Publications

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Sandia National Laboratories is committed to being an informed, compassionate and contributing neighbor in our local communities. This commitment has been demonstrated throughout Sandia's history, and is an enduring part of our future. New Mexico faces many challenges, including one of the highest childhood poverty rates in the United States and one of the lowest educational proficiency rates. Lack of affordable housing and insufficient educational achievement are issues in the Bay Area near our Livermore site. To address the greatest challenges faced in Sandia's communities of Albuquerque, NM, and Livermore, CA, and other remote sites, Sandia's contributions leverage resources in three critical focus areas. In 2019, National Technology and Engineering Solutions of Sandia, contributed $1.4M to our local communities, including $151K in the Livermore area.

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Battery electrodes are composed of polydisperse particles and a porous, composite binder domain. These materials are arranged into a complex mesostructure whose morphology impacts both electrochemical performance and mechanical response. We present image-based, particle-resolved, mesoscale finite element model simulations of coupled electrochemical-mechanical performance on a representative NMC electrode domain. Beyond predicting macroscale quantities such as half-cell voltage and evolving electrical conductivity, studying behaviors on a per-particle and per-surface basis enables performance and material design insights previously unachievable. Voltage losses are primarily attributable to a complex interplay between interfacial charge transfer kinetics, lithium diffusion, and, locally, electrical conductivity. Mesoscale heterogeneities arise from particle polydispersity and lead to material underutilization at high current densities. Particle-particle contacts, however, reduce heterogeneities by enabling lithium diffusion between connected particle groups. While the porous composite binder domain (CBD) may have slower ionic transport and less available area for electrochemical reactions, its high electrical conductivity makes it the preferred reaction site late in electrode discharge. Mesoscale results are favorably compared to both experimental data and macrohomogeneous models. This work enables improvements in materials design by providing a tool for optimization of particle sizes, CBD morphology, and manufacturing conditions.

This work explores how High Perforrnance Computing is enabling acoustic solutions across a wide-range ofscience and engineering applications that were historically intractable.

Communication hypergraph model was introduced in a two-phase setting for encapsulating multiple communication cost metrics (bandwidth and latency), which are proven to be important in parallelizing irregular applications. In the first phase, computational-task-to-processor assignment is performed with the objective of minimizing total volume while maintaining computational load balance. In the second phase, communication-task-to-processor assignment is performed with the objective of minimizing total number of messages while maintaining communication-volume balance. The reduce-communication hypergraph model suffers from failing to correctly encapsulate send-volume balancing. We propose a novel vertex weighting scheme that enables part weights to correctly encode send-volume loads of processors for send-volume balancing. The model also suffers from increasing the total communication volume during partitioning. To decrease this increase, we propose a method that utilizes the recursive bipartitioning framework and refines each bipartition by vertex swaps. For performance evaluation, we consider column-parallel SpMV, which is one of the most widely known applications in which the reduce-task assignment problem arises. Extensive experiments on 313 matrices show that, compared to the existing model, the proposed models achieve considerable improvements in all communication cost metrics. Furthermore, these improvements lead to an average decrease of 30% in parallel SpMV time on 512 processors for 70 matrices with high irregularity.

In this work, the influence of clay platelet size on the corrosion barrier performance of highly-aligned polymer clay nanocomposite (PCN) thin films was examined. Layer-by-layer (LbL) deposition of alternating branched polyethylenimine (PEI) and either laponite (LAP), montromorillonite (MMT) or vermiculite (VMT) clay platelets were assembled on mild steel plates to obtain 20 bilayer (BL) films and cross-linked using glutaraldehyde after deposition. The clay platelets were chosen based on their aspect ratio, approximately 30:1, 400:1, and 2000:1, respectively. Electrochemical impedance spectroscopy of the coated steel plates during immersion showed corrosion rates and coating permeability followed LAP > MMT > VMT for up to 7 days of exposure in 0.6 M NaCl. The PEI/VMT films, ~250 nm thick, slowed corrosion by a factor of >1000 compared to bare steel. The results support the premise that high aspect ratio clay platelets can improve the corrosion barrier efficacy of LbL PCN films by decreasing film permeability and provide exceptional protection to steel in saline environments compared to other thin multilayer coatings and pretreatments.

This report is a condensed version of previous reports identifying technical gaps that, if addressed, could be used to ensure the continued safe storage of SNF for extended periods and support licensing activities. This report includes updated gap priority assessments because the previous gap priorities were based on R&D performed through 2017. Much important work has been done since 2017 that requires a change in a few of the priority rankings to better focus the near-term R&D program. Background material, regulatory positions, operational and inventory status, and prioritization schemes are discussed in detail in Hanson et al. (2012) and Hanson and Alsaed (2019) and are not repeated in this report. One exception is an overview of the prioritization criteria for reference. This is meant to give the reader an appreciation of the framework for prioritization of the identified gaps. A complete discussion of the prioritization scheme is provided in Hanson and Alsaed (2019).

Oxidative decomposition of organic-solvent-based liquid electrolytes at cathode material interfaces has been identified as the main reason for rapid capacity fade in high-voltage lithium ion batteries. The evolution of "cathode electrolyte interphase" (CEI) films, partly or completely consisting of electrolyte decomposition products, has also recently been demonstrated to correlate with battery cycling behavior at high potentials. Using density functional theory calculations, the hybrid PBE0 functional, and the (001) surfaces of spinel oxides as models, we examine these two interrelated processes. Consistent with previous calculations, ethylene carbonate (EC) solvent molecules are predicted to be readily oxidized on the LixMn2O4 (001) surface at modest operational voltages, forming adsorbed organic fragments. Further oxidative decomposition of such CEI fragments to release CO2 gas is however predicted to require higher voltages consistent with LixNi0.5Mn1.5O4 (LNMO) at smaller x values. We argue that multistep reactions, involving first formation of CEI films and then further oxidization of CEI at higher potentials, are most relevant to capacity fade. Mechanisms associated with dissolution or oxidation of native Li2CO3 films, which are removed before the electrolyte is in contact with oxide surfaces, are also explored.

A tethered-balloon system (TBS) has been developed and is being operated by Sandia National Laboratories (SNL) on behalf of the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) User Facility in order to collect in situ atmospheric measurements within mixed-phase Arctic clouds. Periodic tethered-balloon flights have been conducted since 2015 within restricted airspace at ARM's Advanced Mobile Facility 3 (AMF3) in Oliktok Point, Alaska, as part of the AALCO (Aerial Assessment of Liquid in Clouds at Oliktok), ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems), and POPEYE (Profiling at Oliktok Point to Enhance YOPP Experiments) field campaigns. The tethered-balloon system uses helium-filled 34 m3 helikites and 79 and 104 m3 aerostats to suspend instrumentation that is used to measure aerosol particle size distributions, temperature, horizontal wind, pressure, relative humidity, turbulence, and cloud particle properties and to calibrate ground-based remote sensing instruments.

Supercooled liquid water content (SLWC) sondes using the vibrating-wire principle, developed by Anasphere Inc., were operated at Oliktok Point at multiple altitudes on the TBS within mixed-phase clouds for over 200 h. Sonde-collected SLWC data were compared with liquid water content derived from a microwave radiometer, Ka-band ARM zenith radar, and ceilometer at the AMF3, as well as liquid water content derived from AMF3 radiosonde flights. The in situ data collected by the Anasphere sensors were also compared with data collected simultaneously by an alternative SLWC sensor developed at the University of Reading, UK; both vibrating-wire instruments were typically observed to shed their ice quickly upon exiting the cloud or reaching maximum ice loading. Temperature sensing measurements distributed with fiber optic tethered balloons were also compared with AMF3 radiosonde temperature measurements. Combined, the results indicate that TBS-distributed temperature sensing and supercooled liquid water measurements are in reasonably good agreement with remote sensing and radiosonde-based measurements of both properties. From these measurements and sensor evaluations, tethered-balloon flights are shown to offer an effective method of collecting data to inform and constrain numerical models, calibrate and validate remote sensing instruments, and characterize the flight environment of unmanned aircraft, circumventing the difficulties of in-cloud unmanned aircraft flights such as limited flight time and in-flight icing.

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The data from the multi-modal transportation test conducted in 2017 demonstrated that the inputs from the shock events during all transport modes (truck, rail, and ship) were amplified from the cask to the spent commercial nuclear fuel surrogate assemblies. These data do not support common assumption that the cask content experiences the same accelerations as the cask itself. This was one of the motivations for conducting 30 cm drop tests. The goal of the 30 cm drop test is to measure accelerations and strains on the surrogate spent nuclear fuel assembly and to determine whether the fuel rods can maintain their integrity inside a transportation cask when dropped from a height of 30 cm. The 30 cm drop is the remaining NRC normal conditions of transportation regulatory requirement (10 CFR 71.71) for which there are no data on the actual surrogate fuel. Because the full-scale cask and impact limiters were not available (and their cost was prohibitive), it was proposed to achieve this goal by conducting three separate tests. This report describes the first two tests — the 30 cm drop test of the 1/3 scale cask (conducted in December 2018) and the 30 cm drop of the full-scale dummy assembly (conducted in June 2019). The dummy assembly represents the mass of a real spent nuclear fuel assembly. The third test (to be conducted in the spring of 2020) will be the 30 cm drop of the full-scale surrogate assembly. The surrogate assembly represents a real full-scale assembly in physical, material, and mechanical characteristics, as well as in mass.

Gas ingested into the sac of a fuel injector after the injector needle valve closes is known to have crucial impacts on initial spray formation and plume growth in a following injection cycle. Yet little research has been attempted to understand the fate sac gases during pressure expansion and compression typical of an engine. This study investigated cavitation and bubble processes in the sac including the effect of chamber pressure decrease and increase consistent with an engine cycle. A single axial-hole transparent nozzle based on the Engine Combustion Network (ECN) Spray D nozzle geometry was mounted in a vessel filled with nitrogen, and the nitrogen gas pressure was cycled after the end of injection. Interior nozzle phenomena were visualized by high-speed longdistance microscopy with a nanosecond pulsed LED back-illumination. Experimental results showed that the volume of gas in the sac after the needle closes depends upon the vessel gas pressure. Higher back pressure results in less cavitation and a smaller volume of non-condensable gas in the sac. But a pressure decrease mimicking the expansion stroke causes the gas within the sac to expand significantly, proportional to the pressure decrease, while also evacuating liquid in front of the bubble. The volume of the gas in the sac increases during the expansion cycle due both to isothermal expansion as well as desorption of inherent dissolved gas in the fuel. During the compression cycle, the volume of bubbles decreases and additional non-condensable ambient gas is ingested into the sac. As the liquid fuel is nearly incompressible, the volume of both liquid and gas essentially remains constant during compression.

Here, we propose a dislocation adsorption-based mechanism for void growth in metals, wherein a void grows as dislocations from the bulk annihilate at its surface. The basic process is governed by glide and cross-slip of dislocations at the surface of a void. Using molecular dynamics simulations we show that when dislocations are present around a void, growth occurs more quickly and at much lower stresses than when the crystal is initially dislocation-free. Finally, we show that adsorption-mediated growth predicts an exponential dependence on the hydrostatic stress, consistent with the well-known Rice-Tracey equation.

The Waste Isolation Pilot Plant (WIPP) is a geologic repository for defense-related nuclear waste. If left undisturbed, the virtually impermeable rock salt surrounding the repository will isolate the nuclear waste from the biosphere. If humans accidentally intrude into the repository in the future, then the likelihood of a radionuclide release to the biosphere will depend significantly on the porosity and permeability of the repository itself. Room ceilings and walls at the WIPP tend to collapse over time, causing rubble piles to form on floors of empty rooms. The surrounding rock formation will gradually compact these rubble piles until they eventually become solid salt, but the length of time for a rubble pile to reach a certain porosity and permeability is unknown. This report details the first efforts to build models to predict the porosity and permeability evolution of an empty room as it closes. Conventional geomechanical numerical methods would struggle to model empty room collapse and rubble pile consolidation, so three different meshless methods, the Immersed Isogeometric Analysis Meshfree, Reproducing Kernel Particle Method (RKPM), and the Conformal Reproducing Kernel method, were assessed. First, the meshless methods and the finite element method each simulated gradual room closure, without ceiling or wall collapse. All three methods produced equivalent room closure predictions with comparable computational speed. Second, the Immersed Isogeometric Analysis Meshfree method and RKPM simulated two-dimensional empty room collapse and rubble pile consolidation. Both methods successfully simulated large viscoplastic deformations, fracture, and rubble pile rearrangement to produce qualitatively realistic results. In addition to geomechanical simulations, the flow channels in damaged salt and crushed salt were measured using micro-computed tomography, and input into a computational fluid dynamics simulation to predict the salt's permeability. Although room for improvement exists, the current simulation approaches appear promising.

The realization of metamaterials or metasurfaces with simultaneous electric and magnetic response and low loss is generally very difficult at optical frequencies. Traditional approaches using nanoresonators made of noble metals, while suitable for the microwave and terahertz regimes, fail at frequencies above the near-infrared, due to prohibitive high dissipative losses and the breakdown of scaling resulting from the electron mass contribution (kinetic inductance) to the effective reactance of these plasmonic meta-atoms. The alternative route based on Mie resonances of high-index dielectric particles normally leads to structure sizes that tend to break the effective-medium approximation. Here, we propose a subwavelength dark-state-based metasurface, which enables configurable simultaneous electric and magnetic responses with low loss. Proof-of-concept metasurface samples, specifically designed around telecommunication wavelengths (i.e., λ ≈ 1.5 μm), were fabricated and investigated experimentally to validate our theoretical concept. Because the electromagnetic field energy is localized and stored predominantly inside a dark resonant dielectric bound state, the proposed metasurfaces can overcome the loss issue associated with plasmonic resonators made of noble metals and enable scaling to very high operation frequency without suffering from saturation of the resonance frequency due to the kinetic inductance of the electrons

At the molecular level, resonant coupling of infrared radiation with oscillations of the electric dipole moment determines the absorption cross section, $σ$. The parameter σ relates the bond density to the total integrated absorption. In this work, $σ$ was measured for the Si–N asymmetric stretch mode in SiN_x thin films of varying composition and thickness. Thin films were deposited by low pressure chemical vapor deposition at 850 °C from mixtures of dichlorosilane and ammonia. σ for each film was determined from Fourier transform infrared spectroscopy and ellipsometric measurements. Increasing the silicon content from 0% to 25% volume fraction amorphous silicon led to increased optical absorption and a corresponding systematic increase in σ from 4.77 × 10^–20 to 6.95 × 10^–20 cm², which is consistent with literature values. The authors believe that this trend is related to charge transfer induced structural changes in the basal SiN_x tetrahedron as the volume fraction of amorphous silicon increases. Furthermore, experimental $σ$ values were used to calculate the effective dipole oscillating charge, q, for four films of varying composition. The authors find that q increases with increasing amorphous silicon content, indicating that compositional factors contribute to modulation of the Si–N dipole moment. Additionally, in the composition range investigated, the authors found that $σ$ agrees favorably with trends observed in films deposited by plasma enhanced chemical vapor deposition.

The Chemkin-Pro Advanced Programming Interface (API) was used to implement surface-kinetics user-routines to expand current aerosol dynamics models. Phase change mechanisms were expanded to include homogeneous nucleation in super-saturated environments, and particle size dependent vapor condensation and evaporation. Homogeneous nucleation of water droplets was modeled with Classical Nucleation Theory (CNT) and a modified form of nucleation theory published by Dillmann and Meier. The Chemkin-Pro homogeneous nucleation module, developed in this work, was validated against published data for nucleation fluxes at varying pressures, temperatures, and vapor concentrations. A newly released feature in Chemkin-Pro enabled particle-size-dependent surface reaction rates. A Chemkin-Pro vapor condensation and evaporation module was written and verified with the formulation published in Hinds. Lastly, Chemkin-Pro results for coagulation in the transition regime were verified with the semi-implicit method developed by Jacobson. We report good performance was observed for all three Chemkin-Pro modules. This work illustrates the utility of the Chemkin-Pro API, and the flexibility with which models can be developed using surface-kinetics user-routines. This paper illustrates that Chemkin-Pro can be developed to include more physically representative aerosol dynamics processes where rates are defined based on physical and chemical parameters rather than Arrhenius rates. The methods and modules developed in this work can be applied to industrial problems like material synthesis (e.g., powder production), processes involving phase change like heat exchangers, as well as more fundamental scientific processes like cloud physics.

High-temperature optical analysis of three different InGaN/GaN multiple quantum well (MQW) light-emitting diode (LED) structures (peak wavelength λ_p = 448, 467, and 515 nm) is conducted for possible integration as an optocoupler emitter in high density power electronic modules. The commercially available LEDs, primarily used in the display (λ_p = 467 and 515 nm) and lighting (λ_p = 448 nm) applications, are studied and compared to evaluate if they can satisfy the light output requirements in the optocouplers at high temperatures. The temperature- and intensity-dependent electroluminescence (T-IDEL) measurement technique is used to study the internal quantum efficiency (IQE) of the LEDs. All three LEDs exhibit above 70% IQE at 500 K and stable operation at 800 K without flickering or failure. At 800 K, a promising IQE of above 40% is observed for blue for display (BD) (λ_p = 467 nm) and green for display (GD) (λ_p = 515 nm) samples. The blue for light (BL) (λ_p = 448 nm) sample shows 24% IQE at 800 K.

In this work, we have characterized the calcium carbonate (CaCO3) precipitates over time caused by reaction-driven precipitation and dissolution in a micromodel. Reactive solutions were continuously injected through two separate inlets, resulting in transverse-mixing induced precipitation during the precipitation phase. Subsequently, a dissolution phase was conducted by injecting clean water (pH = 4). The evolution of precipitates was imaged in two and three dimensions (2-, 3-D) at selected times using optical and confocal microscopy. With estimated reactive surface area, effective precipitation and dissolution rates can be quantitatively compared to results in the previous works. Our comparison indicates that we can evaluate the spatial and temporal variations of effective reactive areas more mechanistically in the microfluidic system only with the knowledge of local hydrodynamics, polymorphs, and comprehensive image analysis. Our analysis clearly highlights the feedback mechanisms between reactions and hydrodynamics. Pore-scale modeling results during the dissolution phase were used to account for experimental observations of dissolved CaCO3 plumes with dissolution of the unstable phase of CaCO3. Mineral precipitation and dissolution induce complex dynamic pore structures, thereby impacting pore-scale fluid dynamics. Pore-scale analysis of the evolution of precipitates can reveal the significance of chemical and pore structural controls on reaction and fluid migration.

Establishing how water, or the absence of water, affects the structure, dynamics, and function of proteins in contact with inorganic surfaces is critical to developing successful protein immobilization strategies. In this work, the quantity of water hydrating a monolayer of helical peptides covalently attached to self-assembled monolayers (SAMs) of alkyl thiols on Au was measured using neutron reflectometry (NR). The peptide sequence was composed of repeating LLKK units in which the leucines were aligned to face the SAM. When immersed in water, NR measured 2.7 ± 0.9 water molecules per thiol in the SAM layer and between 75 ± 13 and 111 ± 13 waters around each peptide. The quantity of water in the SAM was nearly twice that measured prior to peptide functionalization, suggesting that the peptide disrupted the structure of the SAM. To identify the location of water molecules around the peptide, we compared our NR data to previously published molecular dynamics simulations of the same peptide on a hydrophobic SAM in water, revealing that 49 ± 5 of 95 ± 8 total nearby water molecules were directly hydrogen-bound to the peptide. Finally, we show that immersing the peptide in water compressed its structure into the SAM surface. Together, these results demonstrate that there is sufficient water to fully hydrate a surface-bound peptide even at hydrophobic interfaces. Given the critical role that water plays in biomolecular structure and function, these results are expected to be informative for a broad array of applications involving proteins at the bio/abio interface.

We demonstrate, on a scramjet combustion problem, a constrained probabilistic learning approach that augments physics-based datasets with realizations that adhere to underlying constraints and scatter. The constraints are captured and delineated through diffusion maps, while the scatter is captured and sampled through a projected stochastic differential equation. The objective function and constraints of the optimization problem are then efficiently framed as non-parametric conditional expectations. Different spatial resolutions of a large-eddy simulation filter are used to explore the robustness of the model to the training dataset and to gain insight into the significance of spatial resolution on optimal design.

A series of titanium alkoxides ([Ti(OR)₄] (OR = OCH(CH₃)₂ (OPri), OC(CH₃)₃ (OBut), and OCH₂C(CH₃)₃ (ONep)) were modified with a set of substituted hydroxyl-benzaldehydes [HO-BzA-Lx: x = 1, 2-hydroxybenzaldehyde (L = H), 2-hydroxy-3-methoxybenzaldehyde (OMe-3), 5-bromo-2-hydroxybenzaldehyde (Br-5), 2-hydroxy-5-nitrobenzaldehyde (NO₂-5); x = 2, 3,5-di-tert-butyl-2-hydroxybenzaldehyde (Bu^t-3,5), 2-hydroxy-3,5-diiodobenzaldehyde (I-3,5)] in pyridine (py). Instead of the expected simple substitution, each of the HO-BzA-Lx modifiers were reduced to their respective diol [(py)(OR)₂Ti(κ²(O,μ-O')(OC₆H_4–x(CH₂O)-2)(L)_x] (OR = OPrⁱ, x = 1, L = H (1a), OMe-3 (2a), Br-5 (3a·py), NO2-5 (4a·4py); x = 2, But-3,5 (5a), I-3,5 (6a), ONep; x = 1, L = H (1b), OMe-3 (2b), Br-5 (3b·py), NO2-5 (4b); x = 2, Bu^t-3,5 (5b), I-3,5 (6b·py)), as identified by single crystal X-ray studies. The ¹H NMR spectral data were complex at room temperature but simplified at high temperatures (70 °C). Diffusion ordered spectroscopy (DOSY) NMR experiments indicated that 2a maintained the dinuclear structure in a solution independent of the temperature, whereas 2b appears to be monomeric over the same temperature range. On the basis of additional NMR studies, the mechanism of the reduction of the HO-BzA-L_x to the dioxide ligand was thought to occur by a Meerwein–Pondorf–Verley (MPV) mechanism. The structures of 1a–6b appear to be the intermediate dioxide products of the MPV reduction, which became “trapped” by the Lewis basic solvate.

Since the landmark development of the Scherrer method a century ago, multiple generations of width methods for X-ray diffraction originated to non-invasively and rapidly characterize the property-controlling sizes of nanoparticles, nanowires, and nanocrystalline materials. However, the predictive power of this approach suffers from inconsistencies among numerous methods and from misinterpretations of the results. Therefore, we systematically evaluated twenty-two width methods on a representative nanomaterial subjected to thermal and mechanical loads. To bypass experimental complications and enable a 1:1 comparison between ground truths and the results of width methods, we produced virtual X-ray diffractograms from atomistic simulations. These simulations realistically captured the trends that we observed in experimental synchrotron diffraction. To comprehensively survey the width methods and to guide future investigations, we introduced a consistent, descriptive nomenclature. Alarmingly, our results demonstrated that popular width methods, especially the Williamson-Hall methods, can produce dramatically incorrect trends. We also showed that the simple Scherrer methods and the rare Energy methods can well characterize unloaded and loaded states, respectively. Overall, this work improved the utility of X-ray diffraction in experimentally evaluating a variety of nanomaterials by guiding the selection and interpretation of width methods.

Hermetic microcircuit packaging was the dominant method of protecting semiconductor devices in the 1960s and 1970s. After losing majority market sectors to plastic encapsulated microelectronics over the last a few decades, hermetic packaging remains the preferred method of protecting semiconductor devices for critical applications such as in military, space, and medical fields, where components and systems are required to serve for several decades. MEMS devices impose additional challenges to packaging by requiring specific internal cavity pressures to function properly or deliver the needed quality (Q) factors. In MEMS multichip modules, internal pressure requirement conflicts arise when different MEMS devices require different internal gases and pressures. The authors developed a closed-formed equation to model pressure changes of hermetic enclosures due to gas ingression. This article expands the authors mathematical model to calculate gas pressure of a MEMS multichip module package as well as those of MEMS devices inside the multichip module package. These equations are not only capable of calculating service lifetimes of MEMS devices and multi-chip modules but can also help develop MEMS device packaging strategies to extend the service life of MEMS multi-chip modules.

Hypersonic Vehicle (HV) development has been pursued since the late 1950s. These vehicles could significantly cut the cost of accessing space, lessen flight time anywhere on the planet to two to three hours, and be used as weapons that would be extremely difficult to intercept. Although considerable progress has been made, hypersonic flight remains in the development and testing phase.

Cytoskeletal filaments and motor proteins are critical components in the transport and reorganization of membrane-based organelles in eukaryotic cells. Previous studies have recapitulated the microtubule-kinesin transport system in vitro to dynamically assemble large-scale nanotube networks from multilamellar liposomes and polymersomes. Moving toward more biologically relevant systems, the present work examines whether lipid nanotube (LNT) networks can be generated from giant unilamellar vesicles (GUVs) and subsequently characterizes how the lipid composition may be tuned to alter the dynamics, structure, and fluidity of networks. Here, we describe a two-step process in which microtubule motility (i) drives the transport and aggregation of GUVs to form structures with a decreased energy barrier for LNT formation and (ii) extrudes LNTs without destroying parent GUVs, allowing for the formation of large LNT networks. We further show that the lipid composition of the GUV influences formation and morphology of the extruded LNTs and associated networks. For example, LNTs formed from phase-separated GUVs (e.g., liquid-solid phase-separated and coexisting liquid-ordered and liquid-disordered phase-separated) display morphologies related to the specific phase behavior reflective of the parent GUVs. Overall, the ability to form nanotubes from compositionally complex vesicles opens the door to generating lipid networks that more closely mimic the structure and function of those found in cellular systems.

The failure of 304L laser welds is of interest to system and component designers due to nuclear safety requirements for abnormal environments. Accurately modeling laser weld behavior in full system and component models has proven especially challenging due to three factors: the large variability observed in laser weld characterization tests; the difficulty in isolating the weld material for material characterization and modeling the weld material behavior; and the disparate scales associated with modeling laser welds in large systems. Recent work has shown that meso-scale geometric features of laser welds such as pores and weld root tortuosity are critical to accurately predicting the structural performance of welds. The challenge with modeling these welds is that the geometric features driving their structural performance are generally on the order of ten to hundreds of microns, but can affect the responses of interest in systems and components on the order of centimeters to meters.

A challenge for the TW-class accelerators driving Z-pinch experiments, such as Sandia National Laboratories’ Z machine, is to efficiently couple power from multiple storage banks into a single multi-MA transmission line. The physical processes that lead to current loss are identified in new large-scale, multidimensional simulations of the Z machine. Kinetic models follow the range of physics occurring during a pulse, from vacuum pulse propagation to charged-particle emission and magnetically-insulated current flow to electrode plasma expansion. Simulations demonstrate that current is diverted from the load through a combination of standard transport (uninsulated charged-particle flows) and anomalous transport. Standard transport occurs in regions where the electrode current density is a few 10⁴–10⁵ A/cm² and current is diverted from the load via transport without magnetic insulation. In regions with electrode current density >10⁶ A/cm², electrode surface plasmas develop velocity-shear instabilities and a Hall-field-related transport which scales with electron density and may, therefore, lead to increased current loss.

Soft matter has historically been an unlikely candidate for investigation by electron microscopy techniques due to damage by the electron beam as well as inherent instability under a high vacuum environment. Characterization of soft matter has often relied on ensemble-scattering techniques. The recent development of cryogenic transmission electron microscopy (cryo-TEM) provides the soft matter community with an exciting opportunity to probe the structure of soft materials in real space. Cryo-TEM reduces beam damage and allows for characterization in a native, frozen-hydrated state, providing direct visual representation of soft structure. This article reviews cryo-TEM in soft materials characterization and illustrates how it has provided unique insights not possible by traditional ensemble techniques. Soft matter systems that have benefited from the use of cryo-TEM include biological-based “soft” nanoparticles (e.g., viruses and conjugates), synthetic polymers, supramolecular materials as well as the organic–inorganic interface of colloidal nanoparticles. We conclude that while many challenges remain, such as combining structural and chemical analyses; the opportunity for soft matter research to leverage newly developed cryo-TEM techniques continues to excite.

X.509 certificate revocation defends against man-in-the-middle attacks involving a compromised certificate. Certificate revocation strategies face scalability, effectiveness, and deployment challenges as HTTPS adoption rates have soared. We propose Certificate Revocation Table (CRT), a new revocation strategy that is competitive with or exceeds alternative state-of-the-art solutions in effectiveness, efficiency, certificate growth scalability, mass revocation event scalability, revocation timeliness, privacy, and deployment requirements. The CRT design assumes that locality of reference applies to the certificates accessed by an organization. The CRT periodically checks the revocation status of X.509 certificates recently used by the organization. Pre-checking the revocation status of certificates the clients are likely to use avoids the security problems of on-demand certificate revocation checking. To validate both the effectiveness and efficiency of our approach, we simulated a CRT using 60 days of TLS traffic logs from Brigham Young University to measure the effects of actively refreshing revocation status information for various certificate working set window lengths. A working set window size of 45 days resulted in an average of 99.86% of the TLS handshakes having revocation information cached in advance. The CRT storage requirements are small. The initial revocation status information requires downloading a 6.7 MB file, and subsequent updates require only 205.1 KB of bandwidth daily. Updates that include only revoked certificates require just 215 bytes of bandwidth per day.

Impacts of silicon, carbon, and oxygen interfacial impurities on the performance of high-voltage vertical GaN-based p–n diodes are investigated. The results indicate that moderate levels (≈5 × 10¹⁷ cm^-3) of all interfacial impurities lead to reverse blocking voltages (V_b) greater than 200 V at 1 μA cm^-2 and forward leakage of less than 1 µA cm^-2 at 1.7 V. At higher interfacial impurity levels, the performance of the diodes becomes compromised. Herein, it is concluded that each impurity has a different effect on the device performance. For example, a high carbon spike at the junction correlates with high off-state leakage current in forward bias (≈100× higher forward leakage current compared with a reference diode), whereas the reverse bias behavior is not severely affected (> 200 V at 1 μA cm^-2). High silicon and oxygen spikes at the junction strongly affect the reverse leakage currents (≈ 1–10 V at 1 μA cm^-2). Regrown diodes with impurity (silicon, oxygen, and carbon) levels below 5 × 10¹⁷ cm^-3 show comparable forward and reverse results with the reference continuously grown diodes. The effect of the regrowth interface position relative to the metallurgical junction on the diode performance is also discussed.

Coherent elastic neutrino-nucleus scattering (CEvNS) is calculated to be the dominant neutrino scattering channel for neutrinos of energy E_ν < 100 MeV. We report a limit for this process from data collected in an engineering run of the 29 kg CENNS-10 liquid argon detector located 27.5 m from the pion decay-at-rest neutrino source at the Oak Ridge National Laboratory Spallation Neutron Source (SNS) with 4.2 × 10²² protons on target. The dataset provided constraints on beam-related backgrounds critical for future measurements and yielded < 7.4 candidate CEvNS events which implies a cross section for the process, averaged over the SNS pion decay-at-rest flux, of < 3.4 × 10^–39 cm², a limit within twice the Standard Model prediction. This is the first limit on CEvNS from an argon nucleus and confirms the earlier CsI[Na] nonstandard neutrino interaction constraints from the collaboration. This run demonstrated the feasibility of the ongoing experimental effort to detect CEvNS with liquid argon.

The objective of this project was to increase the rate at which video data is processed using temporal frequency analysis. A common solution to increasing the speed of data processing is to increase the computing power of the system however size, weight and power (SWAP) constraints require computing power to be limited. This project focused on increasing the processing speed by reducing the expense of computing the Fourier Transform (FT).

In this technical note, we present the analysis and results of neutron data collected in 2018 at the Spallation Neutron Source (SNS) by the MARS neutron detector and spectrometer. MARS has been deployed at the SNS "neutrino alley' basement with the purposed of monitoring and characterizing the neutron backgrounds for the COHERENT collaboration. The measured beam neutron rates at the MARS deployment location near some of the COHERENT neutrinos detectors are presented and we discuss what the measured rate and spectra can tell us about the incoming beam neutron flux and energy distribution.

Herein is presented the synthesis and characterization of copper-intercalated zirconium pentatelluride (ZrTe₅). ZrTe₅:Cu_0.05 crystals are synthesized by the chemical vapor transport method in a vacuum. X-ray diffraction and elemental analysis techniques are utilized to validate the synthesis. The results indicate that the intercalation of the layered Zr/Te structure with copper atoms causes the contraction of the unit cell along all three crystalline directions, the shrinkage of the overall volume of the unit cell, and the distortion of the unit cell. A single crystal was isolated, mechanically exfoliated, and used for the measurements of intercalation strains in a Hall bar device. Electronic transport studies indicate that an anomalous resistance drop is observed at T = 19 K. Furthermore, R_xx and R_xy results, respectively, indicate a probable disorder-induced localization effect and electron-type carriers.

Low energy ion scattering (LEIS) and direct recoil spectroscopy (DRS) are among the few experimental techniques that allow for the direct detection of hydrogen on a surface. The interpretation of LEIS and DRS measurements, however, is often made difficult by complexities that can arise from complicated scattering processes. Previously, these complexities were successfully navigated to identify the exact binding configurations of hydrogen on a few surfaces using a simple channeling model for the projectile ion along the surface. For the W(111) surface structure, this simple channeling model breaks down due to the large lateral atomic spacing on the surface and small interlayer spacing. Instead, our observed hydrogen recoil signal can only be explained by considering not just channeling along the surface but also scattering from subsurface atoms. Using this more complete model, together with molecular dynamics (MD) simulations, we determine that hydrogen adsorbs to the bond-centered site for the W(111)+H(ads) system. Additional MD simulations were performed to further constrain the adsorption site to a height h=1.0±0.1Å and a position dBC=1.6±0.1Å along the bond between neighbors in first and second layers. Our determination of the hydrogen adsorption site is consistent with density functional theory simulation results in the literature.

Through the use of advanced control techniques, wave energy converters (WECs) can achieve substantial increases in energy absorption. The motion of the WEC device is a significant contribution to the energy absorbed by the device. Reactive (complex conjugate) control maximizes the energy absorption due to the impedance matching. The issue with complex conjugate control is that, in general, the controller is noncausal, which requires prediction of the incoming waves. This article explores the potential of employing system identification techniques to build a causal transfer function that approximates the complex conjugate controller over a finite frequency band of interest. This approach is quite viable given the band-limited nature of ocean waves. The resulting controller is stable, and the average efficiency of the power captured by the causal controller in realistic ocean waves is 99%, when compared to the noncausal complex conjugate.

High-density growth nanotwins enable high-strength and good ductility in metallic materials. However, twinning propensity is greatly reduced in metals with high stacking fault energy. In this study, we adopted a hybrid technique coupled with template-directed heteroepitaxial growth method to fabricate single-crystal-like, nanotwinned (nt) Ni. The nt Ni primarily contains hierarchical twin structures that consist of coherent and incoherent twin boundary segments with few conventional grain boundaries. In situ compression studies show the nt Ni has a high flow strength of ~2 GPa and good deformability. Moreover, the nt Ni has superb corrosion behavior due to the unique twin structure in comparison to coarse grained and nanocrystalline counterparts. The hybrid technique opens the door for the fabrication of a wide variety of single-crystal-like nt metals with unique mechanical and chemical properties.

Plastic deformations in metals are dissipative. Some fraction of the dissipated mechanical energy (plastic work) is converted into thermal energy and serves as a heat source. In cases where the heat cannot be readily transferred to the environment, the local temperature will increase thereby producing variations in mechanical behaviors associated with temperature-dependent properties (e.g. thermal softening due to decreasing yield strengths). This issue is often referred to as "adiabatic heating as an adiabatic temperature condition corresponds to the limiting case where no heat transfer takes place. The impact of converting plastic work into heat on the mechanical response of metals has been long studied. Nonetheless, it still remains an issue. For instance, with respect to ductile failure, the second Sandia Fracture Challenge noted that accounting for plastic heat generation was necessary for predictions under dynamic loading conditions. Furthermore, both experimental and modeling efforts continue to be pursued to better describe and understand the effect of plastic work conversion into heat on structural responses. Noting the need for capturing plastic work conversion into heat in structural analyses, a simple and fairly traditional representation of these responses has been added into existing modular plasticity models in the Library of Advanced Materials for Engineering (LAME). Here, these capabilities are briefly described with the underlying theory and numerical implementation discussed in Sections 2 and 3, respectively. Examples of syntax are given in Section 4 and some verification exercises are found in Section 5. Simple structural analyses are presented in Section 6 to briefly highlight the impact of these features and concluding thoughts are given.

Sandia National Laboratories will, as time and budget allow, perform the following tasks as part of a New Mexico Small Business Assistance (NMSBA) Program project for Management Sciences, Inc. (MSI): 1. Set up a thermal radar in Sandia's Technical Area (TA) III test bed. 2. Collect alarm data from the thermal radar and a radio frequency (RF) radar during simulated intrusion tests to estimate detection performance, based on the Department of Energy (DOE) threat definition. 3. Collect nuisance alarm data caused by weather and non-intruder-related stimuli, to estimate nuisance alarm rate performance. 4. Provide data to the requester, allowing them to process the data. 5. Provide the requester, as a stretch goal, with live radar and thermal radar sensor feeds, allowing real-time processing of the RF radar and the thermal radar. A key technical issue that will influence the success of this activity is the range accuracy of the thermal radar. If issues are encountered, Sandia will work with the requester to correct the range issues.

Conventional electrolytes made by mixing simple Mg²⁺ salts and aprotic solvents, analogous to those in Li-ion batteries, are incompatible with Mg anodes because Mg metal readily reacts with such electrolytes, producing a passivation layer that blocks Mg²⁺ transport. In this paper, we report that, through tuning a conventional electrolyte—Mg(TFSI)₂ (TFSI^– is N(SO₂CF₃)₂^–)—with an Mg(BH₄)₂ cosalt, highly reversible Mg plating/stripping with a high Coulombic efficiency is achieved by neutralizing the first solvation shell of Mg cationic clusters between Mg²⁺ and TFSI^– and enhanced reductive stability of free TFSI^–. A critical adsorption step between Mg⁰ atoms and active Mg cation clusters involving BH₄^– anions is identified to be the key enabler for reversible Mg plating/stripping through analysis of the distribution of relaxation times (DRT) from operando electrochemical impedance spectroscopy (EIS), operando electrochemical X-ray absorption spectroscopy (XAS), nuclear magnetic resonance (NMR), and density functional theory (DFT) calculations.

An increased demand for privacy in Internet communications has resulted in privacy-centric enhancements to the Domain Name System (DNS), including the use of Transport Layer Security (TLS) and Hypertext Transfer Protocol Secure (HTTPS) for DNS queries. In this paper, we seek to answer questions about their deployment, including their prevalence and their characteristics. Our work includes an analysis of DNS-over-TLS (DoT) and DNS-over-HTTPS (DoH) availability at open resolvers and authoritative DNS servers. We find that DoT and DoH services exist on just a fraction of open resolvers, but among them are the major vendors of public DNS services. We also analyze the state of TCP Fast Open (TFO), which is considered key to reducing the latency associated with TCP-based DNS queries, required by DoT and DoH. The uptake of TFO is extremely low, both on the server side and the client side, and it must be improved to avoid performance degradation with continued adoption of DNS Privacy enhancements.

Trusting simulation output is crucial for Sandia’s mission objectives. Here, we rely on these simulations to perform our high-consequence mission tasks given national treaty obligations. Other science and modeling applications, while they may have high-consequence results, still require the strongest levels of trust to enable using the result as the foundation for both practical applications and future research. To this end, the computing community has developed workflow and provenance systems to aid in both automating simulation and modeling execution as well as determining exactly how was some output was created so that conclusions can be drawn from the data. Current approaches for workflows and provenance systems are all at the user level and have little to no system level support making them fragile, difficult to use, and incomplete solutions. The introduction of container technology is a first step towards encapsulating and tracking artifacts used in creating data and resulting insights, but their current implementation is focused solely on making it easy to deploy an application in an isolated “sandbox” and maintaining a strictly read-only mode to avoid any potential changes to the application. All storage activities are still using the system-level shared storage. This project explores extending the container concept to include storage as a new container type we call data pallets. Data Pallets are potentially writeable, auto generated by the system based on IO activities, and usable as a way to link the contained data back to the application and input deck used to create it.

Hole spins have recently emerged as attractive candidates for solid-state qubits for quantum computing. Their state can be manipulated electrically by taking advantage of the strong spin-orbit interaction (SOI). Crucially, these systems promise longer spin coherence lifetimes owing to their weak interactions with nuclear spins as compared to electron spin qubits. Here we measure the spin relaxation time T1 of a single hole in a GaAs gated lateral double quantum dot device. We propose a protocol converting the spin state into long-lived charge configurations by the SOI-assisted spin-flip tunneling between dots. By interrogating the system with a charge detector we extract the magnetic-field dependence of T1 ∝ B−5 for fields larger than B = 0.5 T, suggesting the phonon-assisted Dresselhaus SOI as the relaxation channel. This coupling limits the measured values of T1 from ~400 ns at B = 1.5 T up to ~60 μs at B = 0.5 T.

The historic city of Saint Petersburg is full of memorial plaques—ballet dancers, literary giants, composers, war heroes, and even mathematicians. Here, if you go to the metro station Petrogradskaya, cross the bridge over the tiny Karpovka River, and reach ulitsa Professora Popova—Professor Popov Street—then almost surely you are going to one of two destinations. First, perhaps you are going to the Saint Petersburg Electrotechnical University, colloquially known as LETI. Second, you may be going for a stroll in the botanical garden of the V. L. Komarov Institute of the Russian Academy of Sciences.

Flame detectors provide an important layer of protection for personnel in petrochemical plants, but effective placement can be challenging. A mixed-integer nonlinear programming formulation is proposed for optimal placement of flame detectors while considering non-uniform probabilities of detection failure. We show that this approach allows for the placement of fire detectors using a fixed sensor budget and outperforms models that do not account for imperfect detection. We develop a linear relaxation to the formulation and an efficient solution algorithm that achieves global optimality with reasonable computational effort. We integrate this problem formulation into the Python package, Chama, and demonstrate the effectiveness of this formulation on a small test case and on two real-world case studies using the fire and gas mapping software, Kenexis Effigy.

The energy grid becomes more complex with increasing penetration of renewable resources, distributed energy storage, distributed generators, and more diverse loads such as electric vehicle charging stations. The presence of distributed energy resources (DERs) requires directional protection due to the added potential for energy to flow in both directions down the line. Additionally, contingency requirements for critical loads within a microgrid may result in looped or meshed systems. Computation speeds of iterative methods required to coordinate loops are improved by starting with a minimum breakpoint set (MBPS) of relays. A breakpoint set (BPS) is a set of breakers such that, when opened, breaks all loops in a mesh grid creating a radial system. A MBPS is a BPS that consists of the minimum possible number of relays required to accomplish this goal. In this paper, a method is proposed in which a minimum spanning tree is computed to indirectly break all loops in the system, and a set difference is used to identify the MBPS. The proposed method is found to minimize the cardinality of the BPS to achieve a MBPS.

The measurement of minority carrier lifetimes is vital to determining the material quality and operational bandwidth of a broad range of optoelectronic devices. Typically, these measurements are made by recording the temporal decay of a carrier-concentration-dependent material property following pulsed optical excitation. Such approaches require some combination of efficient emission from the material under test, specialized collection optics, large sample areas, spatially uniform excitation, and/or the fabrication of ohmic contacts, depending on the technique used. In contrast, here we introduce a technique that provides electrical readout of minority carrier lifetimes using a passive microwave resonator circuit. We demonstrate >105 improvement in sensitivity, compared with traditional photoemission decay experiments and the ability to measure carrier dynamics in micron-scale volumes, much smaller than is possible with other techniques. The approach presented is applicable to a wide range of 2D, micro-, or nano-scaled materials, as well as weak emitters or non-radiative materials.

Here, we review the progress and most recent advances in phonon-polaritonics, an emerging and growing field that has brought about a range of powerful possibilities for mid- to far-infrared (IR) light. These extraordinary capabilities are enabled by the resonant coupling between the impinging light and the vibrations of the material lattice, known as phonon-polaritons (PhPs). These PhPs yield a characteristic optical response in certain materials, occurring within an IR spectral window known as the reststrahlen band. In particular, these materials transition in the reststrahlen band from a high refractive-index behavior, to a near-perfect metal behavior, to a plasmonic behavior - typical of metals at optical frequencies. When anisotropic they may also possess unconventional photonic constitutive properties thought of as possible only with metamaterials. The recent surge in two-dimensional (2D) material research has also enabled PhP responses with atomically-thin materials. Such vast and extraordinary photonic responses can be utilized for a plethora of unusual effects for IR light. Examples include sub-diffraction surface wave guiding, artificial magnetism, exotic photonic dispersions, thermal emission enhancement, perfect absorption and enhanced near-field heat transfer. Finally, we discuss the tremendous potential impact of these IR functionalities for the advancement of IR sources and sensors, as well as for thermal management and THz-diagnostic imaging.

Knowledge graph embedding (KGE) learns latent vector representations of named entities (i.e., vertices) and relations (i.e., edge labels) of knowledge graphs. Herein, we address two problems in KGE. First, relations may belong to one or multiple categories, such as functional, symmetric, transitive, reflexive, and so forth; thus, relation categories are not exclusive. Some relation categories cause non-trivial challenges for KGE. Second, we found that zero gradients happen frequently in many translation based embedding methods such as TransE and its variations. To solve these problems, we propose i) converting a knowledge graph into a bipartite graph, although we do not physically convert the graph but rather use an equivalent trick; ii) using multiple vector representations for a relation; and iii) using a new hinge loss based on energy ratio(rather than energy gap) that does not cause zero gradients. We show that our method significantly improves the quality of embedding.

Electrical tunability of the g-factor of a confined spin is a long-time goal of the spin qubit field. Here we utilize the electric dipole spin resonance (EDSR) to demonstrate it in a gated GaAs double-dot device confining a hole. This tunability is a consequence of the strong spin-orbit interaction (SOI) in the GaAs valence band. The SOI enables a spin-flip interdot tunneling, which, in combination with the simple spin-conserving charge transport leads to the formation of tunable hybrid spin-orbit molecular states. EDSR is used to demonstrate that the gap separating the two lowest energy states changes its character from a charge-like to a spin-like excitation as a function of interdot detuning or magnetic field. In the spin-like regime, the gap can be characterized by the effective g-factor, which differs from the bulk value owing to spin-charge hybridization, and can be tuned smoothly and sensitively by gate voltages.

Commercial light emitting diode (LED) materials - blue (i.e., InGaN/GaN multiple quantum wells (MQWs) for display and lighting), green (i.e., InGaN/GaN MQWs for display), and red (i.e., Al0.05Ga0.45In0.5P/Al0.4Ga0.1In0.5P for display) are evaluated in range of temperature (77–800) K for future applications in high density power electronic modules. The spontaneous emission quantum efficiency (QE) of blue, green, and red LED materials with different wavelengths was calculated using photoluminescence (PL) spectroscopy. The spontaneous emission QE was obtained based on a known model so-called the ABC model. This model has been recently used extensively to calculate the internal quantum efficiency and its droop in the III-nitride LED. At 800 K, the spontaneous emission quantum efficiencies are around 40% for blue for lighting and blue for display LED materials, and it is about 44.5% for green for display LED materials. The spontaneous emission QE is approximately 30% for red for display LED material at 800 K. The advance reported in this paper evidences the possibility of improving high temperature optocouplers with an operating temperature of 500 K and above.

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Due to natural heterogeneity in rock specimens, classifying rock characteristics can present difficulties. 3D printing geo-architectured rock specimens has the potential to reduce the heterogeneity and help evaluate characteristics with reproducible microstructures, bedding, and strength to advance mechanical interpretations. This testing focused on 3D printing effects on strength and rock behavior by varying amount of binder, printing direction, and atmospheric conditions. A powder-based Gypsum 3D printer was used to create 1.5-inch diameter cylindrical samples. Unconfined compressive strength (UCS) testing was completed on these samples to gather failure plots and peak strength. Multiple batches of cylindrical samples were printed with varying printing direction, binder amount, and atmospheric conditions. UCS results show that the strongest samples were those that were printed perpendicular to the loading direction compared to those printed parallel or 45 degrees. Due to reactions of the printing material with water, those at dry conditions were the strongest. Samples with the most binder amount proved to also be stronger than those with less. 3D printing of rock samples has to the potential to reduce heterogeneity rock presents, however additional factors introduced by the printing process can affect overall rock strength and behavior. Test results of the 3D printed geo-architected rock specimens demonstrated reasonable reproducibility and appear to be a promising path towards increasing the ability to characterize natural rock.

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Mitigating corrosion remains a daunting challenge due to localized, nanoscale corrosion events that are poorly understood but are known to cause unpredictable variations in material longevity. Here, the most recent advances in liquid-cell transmission electron microscopy were employed to capture the advent of localized aqueous corrosion in carbon steel at the nanoscale and in real time. Localized corrosion initiated at a triple junction formed by a solitary cementite grain and two ferrite grains and then continued at the electrochemically-active boundary between these two phases. With this analysis, we identified facetted pitting at the phase boundary, uniform corrosion rates from the steel surface, and data that suggest that a re-initiating galvanic corrosion mechanism is possible in this environment. These observations represent an important step toward atomically defining nanoscale corrosion mechanisms, enabling the informed development of next-generation inhibition technologies and the improvement of corrosion predictive models.

The competition between ductile rupture mechanisms in high-purity Cu and other metals is sensitive to the material composition and loading conditions, and subtle changes in the metal purity can lead to failure either by void coalescence or Orowan Alternating Slip (OAS). In situ X-ray computed tomography tensile tests on 99.999% purity Cu wires have revealed that the rupture process involves a sequence of damage events including shear localization; growth of micron-sized voids; and coalescence of microvoids into a central cavity prior to the catastrophic enlargement of the coalesced void via OAS. This analysis has shown that failure occurs in a collaborative rather than strictly competitive manner. In particular, strain localization along the shear band enhanced void nucleation and drove the primary coalescence event, and the size of the resulting cavity and consumption of voids ensured a transition to the OAS mechanism rather than continued void coalescence. Additionally, the tomograms identified examples of void coalescence and OAS growth of individual voids at all stages of the failure process, suggesting that the transition between the different mechanisms was sensitive to local damage features, and could be swayed by collaboration with other damage mechanisms. The competition between the different damage mechanisms is discussed in context of the material composition, the local damage history, and collaboration between the mechanisms.

Changing the length of a laser cavity is a simple technique for continuously tuning the wavelength of a laser but is rarely used for broad fractional tuning, with a notable exception of the vertical-cavity surface-emitting laser (VCSEL)1,2. This is because, to avoid mode hopping, the cavity must be kept optically short to ensure a large free spectral range compared to the gain bandwidth of the amplifying material. Terahertz quantum-cascade lasers are ideal candidates for such a short cavity scheme as they demonstrate exceptional gain bandwidths (up to octave spanning)3 and can be integrated with broadband amplifying metasurfaces4. We present such a quantum-cascade metasurface-based vertical-external-cavity surface-emitting laser (VECSEL) that exhibits over 20% continuous fractional tuning of a single laser mode. Such tuning is possible because the metasurface has subwavelength thickness, which allows lasing on low-order Fabry–Pérot cavity modes. Good beam quality and high output power are simultaneously obtained.

Tetradymite-structured chalcogenides such as bismuth telluride (Bi 2 Te 3 ) are of significant interest for thermoelectric energy conversion and as topological insulators. Dislocations play a critical role during synthesis and processing of such materials and can strongly affect their functional properties. The dislocations between quintuple layers present special interest since their core structure is controlled by the van der Waals interactions between the layers. In this work, using atomic-resolution electron microscopy, we resolve the basal dislocation core structure in Bi 2 Te 3 , quantifying the disregistry of the atomic planes across the core. We show that, despite the existence of a stable stacking fault in the basal plane gamma surface, the dislocation core spreading is mainly due to the weak bonding between the layers, which leads to a small energy penalty for layer sliding parallel to the van der Waals gap. Calculations within a semidiscrete variational Peierls-Nabarro model informed by first-principles calculations support our experimental findings.

In a traditional data-processing pipeline, waveforms are acquired, a detector makes the signal detections (i.e., arrival times, slownesses, and azimuths) and passes them to an associator. The associator then links the detections to the fitting-event hypotheses to generate an event bulletin. Most of the time, this traditional pipeline requires substantial human-analyst involvement to improve the quality of the resulting event bulletin. For the year 2017, for example, International Data Center (IDC) analysts rejected about 40% of the events in the automatic bulletin and manually built 30% of the legitimate events. We propose an iterative processing framework (IPF) that includes a new data-processing module that incorporates automatic analyst behaviors (auto analyst [AA]) into the event-building pipeline. In the proposed framework, through an iterative process, the AA takes over many of the tasks traditionally performed by human analysts. These tasks can be grouped into two major processes: (1) evaluating small events with a low number of location-defining arrival phases to improve their formation; and (2) scanning for and exploiting unassociated arrivals to form potential events missed by previous association runs. To test the proposed framework, we processed a two-week period (15–28 May 2010) of the signal-detections dataset from the IDC. Comparison with an expert analyst-reviewed bulletin for the same time period suggests that IPF performs better than the traditional pipelines (IDC and baseline pipelines). Most of the additional events built by the AA are low-magnitude events that were missed by these traditional pipelines. The AA also adds additional signal detections to existing events, which saves analyst time, even if the event locations are not significantly affected.

The capability to discriminate low-magnitude earthquakes from low-yield anthropogenic sources, both detectable only at local distances, is of increasing interest to the event monitoring community. We used a dataset of seismic events in Utah recorded during a 14-day period (1–14 January 2011) by the University of Utah Seismic Stations network to perform a comparative study of event classification at local scale using amplitude ratio (AR) methods and a machine learning (ML) approach. The event catalog consists of 7377 events with magnitudes MC ranging from −2 and lower up to 5.8. Events were subdivided into six populations based on location and source type: tectonic earthquakes (TEs), mining-induced events (MIEs), and mining blasts from four known mines (WMB, SMB, LMB, and CQB). The AR approach jointly exploits Pg-to-Sg phase ARs and Rg-to-Sg spectral ARs in multivariate quadratic discriminant functions and was able to classify 370 events with high signal quality from the three groups with sufficient size (TE, MIE, and SMB). For that subset of the events, the method achieved success rates between about 80% and 90%. The ML approach used trained convolutional neural network (CNN) models to classify the populations. The CNN approach was able to classify the subset of events with accuracies between about 91% and 98%. Because the neural network approach does not have a minimum signal quality requirement, we applied it to the entire event catalog, including the abundant extremely low-magnitude events, and achieved accuracies of about 94%–100%. We compare the AR and ML methodologies using a broad set of criteria and conclude that a major advantage to ML methods is their robustness to low signal-to-noise ratio data, allowing them to classify significantly smaller events.

Kinesin motors and their associated filaments, microtubules, are essential to many biological processes. The motor and filament system can be reconstituted in vitro with the surface-adhered motors transporting the filaments along the surface. In this format, the system has been used to study active self-assembly and to power microdevices or perform analyte detection. However, fundamental properties of the system, such as the spacing of the kinesin motors bound to the microtubule and the dynamics of binding, remain poorly understood. We show that Fluorescence Interference Contrast (FLIC) microscopy can illuminate the exact height of the microtubule, which for a sufficiently low surface density of kinesin, reveals the locations of the bound motors. We examine the spacing of the kinesin motors on the microtubules at various kinesin surface densities and compare the results with theory. FLIC reveals that the system is highly dynamic, with kinesin binding and unbinding along the length of the microtubule as it is transported along the surface.

The ultrawide bandgap (UWBG) (4.8 eV) and melt-grown substrate availability of β-Ga2O3 give promise to the development of next-generation power electronic devices with dramatically improved size, weight, power, and efficiency over current state-of-the-art WBG devices based on 4H-SiC and GaN. Also, with recent advancements made in gigahertz frequency radio frequency (RF) applications, the potential for monolithic or heterogenous integration of RF and power switches has attracted researchers' attention. However, it is expected that Ga2O3 devices will suffer from self-heating due to the poor thermal conductivity of the material. Thermoreflectance thermal imaging and infrared thermography were used to understand the thermal characteristics of a MOSFET fabricated via homoepitaxy. A 3-D coupled electrothermal model was constructed based on the electrical and thermal characterization results. The device model shows that a homoepitaxial device suffers from an unacceptable junction temperature rise of 1500 °C under a targeted power density of 10 W/mm, indicating the importance of employing device-level thermal managements to individual Ga2O3 transistors. The effectiveness of various active and passive cooling solutions was tested to achieve a goal of reducing the device operating temperature below 200 °C at a power density of 10 W/mm. Results show that flip-chip heterointegration is a viable option to enhance both the steady-state and transient thermal characteristics of Ga2O3 devices without sacrificing the intrinsic advantage of high-quality native substrates. Also, it is not an active thermal management solution that entails peripherals requiring additional size and cost implications.

High-fidelity single-shot readout of spin qubits requires distinguishing states much faster than the T1 time of the spin state. One approach to improving readout fidelity and bandwidth (BW) is cryogenic amplification, where the signal from the qubit is amplified before noise sources are introduced and room-temperature amplifiers can operate at lower gain and higher BW. We compare the performance of two cryogenic amplification circuits: a current-biased heterojunction bipolar transistor circuit (CB-HBT), and an AC-coupled HBT circuit (AC-HBT). Both circuits are mounted on the mixing-chamber stage of a dilution refrigerator and are connected to silicon metal oxide semiconductor (Si-MOS) quantum dot devices on a printed circuit board (PCB). The power dissipated by the CB-HBT ranges from 0.1 to 1 μW whereas the power of the AC-HBT ranges from 1 to 20 μW. Referred to the input, the noise spectral density is low for both circuits, in the 15 to 30 fA/Hz range. The charge sensitivity for the CB-HBT and AC-HBT is 330 μe/Hz and 400 μe/Hz, respectively. For the single-shot readout performed, less than 10 μs is required for both circuits to achieve bit error rates below 10−3, which is a putative threshold for quantum error correction.

We address the problem of simultaneous coverage control and stochastic, multi-target tracking with a single pursuer. We presume linear dynamics for the pursuer and linear stochastic dynamics for the targets. The pursuer is equipped with two sensors of varying fidelity: broad-range and narrow-range. We seek the optimal trajectory for the pursuer, as well as optimal sensor selection, over a finite time horizon. We formulate the problem as a mixed-integer program with quadratic constraints, and exploit a convex relaxation method to enable fast solution of local minima. We demonstrate our approach on several simulated scenarios.

A key problem in social network analysis is to identify nonhuman interactions. State-of-the-art bot-detection systems like Botometer train machine-learning models on user-specific data. Unfortunately, these methods do not work on data sets in which only topological information is available. In this paper, we propose a new, purely topological approach. Our method removes edges that connect nodes exhibiting strong evidence of non-human activity from publicly available electronic-social-network datasets, including, for example, those in the Stanford Network Analysis Project repository (SNAP). Our methodology is inspired by classic work in evolutionary psychology by Dunbar that posits upper bounds on the total strength of the set of social connections in which a single human can be engaged. We model edge strength with Easley and Kleinberg's topological estimate; label nodes as “violators” if the sum of these edge strengths exceeds a Dunbar-inspired bound; and then remove the violator-to-violator edges. We run our algorithm on multiple social networks and show that our Dunbar-inspired bound appears to hold for social networks, but not for nonsocial networks. Our cleaning process classifies 0.04% of the nodes of the Twitter-2010 followers graph as violators, and we find that more than 80% of these violator nodes have Botometer scores of 0.5 or greater. Furthermore, after we remove the roughly 15 million violator-violator edges from the 1.2-billion-edge Twitter-2010 follower graph, 34% of the violator nodes experience a factor-of-two decrease in PageRank. PageRank is a key component of many graph algorithms such as node/edge ranking and graph sparsification. Thus, this artificial inflation would bias algorithmic output, and result in some incorrect decisions based on this output.

A persistent challenge present in inverse or parameter estimation problems with interior data is how to deal with uncertainty in the boundary conditions employed in the forward or state model. In this work we focus on a linear plane stress inverse elasticity problem with measured displacement data where one component of the measured displacement field is known with considerably greater precision than the other. This situation is commonly encountered when the displacement field is measured using ultrasound or optical coherence tomography. We present a novel computational formulation in which no displacement or traction boundary conditions are assumed. The formulation results in coupling the state and adjoint equations, that are typically uncoupled when a well-posed state model is available. Two variants of residual-based stabilization are added. Our approach is applied to a simulated data set and experimental data from an ultrasound phantom.

The populations of flaws in individual layers of microelectromechanical systems (MEMS) structures are determined and verified using a combination of specialized specimen geometry, recent probabilistic analysis, and topographic mapping. Strength distributions of notched and tensile bar specimens are analyzed assuming a single flaw population set by fabrication and common to both specimen geometries. Both the average spatial density of flaws and the flaw size distribution are determined and used to generate quantitative visualizations of specimens. Scanning probe-based topographic measurements are used to verify the flaw spacings determined from strength tests and support the idea that grain boundary grooves on sidewalls control MEMS failure. The findings here suggest that strength controlling features in MEMS devices increase in separation, i.e., become less spatially dense, and decrease in size, i.e., become less potent flaws, as processing proceeds up through the layer stack. The method demonstrated for flaw population determination is directly applicable to strength prediction for MEMS reliability and design.

The Oxford MinION, the first commercial nanopore sequencer, is also the first to implement molecule-by-molecule real-time selective sequencing or “Read Until”. As DNA transits a MinION nanopore, real-time pore current data can be accessed and analyzed to provide active feedback to that pore. Fragments of interest are sequenced by default, while DNA deemed non-informative is rejected by reversing the pore bias to eject the strand, providing a novel means of background depletion and/or target enrichment. In contrast to the previously published pattern-matching Read Until approach, our RUBRIC method is the first example of real-time selective sequencing where on-line basecalling enables alignment against conventional nucleic acid references to provide the basis for sequence/reject decisions. We evaluate RUBRIC performance across a range of optimizable parameters, apply it to mixed human/bacteria and CRISPR/Cas9-cut samples, and present a generalized model for estimating real-time selection performance as a function of sample composition and computing configuration.

Cryogenic transmission electron microscopy is simply transmission electron microscopy conducted on specimens that are cooled in the microscope. The target temperature of the specimen might range from just below ambient temperature to less than 4 K. In general, as the temperature decreases, cost increases, especially below -77°C when liquid He is required. We have two reasons for wanting to cool the specimen - improving stability of the material or observing a material whose properties change at lower temperatures. Both types of study have a long history. The cause of excitement in this field today is that we have a perfect storm of research activity - electron microscopes are almost stable with minimal drift (we can correct what drift there is), we can prepare specimens from the bulk or build them up, we have spherical-aberration-corrected lenses and monochromated beams, we have direct-electron-detector cameras, and computers are becoming powerful enough to handle all the data we produce.

Charge noise can be detrimental to the operation of quantum dot (QD) based semiconductor qubits. We study the low-frequency charge noise by charge offset drift measurements for Si-MOS devices with intentionally implanted donors near the QDs. We show that the MOS system exhibits non-equilibrium drift characteristics, in the form of transients and discrete jumps, that are not dependent on the properties of the donor implants. The equilibrium charge noise indicates a 1/f noise dependence, and a noise strength as low as 1μeV/Hz, comparable to that reported in more model GaAs and Si/SiGe systems (which have also not been implanted). We demonstrate that implanted qubits, therefore, can be fabricated without detrimental effects on long-term drift or 1/f noise for devices with less than 50 implanted donors near the qubit.

Algae ponds used in industrial biomass production are susceptible to pathogen or grazer infestation, resulting in pond crashes with high economic costs. Current methods to monitor and mitigate unhealthy ponds are hindered by a lack of early indicators that precede culture crash. We used solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to identify volatiles emitted from healthy and rotifer infested cultures of Microchloropsis salina. After 48 hours of algal growth, marine rotifers, Brachionus plicatilis, were added to the algae cultures and volatile organic compounds (VOC) were sampled from the headspace using SPME fibers. A GC-MS approach was used in an untargeted analysis of VOCs, followed by preliminary identification. The addition of B. plicatilis to healthy cultures of M. salina resulted in decreased algal cell numbers, relative to uninfected controls, and generated trans-β-ionone and β-cyclocitral, which were attributed to carotenoid degradation. The abundances of the carotenoid-derived VOCs increased with rotifer consumption of algae. Our results indicate that specific VOCs released by infected algae cultures may be early indicators for impending pond crashes, providing a useful tool to monitor algal biomass production and pond crash prevention.

This study provides an overview of the coupled high-resolution Version 1 of the Energy Exascale Earth System Model (E3SMv1) and documents the characteristics of a 50-year-long high-resolution control simulation with time-invariant 1950 forcings following the HighResMIP protocol. In terms of global root-mean-squared error metrics, this high-resolution simulation is generally superior to results from the low-resolution configuration of E3SMv1 (due to resolution, tuning changes, and possibly initialization procedure) and compares favorably to models in the CMIP5 ensemble. Ocean and sea ice simulation is particularly improved, due to better resolution of bathymetry, the ability to capture more variability and extremes in winds and currents, and the ability to resolve mesoscale ocean eddies. The largest improvement in this regard is an ice-free Labrador Sea, which is a major problem at low resolution. Interestingly, several features found to improve with resolution in previous studies are insensitive to resolution or even degrade in E3SMv1. Most notable in this regard are warm bias and associated stratocumulus deficiency in eastern subtropical oceans and lack of improvement in El Niño. Another major finding of this study is that resolution increase had negligible impact on climate sensitivity (measured by net feedback determined through uniform +4K prescribed sea surface temperature increase) and aerosol sensitivity. Cloud response to resolution increase consisted of very minor decrease at all levels. Large-scale patterns of precipitation bias were also relatively unaffected by grid spacing.

When designing or analyzing a mechanical system, energy quantities provide insight into the severity of shock and vibration environments; however, the energy methods in the literature do not address localized behavior because energy quantities are usually computed for an entire structure. The main objective of this paper is to show how to compute the energy in the components of a mechanical system. The motivation for this work is that most systems fail functionally due to component failure, not because the primary structure was overloaded, and the ability to easily compute the spatial distribution of energy helps identify failure sensitive components. The quantity of interest is input energy. That input energy can be decoupled modally is well known. What is less appreciated is that input energy can be computed at the component level exactly, using the component effective modal mass. We show the steady state input energy can be decomposed both spatially and modally and computed using input power spectra. A numerical example illustrates the spatial and modal decomposition of input energy and its utility in identifying components at risk of damage in random vibration and shock environments. Our work shows that the modal properties of the structure and the spectral content of the input must be considered together to assess damage risk. Because input energy includes absorbed energy as well as relative kinetic energy and dissipated energy, it is the recommended energy quantity for assessing the severity for both random vibration and shock environments on a structure.

Subsidence monitoring is a crucial component to understanding cavern integrity of salt storage caverns. This report looks at the historical and current subsidence monitoring program and includes interpretation of the data from the West Hackberry Strategic Petroleum Reserve and LA Storage sites. Given data from current level-and-rod surveys, GPS, and tiltmeter, we do not believe there are any structural integrity issues at the West Hackberry DOE and LA Storage sites.

Sandia National Laboratories (also known as Sandia Labs) is a Government owned contractor operated facility. Sandia's mission is to develop advanced technologies to ensure global peace. The laboratory first began in 1945 as a division of Los Alamos National Laboratory and did not become its own laboratory until 1948. The labs was a descendant of the Manhattan Project and about 20 years later, Sandia National Laboratory became part of the Department of Energy (DOE) laboratories.

Modeling and observations suggest that Thwaites Glacier, West Antarctica, has begun unstable retreat. Concurrently, oceanographic observations have revealed substantial multiyear variability in the temperature of the ocean water driving retreat through melting of the ice shelf that restrains inland glacier flow. Using an ensemble of 72 ice-sheet model simulations that include an idealized representation of ocean temperature variability, we find that variable ice-shelf melting causes delays in grounding line retreat, mass loss, and sea level contribution relative to steady forcing. Modeled delays are up to 43 years after 500 years of simulation, corresponding to a 10% reduction in glacier mass loss. Delays are primarily caused by asymmetric melt forcing in the presence of variability. For the “warm cavity” conditions beneath Thwaites Ice Shelf, increases in access of warm, deeper water are unable to raise water temperatures in the cavity by much, whereas increases in access of significantly colder, shallow water reduce cavity water temperatures substantially. This leads to lowered mean melt rates under variable ocean temperature forcing. Additionally, about one quarter of the mass loss delay is caused by a nonlinear ice dynamic response to varying ice-shelf thinning rate, which is amplified during the initial phases of unstable, bed-topography-driven retreat. Mass loss rates under variability differ by up to 50% from ensemble mean values at any given time. Our results underscore the need for taking climate variability into account when modeling ice sheet evolution and for continued efforts toward the coupling of ice sheet models to ocean and climate models.

In this paper, we report a direct imaging of narrow-band super Planckian thermal radiation in the far field, emitted from a resonant-cavity/tungsten photonic crystal (cavity/W-PC). A spectroscopic study of the cavity/W-PC shows a distinct resonant peak at λ ∼ 1.7 μm. Furthermore, an infrared CCD camera was used to record radiation image of the cavity/W-PC and a carbon-nanotube (CNT) black reference at λ ∼ 1.7 μm emitted from the same sample. The recorded image displays a higher brightness emitted from the cavity/W-PC region than from the blackbody region for all temperatures tested, T = 530-650 K. This observation is in sharp contrast to the common understanding of equilibrium thermal radiation, namely, a blackbody has a unit absorptance, a unity emittance and should emits the strongest radiation. Since the image was taken from the same sample and the temperature difference across the W-PC/ CNT boundary is less than 0.1 K, the observed image contrast gives a truly convincing evidence of super Planckian behavior in our sample. The discovery of a super-intense, narrow band radiation from a heated W-PC could open up a new door for realizing narrow band infrared emitters. The W-PC filament could also be very useful for efficient energy applications such as thermo-photovoltaics, waste heat recycling and radiative cooling.

Charge noise can be detrimental to the operation of quantum dot (QD) based semiconductor qubits. We study the low-frequency charge noise by charge offset drift measurements for Si-MOS devices with intentionally implanted donors near the QDs. We show that the MOS system exhibits non-equilibrium drift characteristics, in the form of transients and discrete jumps, that are not dependent on the properties of the donor implants. The equilibrium charge noise indicates a 1/f noise dependence, and a noise strength as low as 1μeV/Hz, comparable to that reported in more model GaAs and Si/SiGe systems (which have also not been implanted). We demonstrate that implanted qubits, therefore, can be fabricated without detrimental effects on long-term drift or 1/f noise for devices with less than 50 implanted donors near the qubit.

The domain-wall (DW)-magnetic tunnel junction (MTJ) device implements universal Boolean logic in a manner that is naturally compact and cascadable. However, an evaluation of the energy efficiency of this emerging technology for standard logic applications is still lacking. In this article, we use a previously developed compact model to construct and benchmark a 32-bit adder entirely from DW-MTJ devices that communicates with DW-MTJ registers. The results of this large-scale design and simulation indicate that while the energy cost of systems driven by spin-Transfer torque (STT) DW motion is significantly higher than previously predicted, the same concept using spin-orbit torque (SOT) switching benefits from an improvement in the energy per operation by multiple orders of magnitude, attaining competitive energy values relative to a comparable CMOS subprocessor component. This result clarifies the path toward practical implementations of an all-magnetic processor system.

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We present an approach to uncoupling the pair of transient governing equations used in electrokinetics (i.e., streaming potential and electroosmosis). This approach allows for the solution of two uncoupled "intermediate" equations, then the physical solution is found by recombination of these intermediate potentials through a matrix multiplication. We present numerically stable expressions for the coefficients, and an example showing electrokinetics arising from pumping a fully penetrating well in a confined aquifer, surrounded by insulating aquicludes. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. (SAND2019-8712 A)

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