Publications

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high-fidelity, validated models used in modal, vibration, static and shock analysis of weapons systems. This document provides a user’s guide to the input for Sierra/SD. Details of input specifications for the different solution types, output options, element types and parameters are included. The appendices contain detailed examples, and instructions for running the software on parallel platforms.

Work evaluating spent nuclear fuel (SNF) dry storage canister surface environments and canister corrosion progressed significantly in FY23, with the goal of developing a scientific understanding of the processes controlling initiation and growth of stress corrosion cracking (SCC) cracks in stainless steel canisters in relevant storage environments. The results of the work performed at Sandia National Laboratories (SNL) will guide future work and will contribute to the development of better tools for predicting potential canister penetration by SCC.

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents fiscal year 2023 (FY23) updates on the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. In FY23, a series of four simulated commercial drying tests was completed. This report presents the temperature and pressure histories of the drying tests as well as axial temperature profiles that can be compared to data from the Electric Power Research Institute (EPRI) High Burnup Demonstration TN-32B cask. Water content measurements and dew point calculations from a Hiden Analytical HPR-30 mass spectrometer are also presented in this report. Due to familiarization with this first-of-a-kind system, refinements to equipment calibration and test procedures have been identified to better match commercial drying cycles for future simulated tests. However, the presented data demonstrate the successful construction and operation of a viable research platform for quantifying residual water content closely approaching that expected in dry storage canisters during commercial drying procedures.

For the first time the optimal local truncation error method (OLTEM) with 125-point stencils and unfitted Cartesian meshes has been developed in the general 3-D case for the Poisson equation for heterogeneous materials with smooth irregular interfaces. The 125-point stencils equations that are similar to those for quadratic finite elements are used for OLTEM. The interface conditions for OLTEM are imposed as constraints at a small number of interface points and do not require the introduction of additional unknowns, i.e., the sparse structure of global discrete equations of OLTEM is the same for homogeneous and heterogeneous materials. The stencils coefficients of OLTEM are calculated by the minimization of the local truncation error of the stencil equations. These derivations include the use of the Poisson equation for the relationship between the different spatial derivatives. Such a procedure provides the maximum possible accuracy of the discrete equations of OLTEM. In contrast to known numerical techniques with quadratic elements and third order of accuracy on conforming and unfitted meshes, OLTEM with the 125-point stencils provides 11-th order of accuracy, i.e., an extremely large increase in accuracy by 8 orders for similar stencils. The numerical results show that OLTEM yields much more accurate results than high-order finite elements with much wider stencils. The increased numerical accuracy of OLTEM leads to an extremely large increase in computational efficiency. Additionally, a new post-processing procedure with the 125-point stencil has been developed for the calculation of the spatial derivatives of the primary function. The post-processing procedure includes the minimization of the local truncation error and the use of the Poisson equation. It is demonstrated that the use of the partial differential equation (PDE) for the 125-point stencils improves the accuracy of the spatial derivatives by 6 orders compared to post-processing without the use of PDE as in existing numerical techniques. At an accuracy of 0.1% for the spatial derivatives, OLTEM reduces the number of degrees of freedom by 900 - 4∙10⁶ times compared to quadratic finite elements. The developed post-processing procedure can be easily extended to unstructured meshes and can be independently used with existing post-processing techniques (e.g., with finite elements).

Accurate prediction of ductile failure is critical to Sandia’s NW mission, but the models are computationally heavy. The costs of including high-fidelity physics and mechanics that are germane to the failure mechanisms are often too burdensome for analysts either because of the person-hours it requires to input them or because of the additional computational time, or both. In an effort to deliver analysts a tool for representing these phenomena with minimal impact to their existing workflow, our project sought to develop modern data-driven methods that would add microstructural information to business-as-usual calculations and expedite failure predictions. The goal is a tool that receives as input a structural model with stress and strain fields, as well as a machine-learned model, and output predictions of structural response in time, including failure. As such, our project spent substantial time performing high-fidelity, three-dimensional experiments to elucidate materials mechanisms of void nucleation and evolution. We developed crystal-plasticity finite-element models from the experimental observations to enrich the findings with fields not readily measured. We developed engineering length-scale simulations of replicated test specimens to understand how the engineering fields evolve in the presence of fine-scale defects. Finally, we developed deep learning convolutional neural networks, and graph-based neural networks to encode the findings of the experiments and simulations and make forward predictions in time for structural performance. This project demonstrated the power of data-driven methods for model development, which have the potential to vastly increase both the accuracy and speed of failure predictions. These benefits and the methods necessary to develop them are highlighted in this report. However, many challenges remain to implementing these in real applications, and these are discussed along with potential methods for overcoming them.

This memo summarizes the simulation of ductile failure propagation work conducted under the ASC project “V&V of Ductile Failure” conducted during FY 23. Physically, the failure propagation consists of crack propagation in the material. In the numerical setting—specifically in a finite element model—propagation can be accomplished through element death when critical conditions occur locally at an element that is then deleted from the simulation. The validation of the finite element models is evaluated by direct comparison between the experimental and simulation results regarding the rate of crack growth and its influence on the load-deflection response of the specimens tested. This work considers two geometries that display stable crack propagation under displacement-controlled conditions. The first geometry consists of hat specimens loaded in compression with nominally identical geometries but made with three different materials: Steel A286, Al 7075-T651 and 304L stainless steel. The three materials represent a range of ductility values that affect the response and crack propagation within the specimen. The crack induced propagates under an essentially mode-II type of deformation. The second geometry consists of a pre-cracked 304L stainless steel compact tension test specimen loaded so as to induce a mode-I deformation at the crack.

Accurate fuel oxidation mechanisms can enable predictive capabilities that aid in advancing combustion technologies. High-level computational kinetics can yield reasonable rate coefficients with uncertainties, in some cases, below a factor of 2. Computed rate coefficients can be constrained further by optimizing against experimental data. Here, we explore the application of genetic algorithm (GA) optimization to constrain computed rate coefficients in complex fuel oxidation mechanisms in conjunction with temperature-dependent species mole fractions from jet-stirred reactor (JSR) measurements. Cyclohexane is a model candidate for understanding the reactivity of cyclic fuels. In this work, we optimize the rate coefficients of the most recent literature cyclohexane mechanism, which incorporates theoretically computed rate coefficients for the reaction networks stemming from the first and second O2 addition pathways, against the experimental results of two separate literature JSR studies. Optimization consistency is evaluated by carrying out three GA optimizations: fitting to the temperature-dependent species mole fractions in each JSR experiment separately and simultaneously fitting the species mole fractions in both experiments. Local sensitivity analyses are used to identify five influential low-temperature oxidation reactions for optimization. Although the three optimizations do not yield identical rate coefficients, the direction of change in all five rate coefficients is consistent among the three optimizations. Performance of the models from the three optimizations is assessed against literature ignition delay times with differences in the level of agreement observed among the different optimizations. Comparisons are made with our recent optimization work of a cyclopentane oxidation master-equation model against time-resolved species concentrations, and insights and improvements of the strategy for constraining rate coefficients using GA optimization are discussed.

In this study, we demonstrate the ability of polarity inversion of sputtered aluminum scandium nitride thin films through post-fabrication processes with domain widths as small as 220 nm at a periodicity of 440 nm. An approach using photo- and electron-beam lithography to generate sub-quarter micrometer feature size with adjustable duty cycle through a lift-off process is presented. The film with a coercive field Ec+ of 5.35 MV/cm was exercised first with a 1 kHz triangular double bipolar wave and ultimately poled with a 0.5 kHz double monopolar wave using a Radiant Precision Premier II tester. The metal polar (M-polar) and nitrogen polar (N-polar) domains were identified and characterized through potassium hydroxide wet etching as well as piezoresponse force microscopy (PFM). Well-distinguished boundaries between the oppositely polarized domain regions were confirmed through the phase diagram of the PFM results. The relationship between the electrode width, poling voltage, and domain growth was experimentally studied and statistically analyzed, where 7.96 nm/V domain width broadening vs escalating poling voltage was observed. This method produces extremely high domain spatial resolution in III-nitride materials via poling and is transferable to a CMOS-compatible photolithography process. The spatial resolution of the periodically poled Al0.68Sc0.32N is suitable for second-harmonic generation of deep ultraviolet through quasi-phase-matching and RF MEMS operating in the X-Band spectrum.

The US Department of Energy (DOE) Nuclear Energy Research Initiative funded the design and construction of the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories. The start-up of the experiment facility and the execution of the experiments described here were funded by the DOE Nuclear Criticality Safety Program. The 7uPCX is designed to investigate critical systems with fuel for light water reactors in the enrichment range above 5 % ²³⁵U. The 7uPCX assembly is a water-moderated and -reflected array of aluminum-clad U(6.90 %)O₂ fuel rods. Other critical experiments performed in the 7uPCX assembly are documented in LEU-COMP-THERM-078, LEU-COMP-THERM-080, LEU-COMP-THERM-096, LEUCOMP-THERM-097, LEU-COMP-THERM-101, and LEU-COMP-THERM-102. The purpose of these experiments was to measure the effects of molybdenum in nearly-critical systems. The molybdenum was introduced into the fuel arrays as tubular sleeves that surrounded some of the fuel rods in the fuel arrays measured. Four hundred molybdenum tubes nominally 12.7 mm outside diameter, 498 mm long, with 0.762 mm wall thickness were provided for the experiments by the Institut de Radioprotection et de Sûreté Nucléaire (IRSN). Small polyethylene adapters at each end of the tubes were used to center each tube on a fuel rod in the assembly. The critical experiments were done using a set of triangular-pitched grid plates fabricated for these experiments. The grid plate set accommodated a fuel array of a total of 1261 fuel rod positions on a pitch of 0.610 in (1.5494 cm) in a series of 20 hexagonal rings surrounding the central fuel rod. The fuel used in these experiments was fabricated using unirradiated 6.90 % enriched UO₂ fuel pellets from fuel elements designed to be used in the internal nuclear superheater section of the Pathfinder boiling water reactor operated in South Dakota by the Northern States Power Company in the 1960s. The fuel elements were obtained from The Pennsylvania State University where they had been stored for many years. The fuel pellets in those fuel elements were removed from the original Incoloy cladding and reclad in 3003 aluminum tubes and end caps for use in the experiments reported here. The five critical experiments in this series were performed in August through December 2022, in the Sandia Critical Experiments (SCX) at the Sandia Pulsed Reactor Facility. Case 1 had no molybdenum sleeves, Case 2 had 208 molybdenum sleeves clustered at the center of the array, Case 3 had 397 molybdenum sleeves clustered at the center of the array, Case 4 had 175 molybdenum sleeves in the central position and in five alternating hexagonal rings, and Case 5 had 331 molybdenum sleeves in the central position and in seven alternating hexagonal rings. All five critical experiments are judged to be acceptable as benchmark experiments.

Tritium permeability in zirconium-based tritium getter critically impacts tritium storage and environmental safety during operation of tritium-producing burnable absorber rods (TPBARs). Previous experiments indicated that during irradiation operation, the hydrogen equilibrium pressured is increased. Further experimental and modeling studies suggested that the enhanced tritium release observed for reactor scale assemblies might be related to a thermal diffusion known as the Soret effect. A direct measurement of the Soret factor, however, has not been performed. To improve TPBAR and other nuclear applications, here we have applied two non-equilibrium molecular dynamics methods to study thermal diffusion of hydrogen isotopes in low-concentration zirconium hydrides. One of the methods produces sufficiently converged results to distinguish crystal orientation, isotope type, and concentration effects. In conclusion, with this method, crystal orientation, isotope type, and concentration effects are discussed.

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

This report describes specific activities in the Fiscal Year (FY) 2023 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package funded by the Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Spent Fuel and Waste Disposition (SFWD). The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and system performance assessment (PA) models in several potential host-rock environments, and to simulate and analyze these generic repository concepts and models using the GDSA Framework toolkit and other tools as needed. The specific GDSA goal addressed in this report is reference case development, simulation, and analysis for the unsaturated alluvium (UZ), one of the four potential host-rocks considered by the GDSA. Further, we aim to exercise the simulation tools and methodologies under development by GDSA for PA modelling.

The Sibling Pin test campaign is a Department of Energy (DOE) research activity within the Spent Fuel and Waste Science and Technology (SFWST) program that is tasked with characterization of high burnup (HBU) fuel in support of the High Burnup Spent Fuel Data Project. Of the 25 fuel rods in the Sibling Pin inventory, approximately 9 rod lengths have been consumed during the first phase (Phase I) of the test campaign leaving approximately 16 rod lengths for the second phase (Phase II) of testing. This plan outlines the Phase II testing and the motivations for performing these tests. Priorities for Phase II testing are based on previously identified knowledge gaps, lessons-learned from Phase I work, the original objectives of the High Burnup Spent Fuel Data Project and the Sibling Pin test campaign, and input from external stakeholders. The priorities for Phase II testing are to obtain data to characterize the effects of annealing on cladding mechanical properties and fuel rod performance, to quantify the creep behavior of cladding materials and fuel rods and the effects of creep deformations on the performance of cladding and fuel rods, and to gather data to support the final closure of the hydride reorientation and radial hydride induced embrittlement gap for HBU fuel rods.

Microneedle sensors could enable minimally-invasive, continuous molecular monitoring – informing on disease status and treatment in real-time. Wearable sensors for pharmaceuticals, for example, would create opportunities for treatments personalized to individual pharmacokinetics. Here, we demonstrate a commercial-off-the-shelf (COTS) approach for microneedle sensing using an electrochemical aptamer-based sensor that detects the high-toxicity antibiotic, vancomycin. Wearable monitoring of vancomycin could improve patient care by allowing targeted drug dosing within its narrow clinical window of safety and efficacy. To produce sensors, we miniaturize the electrochemical aptamer-based sensors to a microelectrode format, and embed them within stainless steel microneedles (sourced from commercial insulin pen needles). The microneedle sensors achieve quantitative measurements in body-temperature undiluted blood. Further, the sensors effectively maintain electrochemical signal within porcine skin. This COTS approach requires no cleanroom fabrication or specialized equipment, and produces individually-addressable, sterilizable microneedle sensors capable of easily penetrating the skin. In the future, this approach could be adapted for multiplexed detection, enabling real-time monitoring of a range of biomarkers.

Aging of silicon photovoltaic (PV) module packaging is one of the greatest limiters of PV module service lifetimes. Module characterization typically focuses on power degradation metrics, which do not convey the complexities of often simultaneous degradation mechanisms. In this work, PV modules with pristine references and known fielding histories were investigated by non-destructive and destructive methods. Modules from Canadian Solar, Mission Solar, and Hanwha Q-Cells were fielded for up to three years; select modules were removed from fielding each year for coring to allow for characterization of the encapsulant. Modules are commonly encapsulated with two protective layers of partially-crystalline ethylene vinyl acetate (EVA) polymer that must undergo a crosslinking reaction to achieve desired properties. The extent of crystallinity of the encapsulants as studied by differential scanning calorimetry showed differences between manufacturers and over time. Some encapsulants showed different magnitudes of crystal sizes which changed after fielding; encapsulants with the monodisperse crystal sizes did not change with fielding. This is due to differences in thermal history. These results have implications for stress development during module aging, since EVA crystal melting and crosslinking reactions can result in encapsulant density changes.

Translating the surging interest in neuromorphic electronic components, such as those based on nonlinearities near Mott transitions, into large-scale commercial deployment faces steep challenges in the current lack of means to identify and design key material parameters. These issues are exemplified by the difficulties in connecting measurable material properties to device behavior via circuit element models. Here, the principle of local activity is used to build a model of VO2/SiN Mott threshold switches by sequentially accounting for constraints from a minimal set of quasistatic and dynamic electrical and high-spatial-resolution thermal data obtained via in situ thermoreflectance mapping. By combining independent data sets for devices with varying dimensions, the model is distilled to measurable material properties, and device scaling laws are established. The model can accurately predict electrical and thermal conductivities and capacitances and locally active dynamics (especially persistent spiking self-oscillations). The systematic procedure by which this model is developed has been a missing link in predictively connecting neuromorphic device behavior with their underlying material properties, and should enable rapid screening of material candidates before employing expensive manufacturing processes and testing procedures.

Motivated by recent experimental results we calculate from first-principles the lifetime of low-energy quasiparticles in bilayer graphene (BLG). Here, we take into account the scattering rate arising from electron-electron interactions within the GW approximation for the electron self-energy and consider several p-type doping levels ranging from 0 to ρ ≈ 2.4 × 10¹² holes/cm². In the undoped case we find that the average inverse lifetime scales linearly with energy away from the charge neutrality point, with values in good agreement with experiments. The decay rate is approximately three times larger than in monolayer graphene, a consequence of the enhanced screening in BLG. In the doped case, the dependence of the inverse lifetime on quasiparticle energy acquires a non-linear component due to the opening of an additional decay channel mediated by acoustic plasmons.

The Spent Fuel Waste Disposition (SFWD) program is planning to conduct a full-scale seismic shake table test on the dry storage systems of spent nuclear fuel (SNF) to close the gap related to seismic loads on fuel assemblies in dry storage systems. This test will allow for quantifying the strains and accelerations on surrogate fuel assembly hardware and cladding during earthquakes of different magnitudes and frequency content. Full-scale testing is needed because a dry storage system is a complex and highly nonlinear system making it hard to predict (model) the responses to seismic excitations. The non-linearity arises from the multiple spatial gaps in the system – between fuel rods and the basket, between the basket and dry storage canister, between the dry storage canister and the storage cask (overpack), and ventilation gaps. The non-linearities pose significant limitations on the value of tests with scaled systems.

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

Here, we study the impact of deep-level defects on trap-assisted Auger–Meitner recombination in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) method and deep-level optical spectroscopy (DLOS). Carrier dynamics information, including carrier lifetime, recombination rate, and carrier density, is obtained from SSEL, while DLOS is used to obtain the deep-level defect density. Through fitting the nonradiative recombination rates of wafers with different deep-level defect densities, we obtain the Shockley–Read–Hall (SRH) and trap-assisted Auger–Meitner recombination (TAAR) coefficients. We show that defect-related nonradiative recombination, including both SRH and TAAR, accounts for a relatively small fraction of the total nonradiative recombination, which is dominated by intrinsic Auger–Meitner recombination. The interplay between carrier localization and Coulomb enhancement has a different impact on radiative and intrinsic Auger–Meitner recombination. Evidence is presented that the imbalance between the change of radiative and intrinsic Auger–Meitner recombination is the primary cause of the efficiency droop at high carrier densities in the samples studied.

Cast Monel alloys are used in applications requiring a combination of good mechanical properties and excellent resistance to corrosion. Despite prevalent industrial use, relatively few studies have been conducted to investigate the relationships between composition, solidification behavior, and microstructure. Given that these alloys are used in the cast and welded conditions, these factors have a significant influence over the material properties. Here, in this work, microstructural characterization, electron probe microanalysis, X-ray diffraction, and differential scanning calorimetry were used to study how changes in Si and Nb concentrations affected the solidification path and microstructure of Monel alloys. It was found that increasing Nb concentration stabilized higher amounts of MC carbides and suppressed graphite formation during solidification. It was also found that the high nominal concentration and segregation of Si to the liquid led to the formation of Ni₃₁Si₁₂ and other silicides via terminal eutectic reactions at the end of solidification. A pseudo-binary solidification diagram was constructed using experimental data and was applied to predict the mass fraction of solidified eutectic as a function of composition. The modeled microstructures were found to be in good agreement with experimentally measured phase fractions.

We study the impact of deep-level defects on trap-assisted Auger-Meitner recombination in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) method and deep-level optical spectroscopy (DLOS). Carrier dynamics information, including carrier lifetime, recombination rate, and carrier density, is obtained from SSEL, while DLOS is used to obtain the deep-level defect density. Through fitting the nonradiative recombination rates of wafers with different deep-level defect densities, we obtain the Shockley-Read-Hall (SRH) and trap-assisted Auger-Meitner recombination (TAAR) coefficients. We show that defect-related nonradiative recombination, including both SRH and TAAR, accounts for a relatively small fraction of the total nonradiative recombination, which is dominated by intrinsic Auger-Meitner recombination. The interplay between carrier localization and Coulomb enhancement has a different impact on radiative and intrinsic Auger-Meitner recombination. Evidence is presented that the imbalance between the change of radiative and intrinsic Auger-Meitner recombination is the primary cause of the efficiency droop at high carrier densities in the samples studied.

Heterogenous materials under shock compression can be expected to reach different shock states throughout the material according to local differences in microstructure and the history of wave propagation. Here, a compact, multiple-beam focusing optic assembly is used with high-speed velocimetry to interrogate the shock response of porous tantalum films prepared through thermal-spray deposition. The distribution of particle velocities across a shocked interface is compared to results obtained using a set of defocused interferometric beams that sampled the shock response over larger areas. The two methods produced velocity distributions along the shock plateau with the same mean, while a larger variance was measured with narrower beams. The finding was replicated using three-dimensional, mesoscopically resolved hydrodynamics simulations of solid tantalum with a pore structure mimicking statistical attributes of the material and accounting for radial divergence of the beams, with agreement across several impact velocities. Accounting for pore morphology in the simulations was found to be necessary for replicating the rise time of the shock plateau. The validated simulations were then used to show that while the average velocity along the shock plateau could be determined accurately with only a few interferometric beams, accurately determining the width of the velocity distribution, which here was approximately Gaussian, required a beam dimension much smaller than the spatial correlation lengthscale of the velocity field, here by a factor of ∼30×, with implications for the study of other porous materials.

Here, we perform all-atom molecular dynamics simulations of lithium triflate in 1,2-dimethoxyethane using six different literature force fields. This system is representative of many experimental studies of lithium salts in solvents and polymers. We show that multiple historically common force fields for lithium ions give qualitatively incorrect results when compared with those from experiments and quantum chemistry calculations. We illustrate the importance of correctly selecting force field parameters and give recommendations on the force field choice for lithium electrolyte applications.