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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Quantitative Principles for Precise Engineering of Sensitivity in Graphene Electrochemical Sensors

Abstract A major difficulty in implementing carbon‐based electrode arrays with high device‐packing density is to ensure homogeneous and high sensitivities across the array. Overcoming this obstacle requires quantitative microscopic models that can accurately predict electrode sensitivity from its material structure. Such models are currently lacking. Here, it is shown that the sensitivity of graphene electrodes to dopamine and serotonin neurochemicals in fast‐scan cyclic voltammetry measurements is strongly linked to point defects, whereas it is unaffected by line defects. Using the physics of point defects in graphene, a microscopic model is introduced that explains how point defects determine sensitivity. The predictions of this model match the empirical observation that sensitivity linearly increases with the density of point defects. This model is used to guide the nanoengineering of graphene structures for optimum sensitivity. This approach achieves reproducible fabrication of miniaturized sensors with extraordinarily higher sensitivity than conventional materials. These results lay the foundation for new integrated electrochemical sensor arrays based on nanoengineered graphene.

Wu, Ting↗

DOE OSTI2015

Uncertainty Quantification and Management for Multi-scale Nuclear Materials Modeling

Understanding and improving microstructural mechanical stability in metals and alloys is central to the development of high strength and high ductility materials for cladding and cores structures in advanced fast reactors. Design and enhancement of radiation-induced damage tolerant alloys are facilitated by better understanding the connection of various unit processes to collective responses in a multiscale model chain, including: dislocation nucleation, absorption and desorption at interfaces; vacancy production, radiation-induced segregation of Cr and Ni at defect clusters (point defect sinks) in BCC Fe-Cr ferritic/martensitic steels; investigation of interaction of interstitials and vacancies with impurities (V, Nb, Ta, Mo, W, Al, Si, P, S); time evolution of swelling (cluster growth) phenomena of irradiated materials; and energetics and kinetics of dislocation bypass of defects formed by interstitial clustering and formation of prismatic loops, informing statistical models of continuum character with regard to processes of dislocation glide, vacancy agglomeration and swelling, climb and cross slip.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Native defects in Tl{sub 6}SI{sub 4}: Density functional calculations

Tl{sub 6}SI{sub 4} is a promising room-temperature semiconductor radiation detection material. Here, we report density functional calculations of native defects and dielectric properties of Tl{sub 6}SI{sub 4}. Formation energies and defect levels of native point defects and defect complexes are calculated. Donor-acceptor defect complexes are shown to be abundant in Tl{sub 6}SI{sub 4}. High resistivity can be obtained by Fermi level pinning by native donor and acceptor defects. Deep donors that are detrimental to electron transport are identified and methods to mitigate such problem are discussed. Furthermore, we show that mixed ionic-covalent character of Tl{sub 6}SI{sub 4} gives rise to enhanced Born effective charges and large static dielectric constant, which provides effective screening of charged defects and impurities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Elucidation of Iron Gettering Mechanisms in Boron-Implanted Silicon Solar Cells

To facilitate cost-effective manufacturing of boron-implanted silicon solar cells as an alternative to BBr 3 diffusion, we performed a quantitative test of the gettering induced by solar-typical boron-implants with the potential for low saturation current density emitters (< 50 fA/cm 2 ). We show that depending on the contamination level and the gettering anneal chosen, such boron-implanted emitters can induce more than a 99.9% reduction in bulk iron point defect concentration. The iron point defect results as well as synchrotron-based Nano-X-ray-fluorescence investigations of iron precipitates formed in the implanted layer imply that, with the chosen experimental parameters, iron precipitation is the dominant gettering mechanism, with segregation-based gettering playing a smaller role. We reproduce the measured iron point defect and precipitate distributions via kinetics modeling. First, we simulate the structural defect distribution created by the implantation process, and then we model these structural defects as heterogeneous precipitation sites for iron. Unlike previous theoretical work on gettering via boron- or phosphorus-implantation, our model is free of adjustable simulation parameters. The close agreement between the model and experimental results indicates that the model successfully captures the necessary physics to describe the iron gettering mechanisms operating in boron-implanted silicon. Furthermore, this modeling capability allows high-performance, cost-effective implanted silicon solar cells to be designed.

14 SOLAR ENERGY↗

DOE OSTI2018

Dimensional control of defect dynamics in perovskite oxide superlattices

Point defects play a critical role in the structural, physical, and interfacial properties of perovskite oxide superlattices. However, understanding of the fundamental properties of point defects in superlattices, especially their transport properties, is rather limited. Here, we report predictions of the stability and dynamics of oxygen vacancies in SrTiO 3 /PbTiO 3 oxide superlattices using first-principles calculations in combination with the kinetic Monte Carlo method. By varying the stacking period, i.e., changing of n in n STO/ n PTO, we discover a crossover from three-dimensional diffusion to primarily two-dimensional planar diffusion. Such planar diffusion may lead to novel designs of ionic conductors. We show that the dominant vacancy position may vary in the superlattices, depending on the superlattice structure and stacking period, contradicting the common assumption that point defects reside at interfaces. Moreover, we predict a significant increase in room-temperature ionic conductivity for 3STO/3PTO relative to the bulk phases. As a result, considering the variety of cations that can be accommodated in perovskite superlattices and the potential mismatch of spin, charge, and orbitals at the interfaces, this paper identifies a pathway to control defect dynamics for technological applications.

36 MATERIALS SCIENCE↗

NASA NTRS2003

X-Ray Diffraction and Imaging Study of Imperfections of Crystallized Lysozyme with Coherent X-Rays

Phase-sensitive x-ray diffraction imaging and high angular-resolution diffraction combined with phase contrast radiographic imaging are employed to characterize defects and perfection of a uniformly grown tetragonal lysozyme crystal in symmetric Laue case. The fill width at half-maximum (FWHM) of a 4 4 0 rocking curve measured from the original crystal is approximately 16.7 arcseconds, and defects, which include point defects, line defects, and microscopic domains, have been clearly observed in the diffraction images of the crystal. The observed line defects carry distinct dislocation features running approximately along the <110> growth front, and they have been found to originate mostly at a central growth area and occasionally at outer growth regions. Individual point defects trapped at a crystal nucleus are resolved in the images of high sensitivity to defects. Slow dehydration has led to the broadening of the 4 4 0 rocking curve by a factor of approximately 2.4. A significant change of the defect structure and configuration with drying has been revealed, which suggests the dehydration induced migration and evolution of dislocations and lattice rearrangements to reduce overall strain energy. The sufficient details of the observed defects shed light upon perfection, nucleation and growth, and properties of protein crystals.

Hu, Zheng-Wei↗

DOE OSTI2013

First-principles DFT+U modeling of defect behaviors in anti-ferromagnetic uranium mononitride

A series of point defects in uranium mononitride (UN) have been studied by first-principles DFT+U calculations. The influence of intrinsic defects on the properties of UN was explored by considering the anti-ferromagnetic (AFM) order along the [001] direction. Our results show that all the point defects lead to obvious volume swelling of UN crystal. Energetically, the interstitial nitrogen defect is the most favorable one among single-point defects in UN crystal with the formation energy of 4.539 eV, while the N-Frenkel pair becomes the most preferable one among double-point defects. The AFM order induces obvious electron spin polarization of uranium towards neighboring uranium atoms with opposite spin orientations in UN crystal.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Cluster dynamics modeling of irradiation growth in single crystal Zr

Irradiation growth of single-crystal Zr is modeled with a reduced set of cluster dynamics equations. Nucleation and growth of basal and prismatic dislocation loops are both accounted for in the model. Equations are developed for the time evolution of single point defects, a limited number of point defect clusters, interstitial and vacancy loop nucleation rates, as well as for the growth of vacancy loops on basal planes and interstitial loops on prismatic planes. Reduction of the usual infinite hierarchy of cluster dynamics equations to the simple set studied here is justified on the physical basis of the stability of small loops once nucleated. This simplified cluster dynamics model with a small number of adjustable parameters avoids the complexity of explicit representation of higher order point defect clusters. The model shows consistency with experimental observations of the following aspects: (1) the growth rates of Zr crystals along the a- and c-axes; (2) the onset dose for breakaway irradiation growth; (3) the saturation dislocation loop densities of vacancy and interstitial loops; (4) the effects of cold work and temperature on irradiation growth.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Effects of electron-phonon coupling and electronic thermal conductivity in high energy molecular dynamics simulations of irradiation cascades in nickel

The two-temperature model has been applied to investigate the effects of the electronic subsystem on 150 keV Ni ion cascades in nickel using molecular dynamics simulation. We explore the effects of the magnitude of the electron-phonon coupling and the electronic thermal conductivity on defect production and cluster formation. It has been found that stronger electron-phonon coupling allows larger and more rapid energy feedback to the atomic subsystem, leading to reduction of number of point defects and suppression of the formation of larger defect clusters. It was observed that larger electronic thermal conductivity results in slightly increased number of point defects and larger size vacancy clusters. The latter takes place because of suppression of point defects recombination in faster cooling areas of initial damage.

Zarkadoula, Eva↗

DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗

DOE OSTI2023

Analysis of position-dependent cavity parameters in irradiated metals to obtain insight on fundamental defect migration phenomena

Motion of point defects is a fundamental process that governs microstructure and properties of materials. Here, we examine the near-surface and grain boundary cavity swelling depth profiles in neutron- and ion-irradiated simple metals (Cu, Ni, and Fe-Cr) and investigate diffusional broadening of implanted Ni ions in Fe-Cr alloys. Vacancy migration energies and radiation-enhanced diffusion were experimentally estimated. Cavity denuded zone widths near planar sinks are shown to be dependent on temperature, damage rate, balance of point defects and sinks, and vacancy migration energies. An enhanced cavity swelling zone adjacent to the void-denuded zone was observed in specimens with low to moderate sink strength and interpreted as evidence of 1D gliding interstitial clusters. Radiation-enhanced diffusional broadening of implanted Ni ions (at 400–550 °C) in Fe and Fe-Cr was up to 250 nm toward the surface, which leads to a much broader near-peak-damage region where cavity swelling is suppressed. Diffusional broadening of implanted ions is calculated to be similarly pronounced for self-ion irradiations, particularly near the peak and higher swelling temperature regimes. Adequately high ion energies (~8–15 MeV) are recommended for ion-irradiation studies to provide a sufficiently broad midrange safe analysis region with minimized surface and injected ion effects.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Defect Genome of Cubic Perovskites for Fuel Cell Applications

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defects (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2015

Modeling investigation of the stability and irradiation-induced evolution of nanoscale precipitates in advanced structural materials

Materials used in extremely hostile environment such as nuclear reactors are subject to a high flux of neutron irradiation, and thus vast concentrations of vacancy and interstitial point defects are produced because of collisions of energetic neutrons with host lattice atoms. The fate of these defects depends on various reaction mechanisms which occur immediately following the displacement cascade evolution and during the longer-time kinetically dominated evolution such as annihilation, recombination, clustering or trapping at sinks of vacancies, interstitials and their clusters. The long-range diffusional transport and evolution of point defects and self-defect clusters drive a microstructural and microchemical evolution that are known to produce degradation of mechanical properties including the creep rate, yield strength, ductility, or fracture toughness, and correspondingly affect material serviceability and lifetimes in nuclear applications. Therefore, a detailed understanding of microstructural evolution in materials at different time and length scales is of significant importance. The primary objective of this work is to utilize a hierarchical computational modeling approach i) to evaluate the potential for nanoscale precipitates to enhance point defect recombination rates and thereby the self-healing ability of advanced structural materials, and ii) to evaluate the stability and irradiation-induced evolution of such nanoscale precipitates resulting from enhanced point defect transport to and annihilation at precipitate interfaces. This project will utilize, and as necessary develop, computational materials modeling techniques within a hierarchical computational modeling approach, principally including molecular dynamics, kinetic Monte Carlo and spatially-dependent cluster dynamics modeling, to identify and understand the most important physical processes relevant to promoting the “selfhealing” or radiation resistance in advanced materials containing nanoscale precipitates. In particular, the interfacial structure of embedded nanoscale precipitates will be evaluated by electronic- and atomic-scale modeling methods, and the efficiency of the validated interfaces for trapping point defects will next be evaluated by atomic-scale modeling (e.g., determining the sink strength of the precipitates), addressing key questions related to the optimal interface characteristics to attract point defects and enhance their recombination. Kinetic models will also be developed to simulate microstructural evolution of the nanoscale features and irradiation produced defect clusters, and compared with observed microstructural changes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Structures and localized vibrational states of defects in graphite by tight-binding calculations

The structural and vibrational properties of pristine graphite and point defects in graphite are studied by tight-binding (TB) calculations using a three-center TB potential model. We showed that the three-center TB potential without ‘‘ad hoc’’ van der Waals interaction corrections can accurately describe the inter-layer distance of graphite and the lowest-energy structures and stabilities of typical point defects in graphite. The results from our TB calculations are in good agreement with those from density-functional theory calculations with van der Waals interaction corrections. We also investigated the vibrational properties to gain better understanding on the localization of vibrational states induced by the point defects. Our calculation results show that although localized or quasi-localized vibrational modes can be found in all defected graphite, the localization induced by Frenkel pair, dual-vacancy, and dual-interstitial defects is much stronger. Atomic displacements associated with the localized vibrational modes induced by these three point defects are also analyzed

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Defect Thermodynamics and Transport Properties of Proton Conducting Perovskite Electrode and Electrolyte Materials Evaluated Based on Density Functional Theory Modeling

Both electron-rich and electron-poor perovskite oxides have been used in solid oxide cell applications as electrode and electrolyte materials. The rich oxygen defect chemistry and its coupling to temperature, hydrogen-steam or oxygen-steam gas pressure, or to the applied potentials creates enormous complexities for modeling performance and degradation of the materials. Herein, density functional theory-based thermodynamic modeling was carried out to describe the defect chemistry and transport properties of the proton-conducting electrolyte BaZr1-xYxO3-δ (x≤0.1) and of the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr). The defect thermodynamics of intrinsic point defects and the hydrogen-related defect reactions were solved in integrated defect models and further used to predict the Brouwer diagram and the transport properties of the functional perovskites. For the electron-poor electrolytes BaZr0.9Y0.1O3-δ, the developed model has been used to describe the experimental transport properties in the SOC operating conditions. Specifically, the roles played by the acceptor-bound holes and the intrinsic and hydrogen point defects upon the conductivities of holes, protons, and oxygen vacancies under the hydrogen-rich and oxygen-rich conditions at various humidity levels were demonstrated. A defect modeling tool was also developed for the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr) to examine magnetic effects and hydride defects in defect equilibria.

defect thermodynamics↗

DOE OSTI2018

The Interface Influence in TiN/SiN{sub x} Multilayer Nanocomposite Under Irradiation

The paper focuses on studying the kinetics of radiation-induced point defects formed in TiN/SiN{sub x} multilayer nanocomposites with account of their generation, diffusion recombination, and the influence of sinks functioning as interfaces. In order to describe the kinetics in nanocrystalline TiN and amorphous SiN{sub x} phases, a finite-difference method is used to solve the system of balance kinetic equations for absolute defect concentrations depending on the spatiotemporal variables. A model of the disclination-dislocation interface structure is used to study the absorption of radiation-induced point defects on the boundaries in created stress fields. It is shown that the interface effectively absorbs point defects in these phases of TiN/SiN{sub x} multilayer nanocomposite, thereby reducing their amount within the space between phases. This behavior of point defects partially explains a mechanism of the radiation resistance in this type of nanocomposites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2014

Nanodot formation induced by femtosecond laser irradiation

The femtosecond laser generation of ZnSe nanoscale features on ZnSe surfaces was studied. Irradiation with multiple exposures produces 10–100 nm agglomerations of nanocrystalline ZnSe while retaining the original single crystal structure of the underlying material. The structure of these nanodots was verified using a combination of scanning transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. The nanodots continue to grow hours after irradiation through a combination of bulk and surface diffusion. We suggest that in nanodot formation the result of ultrafast laser induced point defect formation is more than an order of magnitude below the ZnSe ultrafast melt threshold fluence. This unique mechanism of point defect injection will be discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

AlScO 3 perovskite—An ~8 eV bandgap oxide predicted to exhibit low small hole polaron ionization energies and p -type conductivity at elevated temperatures

Here, we investigate electronic structure and dopability of an ultrawide bandgap (UWBG) AlScO 3 perovskite, a known high-pressure and long-lived metastable oxide. From first-principles electronic structure calculations, HSE06(+G 0 W 0 ), we find this material to exhibit an indirect bandgap of around 8.0 eV. Defect calculations point to cation and oxygen vacancies as the dominant intrinsic point defects limiting extrinsic doping. While acceptor behaving Al and Sc vacancies prevent n-type doping, oxygen vacancies permit the Fermi energy to reach ~0.3 eV above the valence band maximum, rendering AlScO 3 p-type dopable. Furthermore, we find that both Mg and Zn could serve as extrinsic p-type dopants. Specifically, Mg is predicted to have achievable net acceptor concentrations of ~10 17 cm -3 with ionization energy of bound small hole polarons of ~0.49 eV and free ones below 0.1 eV. These values place AlScO 3 among the UWBG oxides with lowest bound small hole polaron ionization energies, which, as we find, is likely due to large ionic dielectric constant that correlates well with low hole polaron ionization energies across various UWBG oxides.

14 SOLAR ENERGY↗