Publications

The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. We utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.

Laccases from white-rot fungi catalyze lignin depolymerization, a critical first step to upgrading lignin to valuable biodiesel fuels and chemicals. In this study, a wildtype laccase from the basidiomycete Fomitiporia mediterranea (Fom_lac) and a variant engineered to have a carbohydrate-binding module (Fom_CBM) were studied for their ability to catalyze cleavage of β-O-4′ ether and C–C bonds in phenolic and non-phenolic lignin dimers using a nanostructure-initiator mass spectrometry-based assay. Fom_lac and Fom_CBM catalyze β-O-4′ ether and C–C bond breaking, with higher activity under acidic conditions (pH < 6). The potential of Fom_lac and Fom_CBM to enhance saccharification yields from untreated and ionic liquid pretreated pine was also investigated. Adding Fom_CBM to mixtures of cellulases and hemicellulases improved sugar yields by 140% on untreated pine and 32% on cholinium lysinate pretreated pine when compared to the inclusion of Fom_lac to the same mixtures. Adding either Fom_lac or Fom_CBM to mixtures of cellulases and hemicellulases effectively accelerates enzymatic hydrolysis, demonstrating its potential applications for lignocellulose valorization. We postulate that additional increases in sugar yields for the Fom_CBM enzyme mixtures were due to Fom_CBM being brought more proximal to lignin through binding to either cellulose or lignin itself.

Carbon fiber epoxy composites are increasingly used in systems requiring a material that is both strong and light weight, as in airplanes, cars, and pressure vessels. In fire environments, carbon fiber epoxy composites are a fuel source subject to oxidation. This literature review seeks to provide material properties as well as uncertainty bounds for those properties for computational models of decomposing carbon fiber epoxy composites. The goal is to guide analysts when measurements are lacking

Recent experimental studies suggest the use of spatially extended laser beam profiles as a strategy to control the melt pool during laser powder bed fusion (LPBF) additive manufacturing. However, linkages connecting laser beam profiles to thermal fields and resultant microstructures have not been established. Herein, we employ a coupled thermal transport-Monte Carlo model to predict the evolution of temperature fields and grain microstructures during LPBF using Gaussian, ring, and Bessel beam profiles. Simulation results reveal that the ring-shaped beam yields lower temperatures compared with the Gaussian beam. Owing to the small melt pool size when using the Bessel beam, the grains are smaller in size and more equiaxed compared to those using the Gaussian and ring beams. Our approach provides future avenues to predict the impact of laser beam shaping on microstructure development during LPBF.

Measurement

The impact of the high-power impulse magnetron sputtering (HiPIMS) pulse width on the crystallization, microstructure, and ferroelectric properties of undoped HfO2 films is investigated. HfO2 films were sputtered from a hafnium metal target in an Ar/O2 atmosphere, varying the instantaneous power density by changing the HiPIMS pulse width with fixed time-averaged power and pulse frequency. The pulse width is shown to affect the ion-to-neutral ratio in the depositing species with the shortest pulse durations leading to the highest ion fraction. In situ x-ray diffraction measurements during crystallization demonstrate that the HiPIMS pulse width impacts nucleation and phase formation, with an intermediate pulse width of 110 μs stabilizing the ferroelectric phase over the widest temperature range. Although the pulse width impacts the grain size with the lowest pulse width resulting in the largest grain size, the grain size does not strongly correlate with the phase content or ferroelectric behavior in these films. These results suggest that precise control over the energetics of the depositing species may be beneficial for forming the ferroelectric phase in this material.

During fracture amorphous oxides exhibit irreversible processes, including inelastic and nonrecoverable relaxation effects in the process zone surrounding the crack tip. Here, classical molecular dynamics simulations were used with a reactive forcefield to evaluate inelastic relaxation processes in five amorphous sodium silicate compositions. Overall, the 20% Na2O-SiO2(NS20) composition exhibited the most inelastic relaxation, followed by the 15% Na2O-SiO2(NS15) composition, the 25% Na2O-SiO2(NS25) composition, and finally the 10% (NS10) and 30% (NS30) Na2O-SiO2 compositions. Coordination analysis of the Na+ ions identified that during inelastic relaxation the Na+ ions were increasingly coordinated by nonbridging oxygens (NBOs) for the NS10 and NS15 compositions, which was supported by radial analysis of the O-Na-O bond angles surrounding the crack tip. Across the sodium silicate compositional range, two different inelastic relaxation mechanism were identified based on the amount of bridging oxygens (BOs) and NBOs in the Na+ ion coordination shell. At lower (NS10) and higher (NS30) sodium compositions, the entire structured relaxed toward the crack tip. In contrast at intermediate sodium concentrations (NS20) the Na+ ion migrates toward the crack tip separately from the network structure. By developing a fundamental understanding of how modified silica systems respond to static stress fields, we will be able to predict how varying amorphous silicate systems exhibit slow crack growth.

Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation. SIGNIFICANCE STATEMENT: Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add ordersof-magnitude more events than previously catalogued.

Current nuclear facility emergency planning zones (EPZs) are based on outdated distance-based criteria, predating comprehensive dose and risk-informed frameworks. Recent advancements in simulation tools have permitted the development of site-specific, dose, and risk-based consequence-driven assessment frameworks. This study investigated the computation of advanced reactor (AR) EPZs using two atmospheric dispersion models: a straight-line Gaussian plume model (GPM) and a semi-Lagrangian Particle in Cell (PIC). Two case studies were conducted: (1) benchmarking the NRC SOARCA study for the Peach Bottom Nuclear Generating Station and (2) analyzing an advanced INL Heat Pipe Design A microreactor's end-of-cycle inventory. The dose criteria for both cases were 10 mSv at mean weather conditions and 50 mSv at 95th percentile weather conditions at 96 h post-release. Results demonstrated that GPM and PIC estimated similar mean peak dose levels for large boiling water reactors in the farfield case, placing EPZ limits beyond current regulations. For ARs with source terms remaining in the nearfield, PIC modeling without specific nearfield considerations could result in excessively high doses and inaccurate EPZ designations. PIC dispersion demonstrated an order of magnitude higher estimate of nearfield inhalation dose contribution when compared to GPM results. Both models significantly reduced EPZ sizing within the nearfield. Thus, reductions in the AR source term may eliminate the need for a separate EPZ.

This report summarizes important nuances in local water concerns and potential climate impacts that could influence the roll-out of technologies associated with energy transitions. To understand how water and climate dynamics could be influencing these activities for three countries.

A generalized closed-form equation for the shaded collector fraction in solar arrays on rolling or undulating terrain is provided for single-axis tracking and fixed-tilt systems. The equation accounts for different rotation angles between the shaded and shading trackers, cross-axis slope between the two trackers, and offset between the collector plane and axis of rotation. The validity of the equation is demonstrated through comparison with numerical ray-tracing simulations and remaining minor sources of error are quantified. Additionally, a simple procedure to determine backtracking rotations for each row in an array installed on the rolling terrain (varying in the direction perpendicular to the tracker axes) is provided. The backtracking equation accounts for a desired shaded fraction (including complete shade avoidance) as well as an axis-collector offset. Test cases are provided to facilitate implementation of these equations.

Ground heat flux (G0) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G0 data (measured or modeled) for snow-free period as a reference. When observed G0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

Frontiers in Quantum Science and Technology

Magnetized Liner Inertial Fusion experiments have been performed at the Z facility at Sandia National Laboratories. These experiments use deuterium fuel, which produces 2.45 MeV neutrons on reaching thermonuclear conditions. To study the spatial structure of neutron production, the one-dimensional imager of neutrons diagnostic was fielded to record axial resolved neutron images. In this diagnostic, neutrons passing through a rolled edge aperture form an image on a CR-39-based solid state nuclear track detector. Here, we present a modified generalized expectation-maximization algorithm to reconstruct an axial neutron emission profile of the stagnated fusion plasma. We validate the approach by comparing the reconstructed neutron emission profile to an x-ray emission profile provided by a time-integrated pinhole camera.

During hypersonic flight, compressional and viscous heating of the air can form a plasma layer which encases the aircraft. If the boundary layer becomes turbulent, then the electron density fluctuations can effect a parasitic modulation in microwave signals transmitted through the plasma. We developed an approach for studying the interaction of microwave signals with a turbulent, hypersonic plasma layer. The approach affords a great deal of flexibility in both the plasma layer model and the antenna configuration. We then analyzed a situation in which microwaves, transmitted from a rectangular aperture antenna, propagate through a turbulent plasma layer to a distant receiver. We characterized the first- and second-order statistics of the computed parasitic modulation and quantified the depolarization of the signal. The amplitude fluctuations are lognormally distributed at low frequencies and Rice-distributed at high frequencies. Fluctuations in the copolarized phase and amplitude of the far-field signal are strongly anticorrelated. We used a multioutput Gaussian process (MOGP) to model these quantities. The efficacy of the MOGP model is demonstrated by recovering the time evolution of the copolarized phase given the copolarized amplitude and occasional measurements of the phase.

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysicsscenarios. The code suite is composed of several specialized applications which can operate either instandalone mode or coupled with each other. Arpeggio is a supported utility that enables loose couplingof the various Sierra Mechanics applications by providing access to Framework services that facilitatethe coupling.

Achieving commercially acceptable Zn-MnO2 rechargeable batteries depends on the reversibility of active zinc and manganese materials, and avoiding side reactions during the second electron reaction of MnO2. Typically, liquid electrolytes such as potassium hydroxide (KOH) are used for Zn-MnO2 rechargeable batteries. However, it is known that using liquid electrolytes causes the formation of electrochemically inactive materials, such as precipitation Mn3O4 or ZnMn2O4 resulting from the uncontrollable reaction of Mn3+ dissolved species with zincate ions. In this paper, hydrogel electrolytes are tested for MnO2 electrodes undergoing two-electron cycling. Improved cell safety is achieved because the hydrogel electrolyte is non-spillable, according to standards from the US Department of Transportation (DOT). The cycling of “half cells” with advanced-formulation MnO2 cathodes paired with commercial NiOOH electrodes is tested with hydrogel and a normal electrolyte, to detect changes to the zincate crossover and reaction from anode to cathode. These half cells achieved ≥700 cycles with 99% coulombic efficiency and 63% energy efficiency at C/3 rates based on the second electron capacity of MnO2. Other cycling tests with “full cells” of Zn anodes with the same MnO2 cathodes achieved ~300 cycles until reaching 50% capacity fade, a comparable performance to cells using liquid electrolyte. Electrodes dissected after cycling showed that the liquid electrolyte allowed Cu ions to migrate more than the hydrogel electrolyte. However, measurements of the Cu diffusion coefficient showed no difference between liquid and gel electrolytes; thus, it was hypothesized that the gel electrolytes reduced the occurrence of Cu short circuits by either (a) reducing electrode physical contact to the separator or (b) reducing electro-convective electrolyte transport that may be as important as diffusive transport.

The multi-harmonic balance method combined with numerical continuation provides an efficient framework to compute a family of time-periodic solutions, or response curves, for large-scale, nonlinear mechanical systems. The predictor and corrector steps repeatedly solve a sequence of linear systems that scale by the model size and number of harmonics in the assumed Fourier series approximation. In this paper, a novel Newton–Krylov iterative method is embedded within the multi-harmonic balance and continuation algorithm to efficiently compute the approximate solutions from the sequence of linear systems that arise during the prediction and correction steps. The method recycles, or reuses, both the preconditioner and the Krylov subspace generated by previous linear systems in the solution sequence. A delayed frequency preconditioner refactorizes the preconditioner only when the performance of the iterative solver deteriorates. The GCRO-DR iterative solver recycles a subset of harmonic Ritz vectors to initialize the solution subspace for the next linear system in the sequence. The performance of the iterative solver is demonstrated on two exemplars with contact-type nonlinearities and benchmarked against a direct solver with traditional Newton–Raphson iterations.

PDMATLAB2D is a meshfree peridynamics implementation in MATLAB suitable for simulation of two-dimensional fracture problems. The purpose of this code is twofold. First, it provides an entry-level peridynamics computational tool for educational and training purposes. Second, it serves as an accessible and easily modifiable computational tool for peridynamics researchers who would like to adapt the code for a multitude of peridynamics simulation scenarios. The current version of the code implements a bond-based brittle elastic peridynamic model and a critical stretch criterion for bond breaking. However, the code is designed to be extendable for other peridynamic models and computational features. In this paper, we provide an overview of the code structure and functions with illustrative examples. Due to the integrated computation and postprocessing MATLAB capabilities, PDMATLAB2D can serve as an effective testbed for testing new constitutive models and advanced numerical features for peridynamics computations.

Junctions are discontinuities in flat grain boundaries that arise in all polycrystalline materials and are thought to play important roles in the response of a grain boundary network to thermal and mechanical loads. A key open question concerns the mechanisms by which solute segregation to junctions impacts properties of the grain boundary. Here, in this work, we investigate the influence of grain boundary facet junctions on solute embrittlement, and we present an analytical model that uses the hydrostatic stress field contributed by dislocations at multiple junctions to describe these effects. Specifically, we study junctions between {112} facets of various lengths in Au $\langle111\rangle$ Σ3 tilt grain boundaries. Copper and silver solutes are employed to determine if the effect of junctions on solute segregation and embrittlement is dependent on size relative to the host. Combined, atomistic simulation data and the analytical model show that Cu and Ag have opposite segregation responses to junctions due to the sign of the hydrostatic stress field induced by junctions. However, a positive shift in the embrittling potency is computed near junctions regardless of solute type or the stress state of the segregation site. Hence, for the conditions studied, junctions consistently shift the energetic landscape towards embrittlement.

Glycoboehmite (GB) materials are synthesized by a solvothermal reaction to form layered aluminum oxyhydroxide (boehmite) modified by intercalated butanediol molecules. These hybrid materials offer a platform to design materials with potentially novel sorption, wetting, and catalytic properties. Several synthetic methods have been used, resulting in different structural and spectroscopic properties, but atomistic detail is needed to determine the interlayer structure to explore the synthetic control of GB materials. Here, we use classical molecular dynamics (MD) simulations to compare the structural properties of GB interlayers containing chemisorbed butanediol molecules as a function of diol loading. Accompanying quantum (density functional theory, DFT) static calculations and MD simulations are used to validate the classical model and compute the infrared spectra of various models. Classical MD results reveal the existence of two unique interlayer environments at higher butanediol loading, corresponding to smaller (cross-linked) and expanded interlayers. DFT-computed infrared spectra reveal the sensitivity of the aluminol O-H stretch frequencies to the interlayer environment, consistent with the spectrum of the synthesized material. Insight from these simulations will aid in the characterization of the newly synthesized GB materials.

The paper deals with a new effective numerical technique on unfitted Cartesian meshes for simulations of heterogeneous elastic materials. Here, we develop the optimal local truncation error method (OLTEM) with 27- point stencils (similar to those for linear finite elements) for the 3-D time-independent elasticity equations with irregular interfaces. Only displacement unknowns at each internal Cartesian grid point are used. The interface conditions are added to the expression for the local truncation error and do not change the width of the stencils. The unknown stencil coefficients are calculated by the minimization of the local truncation error of the stencil equations and yield the optimal second order of accuracy for OLTEM with the 27-point stencils on unfitted Cartesian meshes. A new post-processing procedure for accurate stress calculations has been developed. Similar to basic computations it uses OLTEM with the 27-point stencils and the elasticity equations. The post-processing procedure can be easily extended to unstructured meshes and can be independently used with existing numerical techniques (e.g., with finite elements). Numerical experiments show that at an accuracy of 0.1% for stresses, OLTEM with the new post-processing procedure significantly (by 10⁵-10⁹ times) reduces the number of degrees of freedom compared to linear finite elements. OLTEM with the 27-point stencils yields even more accurate results than high-order finite elements with wider stencils.

Ionic assemblies, or clusters, determine the structure and dynamics of ionizable polymers and enable their many applications. Fundamental to attaining well-defined materials is controlling the balance between the van der Waals interactions that govern the backbone behavior and the forces that drive the formation of ionic clusters. Here, using small-angle neutron scattering and fully atomistic molecular dynamics simulations, the structure of a model ionomer, sulfonated polystyrene in toluene solutions, was investigated as the cluster cohesion was tweaked by the addition of ethanol. The static structure factor was measured by both techniques and correlated with the size of the ionic clusters as the polymer concentration was varied. The conjunction of SANS results and molecular insight from MD simulations enabled the determination of the structure of these inhomogeneous networks on multiple length scales. We find that across the entire concentration range studied, a network driven by the formation of ionic clusters was formed, where the size of the clusters drives the inhomogeneity of these systems. Tweaking the ionic clusters through the addition of ethanol impacts the packing of the sulfonated groups, their shape, and their size distribution, which, in turn, affects the structure of these networks.

Characterizing and identifying cells in multicellular in vitro models remain a substantial challenge. Here, we utilize hyperspectral confocal Raman microscopy and principal component analysis coupled with linear discriminant analysis to form a label-free, noninvasive approach for classifying bone cells and osteosarcoma cells. Through the development of a library of hyperspectral Raman images of the K7M2-wt osteosarcoma cell lines, 7F2 osteoblast cell lines, RAW 264.7 macrophage cell line, and osteoclasts induced from RAW 264.7 macrophages, we built a linear discriminant model capable of correctly identifying each of these cell types. The model was cross-validated using a k-fold cross validation scheme. The results show a minimum of 72% accuracy in predicting cell type. We also utilize the model to reconstruct the spectra of K7M2 and 7F2 to determine whether osteosarcoma cancer cells and normal osteoblasts have any prominent differences that can be captured by Raman. We find that the main differences between these two cell types are the prominence of the β-sheet protein secondary structure in K7M2 versus the α-helix protein secondary structure in 7F2. Additionally, differences in the CH2 deformation Raman feature highlight that the membrane lipid structure is different between these cells, which may affect the overall signaling and functional contrasts. Overall, we show that hyperspectral confocal Raman microscopy can serve as an effective tool for label-free, nondestructive cellular classification and that the spectral reconstructions can be used to gain deeper insight into the differences that drive different functional outcomes of different cells.

Superconducting topological systems formed by a strong 3D topological insulator (TI) in proximity to a conventional s-wave superconductor (SC) have been intensely studied, as they may host Majorana zero modes. However, there are limited experimental realizations of TI-SC systems in which robust superconducting pairing is induced on the surface states of the TI and a topological superconducting state is established. Here, we fabricate a TI-SC system by depositing, via a focused ion beam, tungsten (W) nanoscale clusters on the surface of TI Bi0.91Sb0.09. We find that the resulting heterostructure supports phase-slip lines (PSLs) that act as effective Josephson junctions (JJs). We probe the response of the system to microwave radiation. We find that for some ac frequencies, and powers, the resulting Shapiro steps’ structure of the voltage-current characteristic exhibits a missing first step and an unexpectedly wide second Shapiro step. The theoretical analysis of the measurements shows that the unusual Shapiro response arises from the interplay between a static JJ and a dynamic one and allows us to identify the conditions under which the missing first step can be attributed to the topological nature of the JJs formed by the PSLs. Our results suggest an approach to induce superconductivity in a TI, a route to realizing highly transparent topological JJs, and show how the response of superconducting systems to microwave radiation can be used to infer the dynamics of PSLs. Highly transparent topological junctions are promising candidates to realize vector field sensors with very high sensitivity. In addition, due to the nontrivial Berry phase of the TI’s surface states such junctions can be in a topological state which is ideal to create topologically protected qubits.

Testing is pivotal for early identification of disease and subsequent infection control. Pathogens’ nucleic acid sequence can change due to naturally-occurring genetic drift or intentional modification. Because of the reliance on molecular assays for human, animal, and plant disease diagnosis, we must understand how nucleotide mutations affect test accuracy. Primers designed against original lineages of a pathogen may be less efficient at detecting variants with genetic changes in priming regions. Here, we made single- and multi-point mutations in priming regions of a model SARS-CoV-2 template that was used as input for a loop-mediated isothermal amplification (LAMP) assay. We found that many of the modifications impacted assay sensitivity, amplification speed, or both. Further research exploring mutations at every position in each of the eight priming regions should be conducted to evaluate trends and determine generalizability.

This presentation includes a look into Sandia critical experiments including the 7uPCX, BUCCX, and assembly design. This presentation touches on the completion of IER 305 with CED-3b, CED-4a, and CED-4b. Finally, there are preparations to perform IER 441 including new hardware, critical configurations, and next steps.

This presentation includes a IER 441 assembly overview and the difference between IER 305 AND IER 441 with central test region assembly and hex pitch. Next this presentation looks at IER 441 procurement issues and delays and new hardware. additionally conducted was a SPRF/CX: IER 441 hardware test fit (Success)). This presentation concludes with lessons learned and acknowledgements.

This presentation titled "Updates on UO₂-BeO Experiment (IER 523)" covers experiment status, experiment motivation, CED-1 summary, current efforts (CED-2), and includes a concluding summary.

Wurtzite ferroelectrics are an emerging material class that expands the functionality and application space of wide bandgap semiconductors. Promising physical properties of binary wurtzite semiconductors include a large, reorientable spontaneous polarization, direct band gaps that span from the infrared to ultraviolet, large thermal conductivities and acoustic wave velocities, high mobility electron and hole channels, and low optical losses. The ability to reverse the polarization in ternary wurtzite semiconductors at room temperature enables memory and analog type functionality and quasi-phase matching in optical devices and boosts the ecosystem of wurtzite semiconductors, provided the appropriate combination of properties can be achieved for any given application. In this article, advances in the design, synthesis, and characterization of wurtzite ferroelectric materials and devices are discussed. Highlights include: the direct and quantitative observation of polarization reversal of ∼135 μC/cm2 charge in Al1−xBxN via electron microscopy, Al1−xBxN ferroelectric domain patterns poled down to 400 nm in width via scanning probe microscopy, and full polarization retention after over 1000 h of 200 °C baking and a 2× enhancement relative to ZnO in the nonlinear optical response of Zn1−xMgxO. The main tradeoffs, challenges, and opportunities in thin film deposition, heterostructure design and characterization, and device fabrication are overviewed.

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%-85% purity. In the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied. Chemical kinetic simulations were performed to predict the effects of cyclo-pentane impurities on the properties, octane rating, and autoignition reactivity under homogeneous charge compression-ignition conditions of PACE-20. From the numerical results, cyclo-pentane with 85% purity or higher is required to reasonably match both the research octane number and motor octane number of the target gasoline. Finally, homogeneous charge compression-ignition engine simulations show that impurities have only a modest effect on reactivity at naturally aspirated conditions, but cyclo-pentane purity is critical to properly replicate the pressure dependency of the reactivity.

In this study, x-ray imaging addresses many challenges with visible light imaging in extreme environments, where optical diagnostics such as digital image correlation (DIC) and particle image velocimetry (PIV) suffer biases from index of refraction changes and/or cannot penetrate visibly occluded objects. However, conservation of intensity—the fundamental principle of optical image correlation algorithms—may be violated if ancillary components in the X-ray path besides the surface or fluid of interest move during the test. The test series treated in this work sought to characterize the safe use of fiber-epoxy composites in aerospace and aviation industries during fire accident scenarios. Stereo X-ray DIC was employed to measure test unit deformation in an extreme thermal environment involving a visibly occluded test unit, incident surface heating to temperatures above 600°C, and flames and soot from combusting epoxy decomposition gasses. The objective of the current work is to evaluate two solutions to resolve the violation of conservation of intensity that resulted from both the test unit and the thermal chamber deforming during the test. The first solution recovered conservation of intensity by pre-processing the path-integrated X-ray images to isolate the DIC pattern of the test unit from the thermal chamber components. These images were then correlated with standard, optical DIC software. The second solution, called Path-Integrated Digital Image Correlation (PI-DIC), modified the fundamental matching criterion of DIC to account for multiple, independently-moving components contributing to the final image intensity. The PI-DIC algorithm was extended from a 2D framework to a stereo framework and implemented in a custom DIC software. Both solutions accurately measured the cylindrical shape of the undeformed test unit, recovering radii values of R = 76.20±0.12 mm compared to the theoretical radius of R_theor = 76.20 mm. During the test, the test unit bulged asymmetrically as decomposition gasses pressurized the interior and eventually burned in a localized jet. Both solutions measured the heterogeneous radius of this bulge, which reached a maximum of approximately R = 91 mm, with a discrepancy of 2–3% between the two solutions. Two solutions that resolve the violation of conservation of intensity for path-integrated X-ray images were developed. Both were successfully employed in a stereo X-ray DIC configuration to measure deformation of an aluminum-skinned, fiber-epoxy composite test unit in a fire accident scenario.

Motivated by reducing errors in the energy budget related to enthalpy fluxes within the Energy Exascale Earth System Model (E3SM), we study several physics-dynamics coupling approaches. Using idealized physics, a moist rising bubble test case, and the E3SM's nonhydrostatic dynamical core, we consider unapproximated and approximated thermodynamics applied at constant pressure or constant volume. With the standard dynamics and physics time-split implementation, we describe how the constant-pressure and constant-volume approaches use different mechanisms to transform physics tendencies into dynamical motion and show that only the constant-volume approach is consistent with the underlying equations. Using time step convergence studies, we show that the two approaches both converge but to slightly different solutions. We reproduce the large inconsistencies between the energy flux internal to the model and the energy flux of precipitation when using approximate thermodynamics, which can only be removed by considering variable latent heats, both when computing the latent heating from phase change and when applying this heating to update the temperature. Finally, we show that in the nonhydrostatic case, for physics applied at constant pressure, the general relation that enthalpy is locally conserved no longer holds. In this case, the conserved quantity is enthalpy plus an additional term proportional to the difference between hydrostatic pressure and full pressure.

Over the last few years, crystalline topology has been used in photonic crystals to realize edge- and corner-localized states that enhance light-matter interactions for potential device applications. However, the band-theoretic approaches currently used to classify bulk topological crystalline phases cannot predict the existence, localization, or spectral isolation of any resulting boundary-localized modes. While interfaces between materials in different crystalline phases must have topological states at some energy, these states need not appear within the band gap, and thus may not be useful for applications. Here, we derive a class of local markers for identifying material topology due to crystalline symmetries, as well as a corresponding measure of topological protection. As our real-space-based approach is inherently local, it immediately reveals the existence and robustness of topological boundary-localized states, yielding a predictive framework for designing topological crystalline heterostructures. In conclusion, beyond enabling the optimization of device geometries, we anticipate that our framework will also provide a route forward to deriving local markers for other classes of topology that are reliant upon spatial symmetries.

Compressed hydrogen stored at cryogenic temperatures has a much higher density than room-temperature storage, which enables large-scale hydrogen storage and transport. An understanding of the release of cryogenic hydrogen from pressurized vessels is needed to evaluate the risk and safety concerns with the use of this fuel. The present work extends the analysis of previous experimental studies that measured the gas concentrations of cryo-compressed hydrogen jets and methane jets using a laser Raman scattering diagnostic system. Since the Raman signals are very small, a denoising algorithm was applied to significantly reduce the noise to enable statistical analysis of the data. The transient features of the turbulent jets were characterized by their concentration intermittencies and probability density functions (PDFs). A two-part PDF was developed to predict the bimodal features of the jet concentration distributions. Then, the flammability factors of the cryogenic jets were calculated based on the intermittency and the PDF.

Experiments have shown that ducted fuel injection (DFI) effectively reduces soot emissions from direct-injection diesel engines. Although many computational studies have evaluated DFI's spray development and soot reduction mechanisms in constant volume chambers, only limited computational work on internal combustion engines exists. The DFI duct assembly changes the engine's in-cylinder flow, spray, and combustion development. Therefore, current production engine designs might not be optimal for achieving the best engine performance with DFI. This work conducted an extensive numerical study to evaluate how parameter changes affect DFI performance. The parameters include swirl ratio, piston geometry, compression ratio (CR), number of injector orifices, split injection strategy, and exhaust gas recirculation (EGR) in a heavy-duty diesel engine utilizing DFI. The combustion and soot emission data from the Sandia compression ignition optical research engine were used for model validation. Simulations showed that an increased swirl ratio resulted in more intense jet flame-piston interaction, slowing down the combustion heat release during the late combustion stage and leading to lower indicated thermal efficiency (ITE) due to higher exhaust losses. A piston-bowl design with a reentrant inner piston edge yielded the highest thermal efficiency, due to the reduced cylinder head heat transfer loss. Additional injector orifices led to higher efficiency owing to a more advanced combustion phasing. Nevertheless, the maximum pressure rise rate (MPRR) and oxides of nitrogen (NOx) emissions also increased with the number of injector orifices due to more rapid heat release and higher combustion temperature. Implementation of a split injection strategy combined with a higher EGR rate effectively inhibited the excessive MPRR and NOx formation. In general, the study concluded that DFI is not sensitive to most parameter changes but will benefit from future parameter optimization.

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is an important diagnostic technique for seedless velocimetry measurements particularly in supersonic and hypersonic flows. Typical FLEET measurements feature a single laser line and camera system to achieve one-component velocimetry along a line, although some multiple-spot and multiple-component configurations have been demonstrated. In this work, tomographic imaging is used to track the three-dimensional location of many FLEET spots. A quadscope is used to combine four unique views onto a single high-speed image intensifier and camera. Tomographic reconstructions of the FLEET emission are analyzed for three-component velocimetry from multiple FLEET spots. Glass wedges are used to create many (nine) closely spaced FLEET spots with less than 10% transmission losses. These developments lead to a significant improvement in the dimensionality and spatial coverage of a FLEET instrument with some increases in experimental complexity and data processing. Multiple-point three-component FLEET velocimetry is demonstrated in an underexpanded jet.

Pyrimidine has two in-plane CH(δ+)/N̈(δ−)/CH(δ+) binding sites that are complementary to the (δ−/2δ+/δ−) quadrupole moment of CO2. We recorded broadband microwave spectra over the 7.5-17.5 GHz range for pyrimidine-(CO2)n with n = 1 and 2 formed in a supersonic expansion. Based on fits of the rotational transitions, including nuclear hyperfine splitting due to the two 14N nuclei, we have assigned 313 hyperfine components across 105 rotational transitions for the n = 1 complex and 208 hyperfine components across 105 rotational transitions for the n = 2 complex. The pyrimidine-CO2 complex is planar, with CO2 occupying one of the quadrupolar binding sites, forming a structure in which the CO2 is stabilized in the plane by interactions with the C-H hydrogens adjacent to the nitrogen atom. This structure is closely analogous to that of the pyridine-CO2 complex studied previously by ( Doran, J. L. J. Mol. Struct. 2012, 1019, 191-195 ). The fit to the n = 2 cluster gives rotational constants consistent with a planar cluster of C2v symmetry in which the second CO2 molecule binds in the second quadrupolar binding pocket on the opposite side of the ring. The calculated total binding energy in pyrimidine-CO2 is −13.7 kJ mol-1, including corrections for basis set superposition error and zero-point energy, at the CCSD(T)/ 6-311++G(3df,2p) level, while that in pyrimidine-(CO2)2 is almost exactly double that size, indicating little interaction between the two CO2 molecules in the two binding sites. The enthalpy, entropy, and free energy of binding are also calculated at 300 K within the harmonic oscillator/rigid-rotor model. This model is shown to lack quantitative accuracy when it is applied to the formation of weakly bound complexes.

Thermal spray deposition is an inherently stochastic manufacturing process used for generating thick coatings of metals, ceramics and composites. The generated coatings exhibit hierarchically complex internal structures that affect the overall properties of the coating. The deposition process can be adequately simulated using rules-based process simulations. Nevertheless, in order for the simulation to accurately model particle spreading upon deposition, a set of predefined rules and parameters need to be calibrated to the specific material and processing conditions of interest. The calibration process is not trivial given the fact that many parameters do not correspond directly to experimentally measurable quantities. This work presents a protocol that automatically calibrates the parameters and rules of a given simulation in order to generate the synthetic microstructures with the closest statistics to an experimentally generated coating. Specifically, this work developed a protocol for tantalum coatings prepared using air plasma spray. The protocol starts by quantifying the internal structure using 2-point statistics and then representing it in a low-dimensional space using Principal Component Analysis. Subsequently, our protocol leverages Bayesian optimization to determine the parameters that yield the minimum distance between synthetic microstructure and the experimental coating in the low-dimensional space.

In many applications, physical domains are geometrically complex making it challenging to perform coarse-scale approximation. A defeaturing process is often used to simplify the domain in preparation for approximation and analysis at the coarse scale. Herein, a methodology is presented for constructing a coarse-scale reproducing basis on geometrically complex domains given an initial fine-scale mesh of the fully featured domain. The initial fine-scale mesh can be of poor quality and extremely refined. The construction of the basis functions begins with a coarse-scale covering of the domain and generation of weighting functions with local support. Manifold geodesics are used to define distances within the local support for general applicability to non-convex domains. Conventional moving least squares is used to construct the coarse-scale reproducing basis. Applications in quasi-interpolation and linear elasticity are presented.

Gas molecule clustering within nanopores holds significance in the fields of nanofluidics, biology, gas adsorption/desorption, and geological gas storage. However, the intricate roles of nanoconfinement and surface chemistry that govern the formation of gas clusters remain inadequately explored. In this study, through free energy calculation in molecular simulations, we systematically compared the tendencies of H2 and CO2 molecules to aggregate within hydrated hydrophobic pyrophyllite and hydrophilic gibbsite nanopores. The results indicate that nanoconfinement enhances gas dimer formation in the nanopores, irrespective of surface chemistry. However, surface hydrophilicity prohibits the formation of gas clusters larger than dimers, while large gas clusters form easily in hydrophobic nanopores. Despite H2 and CO2 both being non-polar, the larger quadrupole moment of CO2 leads to a stronger preference for dimer/cluster formation compared to H2. Our results also indicate that gases prefer to enter the nanopores as individual molecules, but exit the nanopores as dimers/clusters. This investigation provides a mechanistic understanding of gas cluster formation within nanopores, which is relevant to various applications, including geological gas storage.

We present a high-level architecture for how artificial intelligences might advance and accumulate scientific and technological knowledge, inspired by emerging perspectives on how human intelligences advance and accumulate such knowledge. Agents advance knowledge by exercising a technoscientific method—an interacting combination of scientific and engineering methods. The technoscientific method maximizes a quantity we call “useful learning” via more-creative implausible utility (including the “aha!” moments of discovery), as well as via less-creative plausible utility. Society accumulates the knowledge advanced by agents so that other agents can incorporate and build on to make further advances. The proposed architecture is challenging but potentially complete: its execution might in principle enable artificial intelligences to advance and accumulate an equivalent of the full range of human scientific and technological knowledge.

In lithium-metal batteries, grains of lithium can become electrically isolated from the anode, lowering battery performance. We state that experiments reveal that rest periods after battery discharge might help to solve this problem.

Replacement of conventional petroleum fuels with renewable fuels reduces net emissions of carbon and greenhouse gases, and affords opportunities for increased domestic energy security. Here, we present alkyl dialkoxyalkanoates (or DAOAs) as a family of synthetic diesel and marine fuel candidates that feature ester and ether functionality. These compounds employ pyruvic acid and fusel alcohols as precursors, which are widely available as metabolic intermediates at high titer and yield. DAOA synthesis proceeds in high yield using a simple, mild chemical transformation performed under air that employs bioderived and/or easily recovered reagents and solvent. The scalability of the synthetic protocol was proven in continuous flow with in situ azeotropic water removal, yielding 375 g of isolated product. Chemical stability of DAOAs against aqueous 0.01 M H2SO4 and accelerated oxidative conditions is demonstrated. The isolated DAOAs were shown to meet or exceed widely accepted technical criteria for sustainable diesel fuels. In particular, butyl 2,2-dibutoxypropanoate (DAOA-2) has indicated cetane number 64, yield soot index 256 YSI per kg, lower heating value 30.9 MJ kg−1 and cloud point < −60 °C and compares favorably to corresponding values for renewable diesel, biodiesel and petroleum diesel.

Testing of a compact Bremsstrahlung diode was performed at the High Energy Radiation Megavolt Electron Source III (HERMES-III) was performed at Sandia National Laboratories in November, 2023. The compact diode described here is the first prototype diode in a campaign to optimize a Bremsstrahlung diode in terms of size and dose production. The goal was to test the diode at about 13MV, and the experiment realized between 10-12MV at the diode. Modeling and simulation of this geometry was performed

A dry etching process to transfer the pattern of a photonic integrated circuit design for high-speed laser communications is described. The laser stack under consideration is a 3.2-µm-thick InGaAs/InAlAs/InAlGaAs epitaxial structure grown by molecular beam epitaxy. The etching was performed using Cl2-based inductively-coupled-plasma and reactive-ion-etching (ICP-RIE) reactors. Four different recipes are presented in two similar ICP-RIE reactors, with special attention paid to the etched features formed with various hard mask compositions, in-situ passivations, and process temperatures. The results indicate that it is possible to produce high-aspect-ratio features with sub-micron separation on this multilayer structure. Additionally, the results of the etching highlight the tradeoffs involved with the corresponding recipes.

The On-Line Waste Library is a website that contains information regarding United States Department of Energy-managed high-level waste, spent nuclear fuel, and other wastes that are likely candidates for deep geologic disposal, with links to supporting documents for the data. This report provides supporting information for the data for which an already published source was not available.

Recent findings suggest that ions are strongly correlated in atmospheric pressure plasmas if the ionization fraction is sufficiently high ( ≳ 10 − 5 ). A consequence is that ionization causes disorder-induced heating (DIH), which triggers a significant rise in ion temperature on a picosecond timescale. This is followed by a rise in the neutral gas temperature on a longer timescale of up to nanoseconds due to ion-neutral temperature relaxation. The sequence of DIH and ion-neutral temperature relaxation suggests a new mechanism for ultrafast neutral gas heating. Previous work considered only the case of an instantaneous ionization pulse, whereas the ionization pulse extends over nanoseconds in many experiments. Here, molecular dynamics simulations are used to analyze the evolution of ion and neutral gas temperatures for a gradual ionization over several nanoseconds. The results are compared with published experimental results from a nanosecond pulsed discharge, showing good agreement with a measurement of fast neutral gas heating.

NasGen provides a path for migration of structural models from NASTRAN bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Presto).

Coulomb drag experiments have been an essential tool to study strongly interacting low-dimensional systems. Historically, this effect has been explained in terms of momentum transfer between electrons in the active and the passive layer. We report Coulomb drag measurements between laterally coupled GaAs/AlGaAs quantum wires in the multiple one-dimensional (1D) sub-band regime that break Onsager's reciprocity upon both layer and current direction reversal, in contrast to prior 1D Coulomb drag results. The drag signal shows nonlinear current-voltage (I-V) characteristics, which are well characterized by a third-order polynomial fit. These findings are qualitatively consistent with a rectified drag signal induced by charge fluctuations. However, the nonmonotonic temperature dependence of this drag signal suggests that strong electron-electron interactions, expected within the Tomonaga-Luttinger liquid framework, remain important and standard interaction models are insufficient to capture the qualitative nature of rectified 1D Coulomb drag.

A reduction in wake effects in large wind farms through wake-aware control has considerable potential to improve farm efficiency. This work examines the success of several emerging, empirically derived control methods that modify wind turbine wakes (i.e., the pulse method, helix method, and related methods) based on Strouhal numbers on the (Formula presented.). Drawing on previous work in the literature for jet and bluff-body flows, the analyses leverage the normal-mode representation of wake instabilities to characterize the large-scale wake meandering observed in actuated wakes. Idealized large-eddy simulations (LES) using an actuator-line representation of the turbine blades indicate that the (Formula presented.) and (Formula presented.) modes, which correspond to the pulse and helix forcing strategies, respectively, have faster initial growth rates than higher-order modes, suggesting these lower-order modes are more appropriate for wake control. Exciting these lower-order modes with periodic pitching of the blades produces increased modal growth, higher entrainment into the wake, and faster wake recovery. Modal energy gain and the entrainment rate both increase with streamwise distance from the rotor until the intermediate wake. This suggests that the wake meandering dynamics, which share close ties with the relatively well-characterized meandering dynamics in jet and bluff-body flows, are an essential component of the success of wind turbine wake control methods. A spatial linear stability analysis is also performed on the wake flows and yields insights on the modal evolution. In the context of the normal-mode representation of wake instabilities, these findings represent the first literature examining the characteristics of the wake meandering stemming from intentional Strouhal-timed wake actuation, and they help guide the ongoing work to understand the fluid-dynamic origins of the success of the pulse, helix, and related methods.

Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in solution due to the need to include large numbers of solvent molecules. We present a machine-learned electron density model based on a Euclidean neural network framework that includes a built-in understanding of equivariance to model explicitly solvated double-stranded DNA. By training the machine learning model using molecular fragments that sample the key DNA and solvent interactions, we show that the model predicts electron densities of arbitrary systems of solvated DNA accurately, resolves polarization effects that are neglected by classical force fields, and captures the physics of the DNA-solvent interaction at the ab initio level.

The Integrated Tiger Series (ITS) generates a database containing energy deposition data. This data, when stored on an Exodus file, is not typically suitable for analysis within Sierra Mechanics for finite element analysis. The its2sierra tool maps data from the ITS database to the Sierra database.

The role to which a realistic inflow turbulent boundary layer (TBL) influences transient and mean large-scale pool fire quantities of interest (QoIs) is numerically investigated. High-fidelity, low-Mach large-eddy simulations that activate low-dissipation, unstructured numerics are conducted using an unsteady flamelet combustion modeling approach with mutiphysics coupling to soot and participating media radiation transport. Three inlet profile configurations are exercised for a large-scale, high-aspect rectangular pool that is oriented perpendicular to the flow direction: a time-varying, TBL inflow profile obtained from a periodic precursor simulation, the time-mean of the transient TBL, and a steady power-law inflow profile that replicates the mean TBL crosswind velocity of 10.0 m/s at a vertical height of 10 m. Results include both qualitative transient flame evolution and quantitative flame shape with ground-level temperature and convective/radiative heat flux profiles. While transient fire events, which are driven by burst-sweep TBL coupling, such as blow-off and reattachment are vastly different in the TBL case (contributing to increased root mean square QoI fluctuation prediction and disparate flame lengths), mean surface QoI magnitudes are similar. Quadrant analysis demonstrates that the TBL configuration modifies burst-sweep phenomena at windward pool locations, while leeward recovery is found. Positive fluctuations of convective heat flux correlate with fast moving fluid away from the pool surface due to intermittent combustion events.

As ferroelectric hafnium zirconium oxide (HZO) becomes more widely utilized in ferroelectric microelectronics, integration impacts of intentional and nonintentional dielectric interfaces and their effects upon the ferroelectric film wake-up (WU) and circuit parameters become important to understand. In this work, the effect of the addition of a linear dielectric aluminum oxide, Al2O3, below a ferroelectric Hf0.58Zr0.42O2 film in a capacitor structure for FeRAM applications with niobium nitride (NbN) electrodes was measured. Depolarization fields resulting from the linear dielectric is observed to induce a reduction of the remanent polarization of the ferroelectric. Addition of the aluminum oxide also impacts the WU of the HZO with respect to the cycling voltage applied. Intricately linked to the design of a FeRAM 1C/1T cell, the metal-ferroelectric-insulator-metal (MFIM) devices are observed to significantly shift charge related to the read states based on aluminum oxide thickness and WU cycling voltage. A 33% reduction in the separation of read states are measured, which complicates how a memory cell is designed and illustrates the importance of clean interfaces in devices.

Chromium self-diffusion through stainless steel (SS) matrix and along grain boundaries is an important mechanism controlling SS structural materials corrosion. Cr diffusion in austenitic SS was simulated using canonical ab initio molecular dynamics with realistic models of type-316 SS bulk, with and without Cr vacancies, and a low-energy Σ3 twin boundary typically observed at active corrosion sites. Cr self-diffusion coefficients at 750 and 850 °C calculated using Einstein's diffusion equation are 4.2 × 10−6 and 8.1 × 10−6 Å2 ps−1 in pristine bulk, 3.8 × 10−3 and 5.5 × 10−3 Å2 ps−1 in bulk including Cr vacancies, and 9.5 × 10−2 and 1.0 × 10−1 Å2 ps−1 at a Σ3[1 1 1]60° twin boundary.

Detecting changepoints in functional data has become an important problem as interest in monitoring of climate phenomenon has increased, where the data is functional in nature. The observed data often contains both amplitude ((Formula presented.) -axis) and phase ((Formula presented.) -axis) variability. If not accounted for properly, true changepoints may be undetected, and the estimated underlying mean change functions will be incorrect. In this article, an elastic functional changepoint method is developed which properly accounts for these types of variability. The method can detect amplitude and phase changepoints which current methods in the literature do not, as they focus solely on the amplitude changepoint. This method can easily be implemented using the functions directly or can be computed via functional principal component analysis to ease the computational burden. We apply the method and its nonelastic competitors to both simulated data and observed data to show its efficiency in handling data with phase variation with both amplitude and phase changepoints. We use the method to evaluate potential changes in stratospheric temperature due to the eruption of Mt. Pinatubo in the Philippines in June 1991. Using an epidemic changepoint model, we find evidence of a increase in stratospheric temperature during a period that contains the immediate aftermath of Mt. Pinatubo, with most detected changepoints occurring in the tropics as expected.

Living document updating the 5.16 version, SAND2023-09919 of September 2023.

Ducted fuel injection (DFI) is a strategy to improve fuel/charge-gas mixing in direct-injection compression-ignition engines. DFI involves injecting fuel along the axis of a small tube in the combustion chamber, which promotes the formation of locally leaner mixtures in the autoignition zone relative to conventional diesel combustion. Previous work has demonstrated that DFI is effective at curtailing engine-out soot emissions across a wide range of operating conditions. This study extends previous investigations, presenting engine-out emissions and efficiency trends between ducted two-orifice and ducted four-orifice injector tip configurations. For each configuration, parameters investigated include injection pressure, injection duration, intake manifold pressure, intake manifold temperature, start of combustion timing, and intake-oxygen mole fraction. For both configurations and across all parameters, DFI reduced engine-out soot emissions compared to conventional diesel combustion, with little effect on other emissions and engine efficiency. Emissions trends for both configurations were qualitatively the same across the parameters investigated. The four-duct configuration had higher thermal efficiency and indicated-specific engine-out nitrogen oxide emissions but lower indicated-specific engine-out hydrocarbon and carbon monoxide emissions than the two-duct assembly. Both configurations achieved indicated-specific engine-out emissions for both soot and nitrogen oxides that comply with current on- and off-road heavy-duty regulations in the United States without exhaust-gas aftertreatment at an intake-oxygen mole fraction of 12%. High-speed in-cylinder imaging of natural soot luminosity shows that some conditions include a second soot-production phase late in the cycle. The probability of these late-cycle events is sensitive to both the number of ducted sprays and the operating conditions.

Chem

Presented in this document is a portion of the tests that exist in the Sierra Thermal/Fluids verificationtest suite. Each of these tests is run nightly with the Sierra/TF code suite and the results of the testchecked under mesh refinement against the correct analytic result. For each of the tests presented in thisdocument the test setup, derivation of the analytic solution, and comparison of the code results to theanalytic solution is provided.

Perovskite solar cells (PSCs) are emerging photovoltaic (PV) technologies capable of matching power conversion efficiencies (PCEs) of current PV technologies in the market at lower manufacturing costs, making perovskite solar modules (PSMs) cost competitive if manufactured at scale and perform with minimal degradation. PSCs with the highest PCEs, to date, are lead halide perovskites. Lead presents potential environmental and human health risks if PSMs are to be commercialized, as the lead in PSMs are more soluble in water compared to other PV technologies. Therefore, prior to commercialization of PSMs, it is important to highlight, identify, and establish the potential environmental and human health risks of PSMs as well as develop methods for assessing the potential risks. Here, we identify and discuss a variety of international standards, U.S. regulations, and permits applicable to PSM deployment that relate to the potential environmental and human health risks associated with PSMs. The potential risks for lead and other hazardous material exposures to humans and the environment are outlined which include water quality, air quality, human health, wildlife, land use, and soil contamination, followed by examples of how developers of other PV technologies have navigated human health and environmental risks previously. Potential experimentation, methodology, and research efforts are proposed to elucidate and characterize potential lead leaching risks and concerns pertaining to fires, in-field module damage, and sampling and leach testing of PSMs at end of life. Lastly, lower technology readiness level solutions to mitigate lead leaching, currently being explored for PSMs, are discussed. PSMs have the potential to become a cost competitive PV technology for the solar industry and taking steps toward understanding, identifying, and creating solutions to mitigate potential environmental and human health risks will aid in improving their commercial viability.

Tests from the Sierra Structural Dynamics verification test suite are reviewed. Each is run nightly and the results of the test checked versus the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

This report describes qualitative economic effects of storing, transporting, and disposing of spent high assay low-enriched uranium nuclear fuel.

Quantifying the radioactive sources present in gamma spectra is an ever-present and growing national security mission and a time-consuming process for human analysts. While machine learning models exist that are trained to estimate radioisotope proportions in gamma spectra, few address the eventual need to provide explanatory outputs beyond the estimation task. In this work, we develop two machine learning models for a NaI detector measurements: one to perform the estimation task, and the other to characterize the first model’s ability to provide reasonable estimates. To ensure the first model exhibits a behavior that can be characterized by the second model, the first model is trained using a custom, semi-supervised loss function which constrains proportion estimates to be explainable in terms of a spectral reconstruction. The second auxiliary model is an out-of-distribution detection function (a type of meta-model) leveraging the proportion estimates of the first model to identify when a spectrum is sufficiently unique from the training domain and thus is out-of-scope for the model. In demonstrating the efficacy of this approach, we encourage the use of meta-models to better explain ML outputs used in radiation detection and increase trust.

As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.

Cast Monel alloys are used in many industrial applications that require a combination of good mechanical properties and excellent resistance to corrosion. Despite relative widespread use, there has been limited prior research investigating the fundamental composition–structure–property relationships. In this work, microstructural characterization, thermal analysis, electron probe microanalysis, tensile testing, and Varestraint testing were used to assess the effects of variations in nominal composition on the solidification path, microstructure, mechanical properties, and solidification cracking susceptibility of cast Monel alloys. It was found that Si segregation caused the formation of silicides at the end of solidification in grades containing at least 3 wt pct Si. While increases to Si content led to significant improvements in strengthening due to the precipitation of β1-Ni3Si, the silicide eutectics acted as crack nucleation sites during tensile loading which severely reduced ductility. The solidification cracking susceptibility of low-Si Monel alloys was found to be relatively low. However, increases to Si concentration and the onset of associated eutectic reactions increased the solidification temperature range and drastically reduced cracking resistance. Increases in the Cu and Mn concentrations were found to reduce the solubility limit of Si in austenite which promoted additional eutectic formation and exacerbated the reductions in ductility and/or weldability.

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of theASC fire environment simulation project. The fire environment simulation project is directed atcharacterizing both open large-scale pool fires and building enclosure fires. Fuego represents theturbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, andabsorption coefficient model portion of the simulation software.

The Example Problems Manual supplements the User's Manual and the Theory Manual. The goal of the Example Problems Manual is to reduce learning time for complex end to end analyses. These documents are intended to be used together. See the User's Manual for a complete list of the options for a solution case. All the examples are part of the \salinas test suite. Each runs as is.

The rate of electric vehicle (EV) adoption, powered by the Li-ion battery, has grown exponentially; largely driven by technological advancements, consumer demand, and global initiatives to reduce carbon emissions. As a result, it is imperative to understand the state of stability (SoS) of the cells inside an EV battery pack. That understanding will enable the warning of or prevention against catastrophic failures that can lead to serious injury or even, loss of life. The present work explores rapid electrochemical impedance spectroscopy (EIS) coupled with gas sensing technology as diagnostics to monitor cells and packs for failure markers. These failure markers can then be used for onboard assessment of SoS. Experimental results explore key changes in single cells and packs undergoing thermal or electrical abuse. Rapid EIS showed longer warning times, followed by VOC sensors, and then H2 sensors. While rapid EIS gives the longest warning time, with the failure marker often appearing before the cell vents, the reliability of identifying impedance changes in single cells within a pack decreases as the pack complexity increases. This provides empirical evidence to support the significant role that cell packaging and battery engineering intricacies play in monitoring the SoS.

Developing atomically synergistic bifunctional catalysts relies on the creation of colocalized active atoms to facilitate distinct elementary steps in catalytic cycles. Herein, we show that the atomically-synergistic binuclear-site catalyst (ABC) consisting of Zn^δ+ -O-Cr⁶⁺ on zeolite SSZ-13 displays unique catalytic properties for iso-stoichiometric co-conversion of ethane and CO₂. Ethylene selectivity and utilization of converted CO₂ can reach 100 % and 99.0% under 500 °C at ethane conversion of 9.6%, respectively. In-situ/ex-situ spectroscopic studies and DFT calculations reveal atomic synergies between acidic Zn and redox Cr sites. Zn^δ+ (0 < δ < 2) sites facilitate β-C-H bond cleavage in ethane and the formation of Zn-H^δ- hydride, thereby the enhanced basicity promotes CO₂ adsorption/activation and prevents ethane C-C bond scission. The redox Cr site accelerates CO₂ dissociation by replenishing lattice oxygen and facilitates H₂O formation/desorption. This study presents the advantages of the ABC concept, paving the way for the rational design of novel advanced catalysts.

Granular matter takes many paths to pack in natural and industrial processes. The path influences the packing microstructure, particularly for frictional grains. We perform discrete element modeling simulations of different paths to construct packings of frictional spheres. Specifically, we explore four stress-controlled protocols implementing packing expansions and compressions in various combinations thereof. We characterize the eventual packed states through their dependence of the packing fraction and coordination number on packing pressure, identifying non-monotonicities with pressure that correlate with the fraction of frictional contacts. These stress-controlled, bulk-like particle simulations access very low-pressure packings, namely, the marginally stable limit, and demonstrate the strong protocol dependence of frictional granular matter.

The high-pressure compaction of three dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by bonds. A simple multibody interaction is introduced to control Poisson's ratio and the arrangement of particles on the surface of a grain is varied to model both high- and low-frictional grains. At low pressures, the growth in packing fraction and coordination number follow the expected behavior near jamming and exhibit friction dependence. As the pressure increases, deviations from the low-pressure power-law scaling emerge after the packing fraction grows by approximately 0.1 and results from simulations with different friction coefficients converge. These results are compared to predictions from traditional discrete element method simulations which, depending on the definition of packing fraction and coordination number, may only differ by a factor of two. As grains deform under compaction, the average volumetric strain and asphericity, a measure of the change in the shape of grains, are found to grow as power laws and depend heavily on the Poisson's ratio of the constituent solid. Larger Poisson's ratios are associated with less volumetric strain and more asphericity and the apparent power-law exponent of the asphericity may vary. The elastic properties of the packed grains are also calculated as a function of packing fraction. In particular, we find the Poisson's ratio near jamming is 1/2 but decreases to around 1/4 before rising again as systems densify.

3D integration of multiple microelectronic devices improves size, weight, and power while increasing the number of interconnections between components. One integration method involves the use of metal bump bonds to connect devices and components on a common interposer platform. Significant variations in the coefficient of thermal expansion in such systems lead to stresses that can cause thermomechanical and electrical failures. More advanced characterization and failure analysis techniques are necessary to assess the bond quality between components. Frequency domain thermoreflectance (FDTR) is a nondestructive, noncontact testing method used to determine thermal properties in a sample by fitting the phase lag between an applied heat flux and the surface temperature response. The typical use of FDTR data involves fitting for thermal properties in geometries with a high degree of symmetry. In this work, finite element method simulations are performed using high performance computing codes to facilitate the modeling of samples with arbitrary geometric complexity. A gradient-based optimization technique is also presented to determine unknown thermal properties in a discretized domain. Using experimental FDTR data from a GaN-diamond sample, thermal conductivity is then determined in an unknown layer to provide a spatial map of bond quality at various points in the sample.

The epitaxial development and characterization of metamorphic “GaSb-on-silicon” buffers as substrates for antimonide devices is presented. The approach involves the growth of a spontaneously and fully relaxed GaSb metamorphic buffer in a primary epitaxial reactor, and use of the resulting “GaSb-on-silicon” wafer to grow subsequent layers in a secondary epitaxial reactor. The buffer growth involves four steps—silicon substrate preparation for oxide removal, nucleation of AlSb on silicon, growth of the GaSb buffer, and finally capping of the buffer to prevent oxidation. This approach on miscut silicon substrates leads to a buffer with negligible antiphase domain density. The growth of this buffer is based on inducing interfacial misfit dislocations between an AlSb nucleation layer and the underlying silicon substrate, which results in a fully relaxed GaSb buffer. A 1 μm thick GaSb layer buffer grown on silicon has ~9.2 × 10⁷ dislocations/cm². The complete lack of strain in the epitaxial structure allows subsequent growths to be accurately lattice matched, thus making the approach ideal for use as a substrate. Here we characterize the GaSb-on-silicon wafer using high-resolution x-ray diffraction and transmission electron microscopy. The concept’s feasibility is demonstrated by growing interband cascade light emitting devices on the GaSb-on-silicon wafer. The performance of the resulting LEDs on silicon approaches that of counterparts grown lattice matched on GaSb.

Here, we show that a laser at threshold can be utilized to generate the class of coherent and transform-limited waveforms (vt — z)^me^i(kz—ωt) at optical frequencies. We derive these properties analytically and demonstrate them in semiclassical time-domain laser simulations. We then utilize these waveforms to expand other waveforms with high modulation frequencies and demonstrate theoretically the feasibility of complex-frequency coherent absorption at optical frequencies, with efficient energy transduction and cavity loading. This approach has potential applications in quantum computing, photonic circuits, and biomedicine.

Alkali metals are among the most desirable negative electrodes for long duration energy storage due to their extremely high capacities. Currently, only high-temperature (>250 °C) batteries have successfully used alkali electrodes in commercial applications, due to limitations imposed by solid electrolytes, such as low conductivity at moderate temperatures and susceptibility to dendrites. Toward enabling the next generation of grid-scale, long duration batteries, we aim to develop molten sodium (Na) systems that operate with commercially attractive performance metrics including high current density (>100 mA cm-2), low temperature (<200 °C), and long discharge times (>12 h). In this work, we focus on the performance of NaSICON solid electrolytes in sodium symmetric cells at 110 °C. Specifically, we use a tin (Sn) coating on NaSICON to reduce interfacial resistance by a factor of 10, enabling molten Na symmetric cell operation with “discharge” durations up to 23 h at 100 mA cm-2 and 110 °C. Unidirectional galvanostatic testing shows a 70% overpotential reduction, and electrochemical impedance spectroscopy (EIS) highlights the reduction in interfacial resistance due to the Sn coating. Detailed scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) show that Sn-coated NaSICON enables current densities of up to 500 mA cm-2 at 110 °C by suppressing dendrite formation at the plating interface (Mode I). This analysis also provides a mechanistic understanding of dendrite formation at current densities up to 1000 mA cm-2, highlighting the importance of effective coatings that will enable advanced battery technologies for long-term energy storage.

Because of the high-risk nature of emergencies and illegal activities at sea, it is critical that algorithms designed to detect anomalies from maritime traffic data be robust. However, there exist no publicly available maritime traffic data sets with real-world expert-labeled anomalies. As a result, most anomaly detection algorithms for maritime traffic are validated without ground truth. We introduce the HawaiiCoast_GT data set, the first ever publicly available automatic identification system (AIS) data set with a large corresponding set of true anomalous incidents. This data set—cleaned and curated from raw Bureau of Ocean Energy Management (BOEM) and National Oceanic and Atmospheric Administration (NOAA) automatic identification system (AIS) data—covers Hawaii’s coastal waters for four years (2017–2020) and contains 88,749,176 AIS points for a total of 2622 unique vessels. This includes 208 labeled tracks corresponding to 154 rigorously documented real-world incidents.

We demonstrate an order of magnitude reduction in the sensitivity to optical crosstalk for neighboring trapped-ion qubits during simultaneous single-qubit gates driven with individual addressing beams. Gates are implemented via two-photon Raman transitions, where crosstalk is mitigated by offsetting the drive frequencies for each qubit to avoid first-order crosstalk effects from inter-beam two-photon resonance. The technique is simple to implement, and we find that phase-dependent crosstalk due to optical interference is reduced on the most impacted neighbor from a maximal fractional rotation error of 0.185 ( 4 ) without crosstalk mitigation to ≤ 0.006 with the mitigation strategy. Furthermore, we characterize first-order crosstalk in the two-qubit gate and avoid the resulting rotation errors for the arbitrary-axis Mølmer-Sørensen gate via a phase-agnostic composite gate. Finally, we demonstrate holistic system performance by constructing a composite CNOT gate using the improved single-qubit gates and phase-agnostic two-qubit gate. This work is done on the Quantum Scientific Computing Open User Testbed; however, our methods are widely applicable for individual addressing Raman gates and impose no significant overhead, enabling immediate improvement for quantum processors that incorporate this technique.

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

Efficient solution of the Vlasov equation, which can be up to six-dimensional, is key to the simulation of many difficult problems in plasma physics. The discontinuous Petrov-Galerkin (DPG) finite element methodology provides a framework for the development of stable (in the sense of Ladyzhenskaya–Babuška–Brezzi conditions) finite element formulations, with built-in mechanisms for adaptivity. While DPG has been studied extensively in the context of steady-state problems and to a lesser extent with space-time discretizations of transient problems, relatively little attention has been paid to time-marching approaches. In the present work, we study a first application of time-marching DPG to the Vlasov equation, using backward Euler for a Vlasov-Poisson discretization. We demonstrate adaptive mesh refinement for two problems: the two-stream instability problem, and a cold diode problem. We believe the present work is novel both in its application of unstructured adaptive mesh refinement (as opposed to block-structured adaptivity, which has been studied previously) in the context of Vlasov-Poisson, as well as in its application of DPG to the Vlasov-Poisson system. We also discuss extensive additions to the Camellia library in support of both the present formulation as well as extensions to higher dimensions, Maxwell equations, and space-time formulations.

Thermochemical air separation to produce high-purity N2 was demonstrated in a vertical tube reactor via a two-step reduction–oxidation cycle with an A-site substituted perovskite Ba0.15Sr0.85FeO3–δ (BSF1585). BSF1585 particles were synthesized and characterized in terms of their chemical, morphological, and thermophysical properties. A thermodynamic cycle model and sensitivity analysis using computational heat and mass transfer models of the reactor were used to select the system operating parameters for a concentrating solar thermal-driven process. Thermal reduction up to 800 °C in air and temperature-swing air separation from 800 °C to minimum temperatures between 400 and 600 °C were performed in the reactor containing a 35 g packed bed of BSF1585. The reactor was characterized for dispersion, and air separation was characterized via mass spectrometry. Gas measurements indicated that the reactor produced N2 with O2 impurity concentrations as low as 0.02 % for > 30 min of operation. A parametric study of air flow rates suggested that differences in observed and thermodynamically predicted O2 impurities were due to imperfect gas transport in the bed. Temperature swing reduction/oxidation cycling experiments between 800 and 400 °C in air were conducted with no statistically significant degradation in N2 purity over 50 cycles.

We investigate the interplay between the quantum Hall (QH) effect and superconductivity in InAs surface quantum well (SQW)/NbTiN heterostructures using a quantum point contact (QPC). We use QPC to control the proximity of the edge states to the superconductor. By measuring the upstream and downstream resistances of the device, we investigate the efficiency of Andreev conversion at the InAs/NbTiN interface. Our experimental data is analyzed using the Landauer-Büttiker formalism, generalized to allow for Andreev reflection processes. We show that by varying the voltage of the QPC, VQPC, the average Andreev reflection, A, at the QH-SC interface can be tuned from 50% to ∼10%. The evolution of A with VQPC extracted from the measurements exhibits plateaus separated by regions for which A varies continuously with VQPC. The presence of plateaus suggests that for some ranges of VQPC the QPC might be pinching off almost completely from the QH-SC interface some of the edge modes. Our work shows an experimental setup to control and advance the understanding of the complex interplay between superconductivity and QH effect in two-dimensional gas systems.

The size of a pressure transducer is known to affect the accuracy of measurements of wall-pressure fluctuations beneath a turbulent boundary layer because of spatial averaging over the sensing area of the transducer. In this paper, the effect of finite transducer size is investigated by applying spatial averaging or wavenumber filters to a database of hypersonic wall pressure generated from a direct numerical simulation (DNS) that simulates the turbulent portion of the boundary layer over a sharp 7° half-angle cone at nominally Mach 8. Here, a good comparison between the DNS and the experiment in the Sandia Hypersonic Wind Tunnel at Mach 8 is achieved after spatial averaging is applied to the DNS data over an area similar to the sensing area of the transducer. The study shows that a finite sensor size similar to that of the PCB132 transducer can cause significant attenuation in the root-mean-square and power spectral density (PSD) of wall-pressure fluctuations, and the attenuation effect is identical between cone and flat plate configurations at the same friction Reynolds number. The Corcos theory is found to successfully compensate for the attenuated high-frequency components of the wall-pressure PSD.

Color centers in diamond are one of the most promising tools for quantum information science. Of particular interest is the use of single-crystal diamond membranes with nanoscale-thickness as hosts for color centers. Indeed, such structures guarantee a better integration with a variety of other quantum materials or devices, which can aid the development of diamond-based quantum technologies, from nanophotonics to quantum sensing. A common approach for membrane production is what is known as “smart-cut”, a process where membranes are exfoliated from a diamond substrate after the creation of a thin sub-surface amorphous carbon layer by He⁺ implantation. Due to the high ion fluence required, this process can be time-consuming. In this work, we demonstrated the production of thin diamond membranes by neon implantation of diamond substrates. With the target of obtaining membranes of ~200 nm thickness and finding the critical damage threshold, we implanted different diamonds with 300 keV Ne⁺ ions at different fluences. We characterized the structural properties of the implanted diamonds and the resulting membranes through SEM, Raman spectroscopy, and photoluminescence spectroscopy. We also found that a SRIM model based on a two-layer diamond/sp² -carbon target better describes ion implantation, allowing us to estimate the diamond critical damage threshold for Ne⁺ implantation. Compared to He⁺ smart-cut, the use of a heavier ion like Ne⁺ results in a ten-fold decrease in the ion fluence required to obtain diamond membranes and allows to obtain shallower smart-cuts, i.e. thinner membranes, at the same ion energy.

We propose a method to extract the upper laser level’s (ULL’s) excess electronic temperature from the analysis of the maximum light output power (P_max) and current dynamic range ΔJ_d = (J_max – J_th) of terahertz quantum cascade lasers (THz QCLs). We validated this method, both through simulation and experiment, by applying it on THz QCLs supporting a clean three-level system. Detailed knowledge of electronic excess temperatures is of utmost importance in order to achieve high temperature performance of THz QCLs. Our method is simple and can be easily implemented, meaning an extraction of the excess electron temperature can be achieved without intensive experimental effort. This knowledge should pave the way toward improvement of the temperature performance of THz QCLs beyond the state-of-the-art.

We hereby offer a comprehensive analysis of various factors that could potentially enable terahertz quantum cascade lasers (THz QCLs) to achieve room temperature performance. We thoroughly examine and integrate the latest findings from recent studies in the field. Our work goes beyond a mere analysis; it represents a nuanced and comprehensive exploration of the intricate factors influencing the performance of THz QCLs. Through a comprehensive and holistic approach, we propose novel insights that significantly contribute to advancing strategies for improving the temperature performance of THz QCLs. This all-encompassing perspective allows us not only to present a synthesis of existing knowledge but also to offer a fresh and nuanced strategy to improve the temperature performance of THz QCLs. We draw new conclusions from prior works, demonstrating that the key to enhancing THz QCL temperature performance involves not only optimizing interface quality but also strategically managing doping density, its spatial distribution, and profile. This is based on our results from different structures, such as two experimentally demonstrated devices: the spit-well resonant-phonon and the two-well injector direct-phonon schemes for THz QCLs, which allow efficient isolation of the laser levels from excited and continuum states. In these schemes, the doping profile has a setback that lessens the overlap of the doped region with the active laser states. Our work stands as a valuable resource for researchers seeking to gain a deeper understanding of the evolving landscape of THz technology. Furthermore, we present a novel strategy for future endeavors, providing an enhanced framework for continued exploration in this dynamic field. This strategy should pave the way to potentially reach higher temperatures than the latest records reached for T_max of THz QCLs.

Intermediate verification languages like Why3 and Boogie have made it much easier to build program verifiers, transforming the process into a logic compilation problem rather than a proof automation one. Why3 in particular implements a rich logic for program specification with polymorphism, algebraic data types, recursive functions and predicates, and inductive predicates; it translates this logic to over a dozen solvers and proof assistants. Accordingly, it serves as a backend for many tools, including Frama-C, EasyCrypt, and GNATProve for Ada SPARK. But how can we be sure that these tools are correct? The alternate foundational approach, taken by tools like VST and CakeML, provides strong guarantees by implementing the entire toolchain in a proof assistant, but these tools are harder to build and cannot directly take advantage of SMT solver automation. As a first step toward enabling automated tools with similar foundational guarantees, we give a formal semantics in Coq for the logic fragment of Why3. We show that our semantics are useful by giving a correct-by-construction natural deduction proof system for this logic, using this proof system to verify parts of Why3's standard library, and proving sound two of Why3's transformations used to convert terms and formulas into the simpler logics supported by the backend solvers.

Understanding pure H2 and H2/CH4 adsorption and diffusion in earth materials is one vital step toward a successful and safe H2 storage in depleted gas reservoirs. Despite recent research efforts such understanding is far from complete. In this work we first use Nuclear Magnetic Resonance (NMR) experiments to study the NMR response of injected H2 into Duvernay shale and Berea sandstone samples, representing materials in confining and storage zones. Then we use molecular simulations to investigate H2/CH4 competitive adsorption and diffusion in kerogen, a common component of shale. Our results indicate that in shale there are two H2 populations, i.e., free H2 and adsorbed H2, that yield very distinct NMR responses. However, only free gas presents in sandstone that yields a H2 NMR response similar to that of bulk H2. About 10 % of injected H2 can be lost due to adsorption/desorption hysteresis in shale, and no H2 loss (no hysteresis) is observed in sandstone. Our molecular simulation results support our NMR results that there are two H2 populations in nanoporous materials (kerogen). The simulation results also indicate that CH4 outcompetes H2 in adsorption onto kerogen, due to stronger CH4-kerogen interactions than H2-kerogen interactions. Nevertheless, in a depleted gas reservoir with low CH4 gas pressure, about ∼30 % of residual CH4 can be desorbed upon H2 injection. The simulation results also predict that H2 diffusion in porous kerogen is about one order of magnitude higher than that of CH4 and CO2. This work provides an understanding of H2/CH4 behaviors in deleted gas reservoirs upon H2 injection and predictions of H2 loss and CH4 desorption in H2 storage.

Gallium nitride (GaN)-based nanoscale vacuum electron devices, which offer advantages of both traditional vacuum tube operation and modern solid-state technology, are attractive for radiation-hard applications due to the inherent radiation hardness of vacuum electron devices and the high radiation tolerance of GaN. Here, we investigate the radiation hardness of top-down fabricated n-GaN nanoscale vacuum electron diodes (NVEDs) irradiated with 2.5-MeV protons (p) at various doses. We observe a slight decrease in forward current and a slight increase in reverse leakage current as a function of cumulative protons fluence due to a dopant compensation effect. The NVEDs overall show excellent radiation hardness with no major change in electrical characteristics up to a cumulative fluence of 5E14 p/cm2, which is significantly higher than the existing state-of-the-art radiation-hardened devices to our knowledge. The results show promise for a new class of GaN-based nanoscale vacuum electron devices for use in harsh radiation environments and space applications.

Interim dry storage of spent nuclear fuel involves storing the fuel in welded stainless-steel canisters. Under certain conditions, the canisters could be subjected to environments that may promote stress corrosion cracking leading to a risk of breach and release of aerosol-sized particulate from the interior of the canister to the external environment through the crack. Research is currently under way by several laboratories to better understand the formation and propagation of stress corrosion cracks, however little work has been done to quantitatively assess the potential aerosol release. The purpose of the present work is to introduce a reliable generic numerical model for prediction of aerosol transport, deposition, and plugging in leak paths similar to stress corrosion cracks, while accounting for potential plugging from particle deposition. The model is dynamic (changing leak path geometry due to plugging) and it relies on the numerical solution of the aerosol transport equation in one dimension using finite differences. The model’s capabilities were also incorporated into a Graphical User Interface (GUI) that was developed to enhance user accessibility. Model validation efforts presented in this paper compare the model’s predictions with recent experimental data from Sandia National Laboratories (SNL) and results available in literature. We expect this model to improve the accuracy of consequence assessments and reduce the uncertainty of radiological consequence estimations in the remote event of a through-wall breach in dry cask storage systems.

In this work, we evaluate the usefulness of nonsmooth basis functions for representing the periodic response of a nonlinear system subject to contact/impact behavior. As with sine and cosine basis functions for classical Fourier series, which have C∞ smoothness, nonsmooth counterparts with C0 smoothness are defined to develop a nonsmooth functional representation of the solution. Some properties of these basis functions are outlined, such as periodicity, derivatives, and orthogonality, which are useful for functional series applied via the Galerkin method. Least-squares fits of the classical Fourier series and nonsmooth basis functions are presented and compared using goodness-of-fit metrics for time histories from vibro-impact systems with varying contact stiffnesses. This formulation has the potential to significantly reduce the computational cost of harmonic balance solvers for nonsmooth dynamical systems. Rather than requiring many harmonics to capture a system response using classical, smooth Fourier terms, the frequency domain discretization could be captured by a combination of a finite Fourier series supplemented with nonsmooth basis functions to improve convergence of the solution for contact-impact problems.

Abstract not provided.

The diesel-piloted dual-fuel compression ignition combustion strategy is well-suited to accelerate the decarbonization of transportation by adopting hydrogen as a renewable energy carrier into the existing internal combustion engine with minimal engine modifications. Despite the simplicity of engine modification, many questions remain unanswered regarding the optimal pilot injection strategy for reliable ignition with minimum pilot fuel consumption. The present study uses a single-cylinder heavy-duty optical engine to explore the phenomenology and underlying mechanisms governing the pilot fuel ignition and the subsequent combustion of a premixed hydrogen-air charge. The engine is operated in a dual-fuel mode with hydrogen premixed into the engine intake charge with a direct pilot injection of n-heptane as a diesel pilot fuel surrogate. Optical diagnostics used to visualize in-cylinder combustion phenomena include high-speed IR imaging of the pilot fuel spray evolution as well as high-speed HCHO* and OH* chemiluminescence as indicators of low-temperature and high-temperature heat release, respectively. Three pilot injection strategies are compared to explore the effects of pilot fuel mass, injection pressure, and injection duration on the probability and repeatability of successful ignition. The thermodynamic and imaging data analysis supported by zero-dimensional chemical kinetics simulations revealed a complex interplay between the physical and chemical processes governing the pilot fuel ignition process in a hydrogen containing charge. Hydrogen strongly inhibits the ignition of pilot fuel mixtures and therefore requires longer injection duration to create zones with sufficiently high pilot fuel concentration for successful ignition. Results show that ignition typically tends to rely on stochastic pockets with high pilot fuel concentration, which results in poor repeatability of combustion and frequent misfiring. This work has improved the understanding on how the unique chemical properties of hydrogen pose a challenge for maximization of hydrogen's energy share in hydrogen dual-fuel engines and highlights a potential mitigation pathway.

Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. We assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.

In this work, the frequency response of a simplified shaft-bearing assembly is studied using numerical continuation. Roller-bearing clearances give rise to contact behavior in the system, and past research has focused on the nonlinear normal modes of the system and its response to shock-type loads. A harmonic balance method (HBM) solver is applied instead of a time integration solver, and numerical continuation is used to map out the system’s solution branches in response to a harmonic excitation. Stability analysis is used to understand the bifurcation behavior and possibly identify numerical or system-inherent anomalies seen in past research. Continuation is also performed with respect to the forcing magnitude, resulting in what are known as S-curves, in an effort to detect isolated solution branches in the system response.

A quick-start manual for those interested in using the storage sizing and placement simulation application.

The primary goal of any laboratory test is to expose the unit-under-test to conservative realistic representations of a field environment. Satisfying this objective is not always straightforward due to laboratory equipment constraints. For vibration and shock tests performed on shakers over-testing and unrealistic failures can result because the control is a base acceleration and mechanical shakers have nearly infinite impedance. Force limiting and response limiting are relatively standard practices to reduce over-test risks in random-vibration testing. Shaker controller software generally has response limiting as a built-in capability and it is done without much user intervention since vibration control is a closed loop process. Limiting in shaker shocks is done for the same reasons, but because the duration of a shock is only a few milliseconds, limiting is a pre-planned user in the loop process. Shaker shock response limiting has been used for at least 30 years at Sandia National Laboratories, but it seems to be little known or used in industry. This objective of this paper is to re-introduce response limiting for shaker shocks to the aerospace community. The process is demonstrated on the BARBECUE testbed.

Disposal of commercial spent nuclear fuel in a geologic repository is studied. In situ heater experiments in underground research laboratories provide a realistic representation of subsurface behavior under disposal conditions. This study describes process model development and modeling analysis for a full-scale heater experiment in opalinus clay host rock. The results of thermal-hydrology simulation, solving coupled nonisothermal multiphase flow, and comparison with experimental data are presented. The modeling results closely match the experimental data.

The siting of nuclear waste is a process that requires consideration of concerns of the public. This report demonstrates the significant potential for natural language processing techniques to gain insights into public narratives around “nuclear waste.” Specifically, the report highlights that the general discourse regarding “nuclear waste” within the news media has fluctuated in prevalence compared to “nuclear” topics broadly over recent years, with commonly mentioned entities reflecting a limited variety of geographies and stakeholders. General sentiments within the “nuclear waste” articles appear to use neutral language, suggesting that a scientific or “facts-only” framing of “waste”-related issues dominates coverage; however, the exact nuances should be further evaluated. The implications of a number of these insights about how nuclear waste is framed in traditional media (e.g., regarding emerging technologies, historical events, and specific organizations) are discussed. This report lays the groundwork for larger, more systematic research using, for example, transformer-based techniques and covariance analysis to better understand relationships among “nuclear waste” and other nuclear topics, sentiments of specific entities, and patterns across space and time (including in a particular region). By identifying priorities and knowledge needs, these data-driven methods can complement and inform engagement strategies that promote dialogue and mutual learning regarding nuclear waste.