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At least 829 records · Page 46

Quantum material topology via defect engineering

Current approaches of discovering new topological quantum materials, such as (magnetic) Weyl materials, by screening material databases or by rational design suffer from experimental challenges in growing the material in the desired geometry, hampering their potential applications. We take an approach of defect-engineering a topology starting from systems with experimentally well-controlled growth . Using SnTe, an experimentally viable topological crystalline insulator, as our model system, we elucidate the different effects of breaking time-reversal, inversion, and mirror symmetries using magnetic dopant defects, to controllably induce a topological phase transition. To this effect, we compute the thermodynamics, magnetism, and band-structure topology of magnetically doped SnTe using a full ab initio approach. In this process, we have discovered that Cr-doped SnTe is a Weyl semimetal. We have computed its classic Fermi-arc experimental signature on the (001) surface and also showed that it has a large anamolous Hall conductivity (AHC) of ~ 250 Ω - 1 cm - 1 . We predict a large Curie temperature ( T c ) of 62 K even at 3.3 % doping, with both T c and AHC being tunable with Cr concentration, suggesting potential for room-temperature applications. Our study in general paves the way for defect-designing room-temperature topological quantum phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multiscale Modeling of Grain-Boundary Fracture: Cohesive Zone Models Parameterized From Atomistic Simulations

A multiscale modeling strategy is developed to study grain boundary fracture in polycrystalline aluminum. Atomistic simulation is used to model fundamental nanoscale deformation and fracture mechanisms and to develop a constitutive relationship for separation along a grain boundary interface. The nanoscale constitutive relationship is then parameterized within a cohesive zone model to represent variations in grain boundary properties. These variations arise from the presence of vacancies, intersticies, and other defects in addition to deviations in grain boundary angle from the baseline configuration considered in the molecular dynamics simulation. The parameterized cohesive zone models are then used to model grain boundaries within finite element analyses of aluminum polycrystals.

Glaessgen, Edward H.↗

Predicting the reliability of an additively-manufactured metal part for the third Sandia fracture challenge by accounting for random material defects

We describe an approach to predict failure in a complex, additively-manufactured stainless steel part as defined by the third Sandia Fracture Challenge. A viscoplastic internal state variable constitutive model was calibrated to fit experimental tension curves in order to capture plasticity, necking, and damage evolution leading to failure. Defects such as gas porosity and lack of fusion voids were represented by overlaying a synthetic porosity distribution onto the finite element mesh and computing the elementwise ratio between pore volume and element volume to initialize the damage internal state variables. These void volume fraction values were then used in a damage formulation accounting for growth of these existing voids, while new voids were allowed to nucleate based on a nucleation rule. Blind predictions of failure are compared to experimental results. The comparisons indicate that crack initiation and propagation were correctly predicted, and that an initial porosity field superimposed as higher initial damage may provide a path forward for capturing material strength uncertainty. Here, the latter conclusion was supported by predicted crack face tortuosity beyond the usual mesh sensitivity and variability in predicted strain to failure; however, it bears further inquiry and a more conclusive result is pending compressive testing of challenge-built coupons to de-convolute materials behavior from the geometric influence of significant porosity.

36 MATERIALS SCIENCE↗

Physics-Based Model to Represent Membrane-Electrode Assemblies of Solid-Oxide Fuel Cells Based on Gadolinium-Doped Ceria

This paper reports a physics-based model that predicts membrane-electrode assembly (MEA) performance of solid-oxide fuel cells (SOFCs) with Ce 0.9 Gd 0.1 O 2− δ (GDC10) electrolyte membranes. The paper derives self-consistent thermodynamic and transport properties for GDC1o mobile charged defects (oxide vacancies and reduced-ceria small polarons) by fitting published measurements of oxygen non-stoichiometry and conductivity over ranges of temperature and O 2 partial pressures. The button-cell model is applied to evaluate how mixed ionic-electronic conductivity influences the performance of an SOFC MEA with a GDC10 electrolyte sandwiched between a porous, composite Ni-GDC10 anode and a porous, composite cathode of Sm 0.5 Sr 0.5 CoO 3− δ (i.e., SSC) and GDC10. SSC properties are also derived by fitting published conductivity and oxygen non-stoichiometry measurements. Mixed conductivity of GDC10 and competing charge transfer reactions at both electrodes reduce open circuit voltages due to leakage current and buildup of defect concentrations at electrode-electrolyte interfaces. To fit polarization data, the button-cell model includes heterogeneous reaction rates for defect incorporation on the GDC10 surface along with Butler–Volmer expressions derived for competing charge transfer reaction rates from rigorous analyses assuming rate-limiting, elementary charge transfer reactions for each electrode. The calibrated MEA model can support rigorous SOFC modeling with GDC10 electrolytes over the range of conditions within a fully operating cell.

Electrochemistry↗

Lattice Disorder and Oxygen Migration Pathways in Pyrochlore and Defect-Fluorite Oxides

Atomic-scale disorder plays an important role in the chemical and physical properties of oxide materials. The structural flexibility of pyrochlore-type oxides allows for crystal-chemical engineering of these properties. Compositional modification can push pyrochlore oxides toward a disordered defect-fluorite structure with anion Frenkel pair defects that facilitate oxygen migration. The local structure of the long-range average cubic defect-fluorite was recently claimed to consist of randomly arranged orthorhombic weberite-type domains. Here, we show, using low-temperature neutron total-scattering experiments, that this is not the case for Zr-rich defect-fluorites. By analyzing data from the pyrochlore/defect-fluorite Y 2 Sn 2–x Zr x O 7 series using a combination of neutron pair distribution function and big-box modelling, we have differentiated and quantified the relationship between anion sub-lattice disorder and Frenkel defects. These details directly influence the energy landscape for oxygen migration and are crucial for simulations and design of new materials with improved properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Super-Resolution Microscopy Reveals Shape and Distribution of Dislocations in Single Crystal Nanocomposites

With their potential to offer new properties, single crystals containing nanoparticles provide an attractive class of nanocomposite materials. Yet, to fully profit from these, it is essential that we can characterise their 3D structures, identifying the locations of individual nanoparticles, and the defects present within the host crystals. With calcite crystals containing quantum dots as a model system, we here use 3D stochastic optical reconstruction microscopy (STORM) to locate the positions of the nanoparticles within the host crystal. The nanoparticles are shown to preferentially associate with dislocations in a manner previously recognised for atomic impurities, rendering these defects visible by STORM. Our images also demonstrate that the types of dislocations formed at the crystal/ substrate interface vary according to the nucleation face, and dislocation loops are observed that have entirely different geometries to classic misfit dislocations. This approach offers a rapid, easily accessed, and non-destructive method for visualising the dislocations present within crystals, and gives insight into the mechanisms by which additives become occluded within crystals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Radiation damage effects in beryllium for next generation neutrino beam targetry (Final Technical Report)

Current and future high-power accelerators put severe requirements on materials used for target and beam windows and target facilities have been recognized as a critical challenge in development of future particle accelerators. In accelerators, window and target materials are exposed to extreme conditions, which include bombardment with very high energy protons (1- 100 GeV) and thermomechanical shock waves. Radiation can cause direct damage in the material, and it leads to production of transmutation products (especially helium), both phenomena having a potential adverse effect on the stability and durability of the target/window material. At high enough temperatures, He can aggregate to form gas bubbles, which in turn cause significant dimensional changes (swelling), enable easy crack propagation, and eventually cause failure by fracture. On the other hand, if the temperature is too low, radiation damage accumulates in the form of internal defects (e.g., dislocations), leading to hardening and a decreased ductility of the material. In this project, we will focus on beryllium since it is considered to be one of the candidate materials for beam windows and targets in the next-generation proton accelerators, e.g., the Long Baseline Neutrino Facility (LBNF). Radiation effects in Be have been studied in the context of nuclear fusion reactor applications. However, key differences exist between reactor and accelerator conditions, including neutron vs. proton irradiation, continuous vs. pulsed beam flux, much higher energies of bombarding particles in accelerators, and higher operating temperatures for typical reactors. For example, the impact of beam pulsing on the radiation damage and the He bubble kinetics is largely unknown. While results obtained on Be from fusion research might not be directly transferrable to understanding target materials, there is an opportunity to bring state-of-the-art tools from materials research in nuclear reactors to aid design of target and beam window materials in high-power accelerators. To this end, the overarching goal of this project are to develop an experimentally-validated computational framework capable of predicting radiation damage evolution in beryllium relevant to beam window and target conditions, focusing on He bubble formation and growth as a function of irradiation temperature. Our model will be based on the cluster dynamics formalism, where size distribution of defects and He bubbles is simulated as a function of time, temperature, and radiation dose. Parameters for the model will be taken from published experiments and from high-fidelity atomistic simulations proposed in this project. In addition, we will carry out a series of targeted ex-situ and in-situ dual-beam experiments using low-energy protons to provide critical data for validation of the model on the effects of radiation on He clustering, He bubble distribution, and dislocation loop density/size in proton irradiated Be.

36 MATERIALS SCIENCE↗

Ball bearing vibrations amplitude modeling and test comparisons

Bearings generate disturbances that, when combined with structural gains of a momentum wheel, contribute to induced vibration in the wheel. The frequencies generated by a ball bearing are defined by the bearing's geometry and defects. The amplitudes at these frequencies are dependent upon the actual geometry variations from perfection; therefore, a geometrically perfect bearing will produce no amplitudes at the kinematic frequencies that the design generates. Because perfect geometry can only be approached, emitted vibrations do occur. The most significant vibration is at the spin frequency and can be balanced out in the build process. Other frequencies' amplitudes, however, cannot be balanced out. Momentum wheels are usually the single largest source of vibrations in a spacecraft and can contribute to pointing inaccuracies if emitted vibrations ring the structure or are in the high-gain bandwidth of a sensitive pointing control loop. It is therefore important to be able to provide an a priori knowledge of possible amplitudes that are singular in source or are a result of interacting defects that do not reveal themselves in normal frequency prediction equations. This paper will describe the computer model that provides for the incorporation of bearing geometry errors and then develops an estimation of actual amplitudes and frequencies. Test results were correlated with the model. A momentum wheel was producing an unacceptable 74 Hz amplitude. The model was used to simulate geometry errors and proved successful in identifying a cause that was verified when the parts were inspected.

Hightower, Richard A., III↗

Uranium-hydrogen reaction mechanism and numerical model

We have developed a numerical model to help predict lifetimes of uranium parts in situations where the uranium surface is exposed to hydrogen in the gas headspace. Assessments can be made based on hydrogen pressure and on an upper limit of size of a surface breached hydride spot (volume of hydride corrosion product produced). The model assumes development of a hydride nucleus at a single arbitrary subsurface location associated with an arbitrary surface defect and follows the development of the hydride nucleus to the break-through phase and further growth to the upper limit of acceptable volume of corrosion product. The model has been developed from an understanding of the hydriding mechanism outlined below in 10 steps and measured rates of hydrogen ingress at several types (chemically) of uranium surfaces at ambient temperature and variable pressure. The key points are 1) that the hydrides nucleate only at locations where a surface defect allows hydrogen ingress (reactant delivery) into the uranium metal subsurface (beyond the oxide), and 2) that the hydrides which eventually reach surface break-through status, nucleate and grow in the near surface (few 10s of micron depth maximum) – those beyond ~50 micron have arrested growth and never reach break-through status.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗

Learning to Predict Crystal Plasticity at the Nanoscale: Deep Residual Networks and Size Effects in Uniaxial Compression Discrete Dislocation Simulations

The density and configurational changes of crystal dislocations during plastic deformation influence the mechanical properties of materials. These influences have become clearest in nanoscale experiments, in terms of strength, hardness and work hardening size effects in small volumes. The mechanical characterization of a model crystal may be cast as an inverse problem of deducing the defect population characteristics (density, correlations) in small volumes from the mechanical behavior. In this work, we demonstrate how a deep residual network can be used to deduce the dislocation characteristics of a sample of interest using only its surface strain profiles at small deformations, and then statistically predict the mechanical response of size-affected samples at larger deformations. As a testbed of our approach, we utilize high-throughput discrete dislocation simulations for systems of widths that range from nano- to micro- meters. We show that the proposed deep learning model significantly outperforms a traditional machine learning model, as well as accurately produces statistical predictions of the size effects in samples of various widths. By visualizing the filters in convolutional layers and saliency maps, we find that the proposed model is able to learn the significant features of sample strain profiles.

36 MATERIALS SCIENCE↗

Kinetic Simulations of Cu Doping in Chlorinated CdSeTe PV Absorbers

This paper reports on 1D kinetic modeling of p-type doping formation in Cu-doped chlorinated CdSeTe photovoltaic (PV) absorbers with graded Se profiles. Following the recent progress in kinetic simulations of the defect chemistry in stoichiometric CdTe films, this work extends simulation capabilities to a domain of semiconductor alloy films with graded stoichiometries. The defect formation energies and ionization levels, as well as the diffusion and reaction barriers used in the reaction-diffusion equations are calculated from the first principles. A new formalism is employed to account for the uncertainty of the defect formation energies in semiconductor alloys caused by unknown local surrounding. Finally, the developed methodology is used to model a practical fabrication process of p-type doping formation in graded CdSeTe absorbers and to study the effect of alloy stoichiometry on the doping activation.

14 SOLAR ENERGY↗

Local Ultrasonic Resonance Spectroscopy of Lithium Metal Batteries for Aerospace Applications

As next-generation aircraft and vehicles continue to develop, so do their associated energy demands. Lithium metal batteries are a leading candidate to fulfill this energy requirement, but these batteries are prone to internal dendrite defects that can lead to catastrophic thermal runaway events. Current battery management systems are capable of mitigating such risks, but are unable to detect such defects until thermal runaway has already begun. Various nondestructive evaluation (NDE) techniques, particularly ultrasonic NDE, can directly monitor internal battery parameters giving them the potential to detect critical defects prior to catastrophic failure. However, most of the current battery NDE research has focused on improved battery state-of-charge (SOC) and stateof- health (SOH) monitoring with little emphasis on critical defect detection. Thus, a measurement technique sensitive to subtle battery defects is needed. In addition, the complex mechanics of ultrasound in porous, thin, multilayered batteries prompt the use of physics-based simulation to guide inspections. In this work, an ultrasonic NDE technique has been developed utilizing frequency domain analysis of local battery resonances to detect the presence of battery defects. This technique is a practical extension of local ultrasonic resonance spectroscopy (LURS) – which previously required non-contact laser ultrasonics – to measurements with piezoelectric contact and immersion scan transducers. To extend the technique to work with piezoelectric transducers, ultrasonic battery measurements were compared to a sans-battery calibration measurement. Then, a linear systems deconvolution was used to eliminate the transfer functions of extraneous factors such as the transducer and electronics, leaving only the frequency-dependent battery reflection coefficient. The LURS technique was first validated on stainless steel and aluminum plates, producing reflection coefficients in line with analytical and numerical finite element modeling (FEM) results. Functioning Li-metal pouch cells were then seeded with lithium chip defects prior to LURS measurements. The presence of these defects is shown to cause a measurable shift in the battery’s through-thickness local resonances. 2D, frequency-domain poroelastic models of ultrasonic propagation in a single-cell lithium metal pouch battery were created and corroborated these findings. Thus, this work has both extended and proven the feasibility of the LURS technique in the detection of local battery defects.

Ultrasound↗

Self-organized dynamics and the transition to turbulence of confined active nematics

We study how confinement transforms the chaotic dynamics of bulk microtubule-based active nematics into regular spatiotemporal patterns. For weak confinements in disks, multiple continuously nucleating and annihilating topological defects self-organize into persistent circular flows of either handedness. Increasing confinement strength leads to the emergence of distinct dynamics, in which the slow periodic nucleation of topological defects at the boundary is superimposed onto a fast procession of a pair of defects. A defect pair migrates toward the confinement core over multiple rotation cycles, while the associated nematic director field evolves from a distinct double spiral toward a nearly circularly symmetric configuration. The collapse of the defect orbits is punctuated by another boundary-localized nucleation event, that sets up long-term doubly periodic dynamics. Comparing experimental data to a theoretical model of an active nematic reveals that theory captures the fast procession of a pair of + 1 / 2 defects, but not the slow spiral transformation nor the periodic nucleation of defect pairs. Theory also fails to predict the emergence of circular flows in the weak confinement regime. The developed confinement methods are generalized to more complex geometries, providing a robust microfluidic platform for rationally engineering 2D autonomous flows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Localizing tetrahedral aluminum in nitrate-bearing gibbsite to constrain defect-impurity coupling

The enhanced radiolytic stability of gibbsite (α-Al(OH) 3 ) containing trace nitrate (NO 3 − ) is a phenomenon in nuclear waste management, but its structural origins remain unresolved. Motivated by the detection of minority tetrahedral aluminum (T d ) defects in synthetic gibbsite, we hypothesized that these sites may participate in NO 3 − retention or mediate H 2 suppression. To evaluate this, we combined orthogonal techniques comprised of spatially selective solid-state 27 Al MAS NMR, comparative spectroscopy, and density functional theory (DFT) modeling. Paramagnetic editing and dynamic nuclear polarization (DNP) MAS NMR confirm that T d defects are confined to the particle interior. DFT calculations reveal no energetic stabilization of NO 3 − near T d sites. Comparative NMR analysis shows that T d is also present in chloride-bearing gibbsite, which exhibits high radiolytic hydrogen yields. These three independent disqualifications rule out T d as a structural contributor to nitrate-mediated suppression and narrow the scope of defect-driven explanations. The findings redirect mechanistic attention away from coordination defects and toward redox-active impurity pathways, providing a refined foundation for understanding radiation tolerance in Al(OH) 3 .

Graham, Trent R. [Pacific Northwest National Labor↗

Atomic oxygen interaction at defect sights in protective coatings on polymers flown on LDEF

Although the Long Duration Exposure Facility (LDEF) has exposed materials with a fixed orientation relative to the ambient low-Earth-orbital environment, arrival of atomic oxygen is angularly distributed as a result of the atomic oxygen's high temperature Maxwellian velocity distribution and the LDEF's orbital inclination. Thus, atomic oxygen entering defects in protective coatings on polymeric surfaces can cause wider undercut cavities than the size of the defect in the protective coating. Because only a small fraction of atomic oxygen reacts upon first impact with most polymeric materials, secondary reactions with lower energy thermally accommodated atomic oxygen can occur. The secondary reactions of scattered and/or thermally accommodated atomic oxygen also contribute to widening the undercut cavity beneath the protective coating defect. As the undercut cavity enlarges, exposing more polymer, the probability of atomic oxygen reacting with underlying polymeric material increases because of multiple opportunities for reaction. Thus, the effective atomic oxygen erosion yield for atoms entering defects increases above that of the unprotected material. Based on the results of analytical modeling and computational modeling, aluminized Kapton multilayer insulation exposed to atomic oxygen on row 9 lost the entire externally exposed layer of polyimide Kapton, yet based on the results of this investigation, the bottom surface aluminum film must have remained in place, but crazed. Atomic oxygen undercutting at defect sites in protective coatings on graphite epoxy composites indicates that between 40 to 100 percent of the atomic oxygen thermally accommodates upon impact, and that the reaction probability of thermally accommodated atomic oxygen may range from 7.7 x 10(exp -6) to 2.1 x 10(exp -3), depending upon the degree of thermal accommodation upon each impact.

Banks, Bruce A.↗

Closure of Internal Porosity in Continuous Casting Bloom During Heavy Reduction Process

To investigate the closure behavior of internal porosity (also referred to as internal void) in continuous casting bloom during heavy reduction (HR) and thus provide theoretical guidance for minimizing this kind of internal defect more effectively with HR, a three-dimensional (3D) mechanical model was developed based on the predicted temperature field by a 2D heat transfer model. With this 3D mechanical model, closure behaviors of internal porosity in continuous casting bloom during HR at and after the strand solidification end under different process conditions were numerically studied. It was found that the void axis length decreased significantly along the bloom thickness direction and increased slightly along the casting and bloom width directions after HR, and the influence of the initial void size on the void closure was not obvious. With a decrease of temperature difference between the bloom surface and center, HR efficiency for minimizing internal void decreased, while the required reduction force significantly increased. Compared with blooms with a uniform temperature distribution of 1100 °C, the void closure index after HR implemented at the strand solidification end was increased by ~ 25 pct. Compared with a conventional flat roll, the application of a convex roll during HR could contribute to minimizing the internal porosity more effectively and significantly enhance the reduction capacity of the withdrawal and straightening units. The void closure index of η{sub s} and η{sub v} (where η{sub s} and η{sub v} were defined based on the variation of the void aspect ratio and the void volume, respectively) was closely related to the equivalent strain (ε{sub eq}) and the hydrostatic integration parameter (Q), respectively, and two mathematical equations were derived to quantitatively describe the relationship of η{sub s} − ε{sub eq} and η{sub v} − Q.

36 MATERIALS SCIENCE↗