, we advance a novel methodology to determine point defect capture rates locally within a spatially resolved finite difference solution to the diffusion problem for arbitrarily directed dislocations and the corresponding strain fields. In addition to examining the effects of these couplings on local and effective absorption rates of dislocation networks, the potential consequences of these interactions on other microstructure evolution phenomena are examined using void swelling under irradiation as an example. Our study indicates that local rates of defect mediated microstructural changes such as cavity growth can vary strongly as a consequence of the arrangement of the dislocation network and the corresponding strain state. Lastly, the heterogeneous aspects of the resultant defect populations are shown to provide mechanisms for microstructural evolution under irradiation that are not available in the conventional homogeneous theory.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identifying native point defect configurations in α-alumina

Intimately intertwined atomic and electronic structures of point defects govern diffusion-limited corrosion and underpin the operation of optoelectronic devices. For some materials, complex energy landscapes containing metastable defect configurations challenge first-principles modeling efforts. Here, we thoroughly reevaluate native point defect geometries for the illustrative case of α-Al 2 O 3 by comparing three methods for sampling candidate geometries in density functional theory calculations: displacing atoms near a naively placed defect, initializing interstitials at high-symmetry points of a Voronoi decomposition, and Bayesian optimization. We find symmetry-breaking distortions for oxygen vacancies in some charge states, and we identify several distinct oxygen split-interstitial geometries that help explain literature discrepancies involving this defect. We also report a surprising and, to our knowledge, previously unknown trigonal geometry favored by aluminum interstitials in some charge states. Importantly, these new configurations may have transformative impacts on our understanding of defect migration pathways in aluminum-oxide scales protecting metal alloys from corrosion. Overall, the Voronoi scheme appears most effective for sampling candidate interstitial sites because it always succeeded in finding the lowest-energy geometry identified in this study, although no approach found every metastable configuration. Finally, we show that the position of defect levels within the band gap can depend strongly on the defect geometry, underscoring the need to conduct careful searches for ground-state geometries in defect calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1997

Lithium-ion drifting: Application to the study of point defects in floating-zone silicon

The use of lithium-ion (Li(+)) drifting to study the properties of point defects in p-type Floating-Zone (FZ) silicon crystals is reported. The Li(+) drift technique is used to detect the presence of vacancy-related defects (D defects) in certain p-type FZ silicon crystals. SUPREM-IV modeling suggests that the silicon point defect diffusivities are considerably higher than those commonly accepted, but are in reasonable agreement with values recently proposed. These results demonstrate the utility of Li(+) drifting in the study of silicon point defect properties in p-type FZ crystals. Finally, a straightforward measurement of the Li(+) compensation depth is shown to yield estimates of the vacancy-related defect concentration in p-type FZ crystals.

Silicon↗
DOE OSTI2025

Revisiting point defect thermodynamics in group IVB and VB transition metal carbides

We present a comprehensive re-examination of point defect thermodynamics in group IVB and VB transition metal carbides (TMCs) with the rocksalt structure using a combination of density functional theory (DFT) calculations and a statistical mechanical Wagner-Schottky model within the canonical ensemble. The most stable configurations of point defects were discovered using basin-hopping global optimization, driven by either a machine learning interatomic potential (MLIP) or DFT. A key finding is the identification of previously unreported dicarbon antisites—a C–C dimer occupying a metal site—as the structural (constitutional) defects on the carbon-rich side of stoichiometry in all group IVB and VB TMCs except TaC. Furthermore, dicarbon antisite-containing thermal defect complexes, such as quadruple and interbranch defects, can dominate in TMCs under specific stoichiometric and temperature conditions. In conclusion, by incorporating dicarbon antisites into the defect landscape, this work provides a revised understanding of the thermodynamics of point defects in TMCs.

Carbides↗
DOE OSTI2021

Density functional theory calculations of the thermodynamic and kinetic properties of point defects in β -U

Density functional theory (DFT) calculations of the thermodynamic and kinetic properties of point defects in the β phase of uranium are reported. Defect energies and entropies were calculated using 2 x 2 x 2 supercells and the Generalized Gradient Approximation (GGA) of Perdew-Burke-Ernzerhof (PBE) for the exchange-correlation potential. Due to computational cost, calculations of the vibrational properties governing entropies were performed by only displacing atoms within (roughly) the 3rd or 4th nearest neighbor shell of the defect, which implicitly assumes that atoms beyond this distance are unaffected by the defect. Migration barriers were estimated by nudged elastic band (NEB) calculations. The low symmetry of the β-U phase (the unit cell is tetragonal and contains 30 atoms) results in many point defect configurations and even more migration pathways. A connectivity map, starting from the most stable point defects, was developed in order to identify the rate-limiting step controlling the net diffusion rate in each crystallographic direction. The uranium self-diffusivity tensor was calculated by combining the defect formation energies, entropies, migration barriers and attempt frequencies. The fastest diffusion rate was determined to be a vacancy mechanism in the z crystallographic direction. The predicted uranium self-diffusivity for this mechanism agrees well with available experimental data. Finally, the diffusion mechanisms and rates identified in this study will inform fuel performance models of swelling and gas evolution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Native point defects in HgCdTe infrared detector material: Identifying deep centers from first principles

We investigate the native point defects in the long-wavelength infrared (LWIR) detector material Hg0.75Cd0.25Te using a dielectric-dependent hybrid density functional combined with spin–orbit coupling. Characterizing these point defects is essential as they are responsible for intrinsic doping and nonradiative recombination centers in the detector material. The dielectric-dependent hybrid functional allows for an accurate description of the bandgap (Eg) for Hg1−xCdxTe (MCT) over the entire compositional range, a level of accuracy challenging with standard hybrid functionals. Our comprehensive examination of the native point defects confirms that cation vacancies VHg(Cd) are the primary sources of p-type conductivity in the LWIR material given their low defect formation energies and the presence of a shallow acceptor level (−/0) near the valence-band maximum. In addition to the shallow acceptor level, the cation vacancies exhibit a deep charge transition level (2−/−) situated near the midgap, characteristic of nonradiative recombination centers. Our results indicate that Hg interstitial could also be a deep center in the LWIR MCT through a metastable configuration under the Hg-rich growth conditions. While an isolated Te antisite does not show deep levels, the formation of VHg–TeHg defect complex introduces a deep acceptor level within the bandgap.

Physics↗
DOE OSTI2017

Hybrid functional study of native point defects and impurities in ZnGeN 2

Using hybrid density functional theory, we explore the properties of native point defects and hydrogen and oxygen impurities in ZnGeN 2 , a wide-band-gap semiconductor that is promising for applications in electronic and optoelectronic devices. We find that cation antisites have the lowest formation energies amongst all of the native point defects for a wide range of chemical potential conditions. Yet, native point defects must not act as sources of doping. Unintentional n-type conductivity in ZnGeN 2 must be attributed to impurities: substitutional oxygen on a nitrogen site and interstitial hydrogen act as donors.

36 MATERIALS SCIENCE↗