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At least 361 records · Page 20

Active and passive defects in tetragonal tungsten bronze relaxor ferroelectrics

Tetragonal tungsten bronze (TTB) based oxides constitute a large family of dielectric materials which are known to exhibit complex distortions producing incommensurately modulated superstructures as well as significant local deviations from their average symmetry. The local deviations produce diffuse scattering in diffraction experiments. The structure as well as the charge dynamics of these materials are anticipated to be sensitive to defects, such as cation or oxygen vacancies. In this work, in an effort to understand how the structural and charge dynamical properties respond to these two types of vacancy defects, we have performed measurements of dielectric susceptibilities and single crystal diffraction experiments of two types of TTB materials with both ‘filled’ (Ba 2 NdFeNb 4 O 15 and Ba 2 PrFeNb 4 O 15 ) and ‘unfilled’ (Sr 0.5 Ba 0.5 Nb 2 O 6 ) cation sublattices. We also perform these measurements before and after oxygen annealing, which alters the oxygen vacancy concentrations. Surprisingly, we find that many of the diffuse scattering features that are present in the unfilled structure are also present in the filled structure, suggesting that the random fields and disorder that are characteristic of the unfilled structure are not responsible for many of the local structural features that are reflected in the diffuse scattering. Furthermore, oxygen annealing clearly affected both color and dielectric properties, consistent with a diminishment of the oxygen vacancy concentration, but had little effect on observed diffuse patterns.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Pinhole array capacitor for oxide integrity analysis

The integrity of the metal-poly oxide and the gate oxide was evaluated for several 5-micron CMOS-bulk processes. The pinhole array capacitor consists of diffused and poly fingers that form a network of MOS transistors (elements), which are capped by a deposited oxide and metal layer. The smallest structure used in this study contained about 15,000 elements and the largest structure contained about 68,000 elements. Each structure was divided into several subarrays. The structures are placed a number of times on each wafer. From a yield analysis of the subarrays, the elements per defect were found to be typically in excess of 50,000 elements/defect for the metal-poly oxide and 100,000 elements/defect for the gate oxide. From the switching behavior of the transistors, the gate oxide defects were tentatively identified as gate-to-body shorts rather than gate-to-diffusion shorts.

Buehler, M. G.↗

Topological phase transition to a hidden charge density wave liquid

Charge density waves (CDWs), electronic crystals that form within a host solid, have long been speculated to melt into a spatially textured electronic liquid. Though they have not been previously detected, liquid CDWs may nonetheless be fundamental to the phase diagrams of many correlated electron systems, including high temperature superconductors and quantum Hall states. In one of the most promising candidate materials capable of hosting a liquid CDW, 1T-TaS2, a structural phase transition impedes its observation. Here, by irradiating the material with a femtosecond light pulse, we circumvent the structural phase transition to reveal how topological defect dynamics govern the otherwise invisible CDW correlations. Upon photoexcitation, the CDW diffraction peaks broaden azimuthally, initially revealing a hexatic state. At higher temperatures, photoexcitation completely destroys translational and orientational order and only a ring of diffuse scattering is observed, a key signature of a liquid CDW. Our work provides compelling evidence for a defect-unbinding transition to a CDW liquid and presents a protocol for uncovering states that are hidden by other transitions in thermal equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗

The Diffusion Mechanism of Ge During Oxidation of Si/SiGe Nanofins

A recently discovered, enhanced Ge diffusion mechanism along the oxidizing interface of Si/SiGe nanostructures has enabled the formation of single-crystal Si nanowires and quantum dots embedded in a defect-free, single-crystal SiGe matrix. Here, we report oxidation studies of Si/SiGe nanofins aimed at gaining a better understanding of this novel diffusion mechanism. Here, a superlattice of alternating Si/Si 0.7 Ge 0.3 layers was grown and patterned into fins. After oxidation of the fins, the rate of Ge diffusion down the Si/SiO 2 interface was measured through the analysis of HAADF-STEM images. The activation energy for the diffusion of Ge down the sidewall was found to be 1.1 eV, which is less than one-quarter of the activation energy previously reported for Ge diffusion in bulk Si. Through a combination of experiments and DFT calculations, we propose that the redistribution of Ge occurs by diffusion along the Si/SiO 2 interface followed by a reintroduction into substitutional positions in the crystalline Si.

36 MATERIALS SCIENCE↗

Ab-initio informed cluster dynamics simulation of self- and Xe diffusivity in uranium mononitride under irradiation

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuels considered for light water reactor and advanced reactor designs, as it presents significant advantages such as high uranium density (better economics) and high thermal conductivity and melting point (increased safety). Self- and fission gas diffusivities need to be better understood, given that they influence key fuel performance phenomena like swelling and fission gas release. Recently, radiation enhanced diffusivity was investigated in UN by means of cluster dynamics simulations relying on empirical potential-based parameterizations, the reliability of which highly depends on the interatomic potential accuracy. Here, in this work, we refine this approach by determining, using ab-initio calculations, the properties of defect clusters containing vacancies, self-interstitials and Xe impurities. We also consider larger clusters than previous studies. The obtained dataset (formation enthalpies, entropies, and migration barriers) is used to parameterize a cluster dynamics model of mobile clusters, and to calculate the defect cluster concentrations under irradiation. This gives us access to the radiation enhanced self- and fission gas diffusivities. Although the resulting diffusivities are close to the values reported in the literature, we find important qualitative differences in the diffusion mechanisms. Capturing the correct mechanisms is crucial to properly describe the chemistry and fission rate dependence of the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Solar Wind Implantation into Lunar Regolith: Hydrogen Retention in a Surface with Defects

Solar wind protons are implanted directly into the top 100 nm of the lunar near-surface region, but can either quickly diffuse out of the surface or be retained, depending upon surface temperature and the activation energy, U, associated with the implantation site. In this work, we explore the distribution of activation energies upon implantation and the associated hydrogen-retention times; this for comparison with recent observation of OH on the lunar surface. We apply a Monte Carlo approach: for simulated solar wind protons at a given local time, we assume a distribution of U values with a central peak, U(sub c) and width, U(sub w), and derive the fraction retained for long periods in the near-surface. We find that surfaces characterized by a distribution with predominantly large values of U (greater than 1 eV) like that expected at defect sites will retain implanted H (to likely form OH). Surfaces with the distribution predominantly at small values of U (less than 0.2 eV) will quickly diffuse away implanted H. However, surfaces with a large portion of activation energies between 0.3 eV less than U less than 0.9 eV will tend to be H-retentive in cool conditions but transform into H-emissive surfaces when warmed (as when the surface rotates into local noon). These mid-range activation energies give rise to a diurnal effect with diffusive loss of H at noontime.

regolith↗

Effect of local chemical order on the irradiation-induced defect evolution in CrCoNi medium-entropy alloy

High- (and medium-) entropy alloys have emerged as potentially suitable structural materials for nuclear applications, particularly as they appear to show promising irradiation resistance. Recent studies have provided evidence of the presence of local chemical order (LCO) as a salient feature of these complex concentrated solid-solution alloys. However, the influence of such LCO on their irradiation response has remained uncertain thus far. Here, in this work, we combine ion irradiation experiments with large-scale atomistic simulations to reveal that the presence of chemical short-range order, developed as an early stage of LCO, slows down the formation and evolution of point defects in the equiatomic medium-entropy alloy CrCoNi during irradiation. In particular, the irradiation-induced vacancies and interstitials exhibit a smaller difference in their mobility, arising from a stronger effect of LCO in localizing interstitial diffusion. This effect promotes their recombination as the LCO serves to tune the migration energy barriers of these point defects, thereby delaying the initiation of damage. These findings imply that local chemical ordering may provide a variable in the design space to enhance the resistance of multi-principal element alloys to irradiation damage.

36 MATERIALS SCIENCE↗

Understanding the interface interaction between U3Si2 fuel and SiC cladding

Abstract Triuranium disilicide (U 3 Si 2 ) fuel with silicon carbide (SiC) composite cladding is being considered as an advanced concept/accident tolerant fuel for light water reactors thus, understanding their chemical compatibility under operational and accident conditions is paramount. Here we provide a comprehensive view of the interaction between U 3 Si 2 and SiC by utilizing density functional theory calculations supported by diffusion couple experiments. From the calculated reaction energies, we demonstrate that triuranium pentasilicide (U 3 Si 5 ), uranium carbide (UC), U 20 Si 16 C 3 , and uranium silicide (USi) phases can form at the interface. A detailed study of U 3 Si 2 and SiC defect formation energies of the equilibrated materials yielding the interfacial phases U 20 Si 16 C 3 , U 3 Si 5 and UC reveal a thermodynamic driving force for generating defects in both fuel and cladding. The absence of either the U 3 Si 2 or SiC phase, however, causes the defect formation energies in the other phase to be positive, removing the driving force for additional interfacial reactions. The diffusion couple experiments confirm the conclusion with demonstrated restricted formation of U 3 Si 5 , UC, and U 20 Si 16 C 3 /USi phases at the interface. The resulting lack of continuous interaction between the U 3 Si 2 and SiC, reflects the diminishing driving force for defect formation, demonstrating the substantial stability of this fuel-cladding system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Molecular dynamics simulations of radiation response of $\mathrm{LiAlO_2}$ and $\mathrm{LiAl_5O_8}$

Here, we report the findings of a computational investigation of defect production and migration in two lithium aluminate ceramics: LiAlO 2 and LiAl 5 O 8 . Although the first ceramic, LiAlO 2 has been widely investigated computationally, especially via molecular dynamics (MD), there have been no MD studies done on LiAl 5 O 8 up to date, due to the lack of interatomic potentials for this system. This work implemented an existing set of Li-Al-O coulombic and Buckingham potential parameters for the LiAl 5 O 8 system from the literature, followed by validating it based on experimental values of density, crystallinity, bond lengths and melting point. The Li + diffusion in the two ceramics was examined and was found to be one order of magnitude slower in LiAl 5 O 8 (D 0 = 3.17 x 10 -11 m 2 /s) as compared to that in LiAlO 2 (D 0 = 4.02 x 10 -10 m 2 /s) at 600 K. The lithium vacancy migration barrier of 4.15 eV in LiAl 5 O 8 was more than three times that in LiAlO 2 (1.31 eV) possibly due to stronger ordering in the Li-O 6 octahedra of LiAl 5 O 8 than in Li-O 4 tetrahedra of LiAlO 2 . The Li displacement threshold energy (E d ) in LiAl 5 O 8 was found to have a median value of 68 eV which is much higher than that in LiAlO 2 (40 eV). The greater E d for Li signifies a lower likelihood for defect formation and clustering and thus lower tendency for amorphization in LiAl 5 O 8 . The presented results show the difference in defect dynamics in the two ceramics that may help us understand the susceptibility of the two ceramics to amorphization caused by irradiation.

36 MATERIALS SCIENCE↗

Imaging CdCl 2 defect passivation and formation in polycrystalline CdTe films by cathodoluminescence

Polycrystalline thin-film solar cells are attractive for low-cost photovoltaics, but their efficiencies are hindered by material quality issues. State-of-the-art CdTe solar cells use CdCl 2 annealing treatments whose effects are still being discovered at a fundamental level. Here, a series of CdTe samples with different annealing temperatures is investigated with high-resolution hyperspectral cathodoluminescence mapping measured at both room temperature and low temperature on the same microscopic areas. A statistical analysis over a large number of grains is combined with a local analysis at grain boundaries. The results elucidate the dynamic interplay between grain boundary and intragrain defect passivation and formation, in the midst of grain growth. The CdCl 2 annealing initially contributes to an increase of the grain size and the passivation of both grain boundaries and grain interiors, increasing the overall luminescence and diffusion length. For higher annealing temperatures, a further increase of grain size is counterbalanced by the rise of bulk defects. The results illustrate the tradeoffs that lead to an optimal annealing temperature, as well as new methods for understanding defect passivation and creation in thin film solar cells.

14 SOLAR ENERGY↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

Diffusion-mediated chemical concentration variation and void evolution in ion-irradiated NiCoFeCr high-entropy alloy

High-entropy alloys (HEAs) are proposed as potential structural materials for advanced nuclear systems, but little is known about the response of matrix chemistry in HEAs upon irradiation. Here, we reveal a substantial change of matrix chemical concentration as a function of irradiation damage (depth) in equiatomic NiCoFeCr HEA irradiated by 3 MeV Ni ions. After ion irradiation, the matrix contains more Fe/Cr in depth shallower than ~900–1000 nm but more Ni/Co from ~900–1000 nm to the end of the ion-damaged region due to the preferential diffusion of vacancies through Fe/Cr. Preferential diffusion also facilitates migration of vacancies from high radiation damage region to low radiation damage region, leading to no void formation below ~900–1000 nm and void formation around the end of the ion-damaged region at a fluence of 5 × 10 16 cm -2 (~123 dpa, displacements per atom, peak dose under full cascade mode). As voids grow significantly at an increased fluence (8 × 10 16 cm -2 , 196 dpa), the matrix concentration does not change dramatically due to new voids formed below ~900–1000 nm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Permeation of halide anions through phospholipid bilayers occurs by the solubility-diffusion mechanism

Two alternative mechanisms are frequently used to describe ionic permeation of lipid bilayers. In the first, ions partition into the hydrophobic phase and then diffuse across (the solubility-diffusion mechanism). The second mechanism assumes that ions traverse the bilayer through transient hydrophilic defects caused by thermal fluctuations (the pore mechanism). The theoretical predictions made by both models were tested for halide anions by measuring the permeability coefficients for chloride, bromide, and iodide as a function of bilayer thickness, ionic radius, and sign of charge. To vary the bilayer thickness systematically, liposomes were prepared from monounsaturated phosphatidylcholines (PC) with chain lengths between 16 and 24 carbon atoms. The fluorescent dye MQAE (N-(ethoxycarbonylmethyl)-6-methoxyquinolinium bromide) served as an indicator for halide concentration inside the liposomes and was used to follow the kinetics of halide flux across the bilayer membranes. The observed permeability coefficients ranged from 10(-9) to 10(-7) cm/s and increased as the bilayer thickness was reduced. Bromide was found to permeate approximately six times faster than chloride through bilayers of identical thickness, and iodide permeated three to four times faster than bromide. The dependence of the halide permeability coefficients on bilayer thickness and on ionic size were consistent with permeation of hydrated ions by a solubility-diffusion mechanism rather than through transient pores. Halide permeation therefore differs from that of a monovalent cation such as potassium, which has been accounted for by a combination of the two mechanisms depending on bilayer thickness.

NASA Discipline Exobiology↗

Cluster Dynamics Simulations of Intra-Granular Fission Gas Bubble Size and Pressure Evolution in UO 2

Fission gases such as xenon (Xe) play a critical role in determining the behavior and response of nuclear fuel. Given that Xe has little solubility in UO 2 , it accumulates and forms bubbles, which significantly impact fuel performance. Intra- and inter-granular bubble nucleation and growth can lead to fuel swelling, and once bubbles interconnect at grain boundaries, fission gas can be released into the plenum. At low temperatures, limited uranium vacancy mobility can restrict swelling, therefore causing the bubbles to become highly pressurized. Consequently, this can induce micro-cracking, promote fission gas release (increasing the likelihood of cladding failure), and even lead to fuel pulverization under accident conditions such as a loss of coolant accident. As bubble evolution is strongly influenced by local temperature and fission rate, markedly different behavior occurs across the radial profile of the fuel pellet. Capturing the mechanisms that underpin bubble evolution is therefore important to predict these behaviors in the fuel. Previous models describing important mechanisms informed by lower length scale simulations have been developed under the NEAMS program. These can describe the evolution of a single bubble type (i.e., single value for radius and pressure) at each position in the pellet, for instance using the Centipede cluster dynamic code. However, in reality, a full distribution in bubble sizes and pressures exists within the microstructure at a given position in the pellet. To address this the cluster dynamics code Xolotl, which can predict Xe and vacancy phase space (i.e., bubble distributions) for intra-granular bubbles, has been used before. Prior work benchmarked the Xolotl code against the Centipede cluster dynamics code to ensure compatibility and to verify that mobile defect properties are adequately transferred between the two codes, along with some physics improvements. In this work, we go further by introducing a physics-based set of improvements that will allow us to accurately predict bubble size distributions and internal bubble pressures under representative UO 2 irradiation conditions. The improvements include (i) coupling bubble-defect reaction energies to a virial equation of state (EOS), (ii) including a bubble surface tension contribution, (iii) incorporating radiation-induced re-solution of Xe and vacancies, (iv) enabling pressure-driven dislocation loop punching through an effective emission of interstitial clusters informed by interstitial loop energetics, (v) accounting for radiation induced athermal diffusion of Xe, and (vi) implementing a Booth-type grain boundary sink representation for all mobile defects and defect clusters. After these modifications, we observe good agreement of Xolotl fission gas bubble size and concentration predictions with legacy experimental measurements. Additionally, it allows the distribution of Xe bubble pressures and radius to also be predicted and compared to data produced through the Advanced Fuels Campaign (AFC) program. Here, we have done this by running simulations under conditions similar to the AFC post-irradiation examination (PIE) samples irradiated at North Anna 2 light water reactor (LWR). Our results shows excellent agreement with these experimental measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncovering metallic glasses hidden vacancy-like motifs using machine learning

Vacancies are a ubiquitous type of defect in crystalline materials that can affect their properties and behavior, including atomic diffusivity, deformation processes, thermal conductivity, and electrical conductivity. While well-defined in crystals, it is challenging to identify such topological footprints in the amorphous structure of metallic glasses (MGs). Here, we uncover an unforeseen vacancy-like structural motif named Q7, which refers to an atomic Voronoi polyhedron with seven quadrangular faces, by investigating MG local atomic configurations with the help of machine learning. The Q7 motif exhibits characteristics similar to crystalline vacancies and plays a significant role in short-range structural disorder in MGs. The atoms at the center of the Q7 motif display larger local entropy, atomic volume, and local tension. Additionally, its concentration follows an Arrhenius-like relationship with temperature, accurately indicating the glass transition temperature, and is strongly correlated with the yield and failure of MGs during mechanical deformation. The discovery of the Q7 motif provides new insights into understanding the intricate relationship between local disorder and structural relaxation in MGs, offering a remarkable ability to predict their thermal and mechanical behavior. This potentially paves the way for enhancements in the design and manufacturing processes of MGs and other amorphous materials.

36 MATERIALS SCIENCE↗

Study of radiation induced deep-level defects in proton irradiated AlGaAs-GaAs solar cells

Radiation induced deep-level defects (both electron and hole traps) in proton irradiated AlGaAs-GaAs p-n junction solar cells are investigated along with the correlation between the measured defect parameters and the solar cell performance parameters. The range of proton energies studied was from 50 KeV to 10 MeV and the proton fluence was varied from 10 to the 10th power to 10 to the 13th power P/sq cm. Experimental tools employed include deep-level transient spectroscopy, capacitance-voltage, current voltage, and SEM-EBIC methods. Defect and recombination parameters such as defect density and energy level, capture cross section, carrier lifetimes and effective hole diffusion lengths in n-GaAs LPE layers were determined from these measurements.

Li, S. S.↗

Process-induced defects in solar cell silicon

The microstructure of as-grown and processed, edge-defined film-fed grown, silicon ribbons was studied in order to identify the basic mechanisms responsible for the change of the as-grown defect structure during processing at elevated temperatures. The short heat treatment required to diffuse the p-n junction was sufficient to cause heterogeneous precipitation of impurity atoms, particularly transition metals. In addition, an elastic recovery of the ribbon occurred by dislocation glide, resulting in the formation of a polygonizationlike structure of subboundaries in the base. Mechanisms are suggested by which twin boundaries, acting as dislocation obstacles, can concentrate the relatively low average dislocation densities typical of edge-defined film-fed grown ribbons (10 to the 4th to 10 to the 8th/sq cm) to values which are sufficient to induce the formation of subgrainlike boundary structures.

Gleichmann, R.↗