Publications

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This project plan gives a high-level description of the US Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Disposition (SFWD) campaign in situ borehole heater test project being planned for the Waste Isolation Pilot Plant (WIPP) site This plan provides an overview of the schedule and responsibilities of the parties involved. This project is a collaborative effort by Sandia, Los Alamos, and Lawrence Berkeley National Laboratories to execute a series of small-diameter borehole heater tests in salt for the DOE-NE SFWD campaign. Design of a heater test in salt at WIPP has evolved over several years. The current design was completed in fiscal year 2017 (FY17), an equipment shakedown experiment is underway in April FY18, and the test implementation will begin in summer of FY18. The project comprises a suite of modular tests, which consist of a group of nearby boreholes in the wall of drifts at WIPP. Each test is centered around a packer-isolated heated borehole (5" diameter) containing equipment for water-vapor collection and brine sampling, surrounded by smaller-diameter (2" diameter) satellite observation boreholes. Observation boreholes will contain temperature sensors, tracer release points, electrical resistivity tomography (ERT) sensors, fiber optic sensing, and acoustic emission (AE) measurements, and sonic velocity sources and sensors. These satellite boreholes will also be used for plugging/sealing tests. The first two tests to be implemented will have the packer-isolated borehole heated to 120°C, with one observation borehole used to monitor changes. Follow-on tests will be designed using information gathered from the first two tests, will be conducted at other temperatures, will use multiple observation boreholes, and may include other measurement types and test designs.

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Security vulnerabilities such as Meltdown and Spectre demonstrate how chip complexity grew faster than our ability to manage unintended consequences. Attention to security from the outset should be part of the rememdy, yet complexity must be controlled at a more fundamental level.

The earliest stages of soot formation in flames are believed to involve the formation of small, nanoscale clusters of polycyclic aromatic hydrocarbon molecules. The structure of these clusters is still highly uncertain, however, impeding the construction of quantitative models of soot inception and growth. To provide insight into the structure of incipient soot, we produced nanoclusters of hydrocarbon molecules by annealing coronene films deposited on Pt(111), and examined them with scanning tunneling microcopy. We find that clusters containing ∼20–100 molecules, are disordered agglomerations of stacks that are ∼5–6 molecules tall. These structures are quite distinct from crystalline coronene, but bear a striking resemblance to recently proposed models for the equilibrium structure of similarly-sized clusters that are assumed to initiate soot formation. In contrast to mature soot, the surfaces of these clusters contain very few molecules with graphitic planes oriented parallel to the surface.

This research uses the acoustic coda phase delay method to estimate relative changes in air temperature between explosions with varying event masses and heights of burst. It also places a bound on source-receiver distance for the method. Previous studies used events with different shapes, height of bursts, and masses and recorded the acoustic codas at source-receiver distances less than 1 km. This research further explores the method using explosions that differ in mass (by up to an order of magnitude) and are placed at varying heights. Source-receiver distances also cover an area out to 7 km. Relative air temperature change estimates are compared to complementary meteorological observations. Results show that two explosions that differ by an order of magnitude cannot be used with this method because their propagation times in the near field and their fundamental frequencies are different. These differences are expressed as inaccuracies in the relative air temperature change estimates. An order of magnitude difference in mass is also shown to bias estimates higher. Small differences in height of burst do not affect the accuracy of the method. An upper bound of 1 km on source-receiver distance is provided based on the standard deviation characteristics of the estimates.

Hydrologic exchange flux (HEF) is an important hydrologic component in river corridors that includes both bidirectional (hyporheic) and unidirectional (gaining/losing) surface water-groundwater exchanges. Quantifying HEF rates in a large regulated river is difficult due to the large spatial domains, complexity of geomorphologic features and subsurface properties, and the great stage variations created by dam operations at multiple time scales. In this study, we developed a method that combined numerical modeling and field measurements for estimating HEF rates across the riverbed in a 7 km long reach of the highly regulated Columbia River. A high-resolution computational fluid dynamics (CFD) modeling framework was developed and validated by field measurements and other modeling results to characterize the HEF dynamics across the riverbed. We found that about 85% of the time from 2008 to 2014 the river was losing water with an annual average net HEF rates across the riverbed (Qz) of −2.3 m3 s−1 (negative indicating downwelling). June was the only month that the river gained water, with monthly averaged Qz of 0.8 m3 s−1. We also found that the daily dam operations increased the hourly gross gaining and losing rate over an average year of 8% and 2%, respectively. By investigating the HEF feedbacks at various time scales, we suggest that the dam operations could reduce the HEF at seasonal time scale by decreasing the seasonal flow variations, while also enhance the HEF at subdaily time scale by generating high-frequency discharge variations. These changes could generate significant impacts on biogeochemical processes in the hyporheic zone.

A unified physics-based model of electron transport in metal-insulator-metal (MIM) systems is presented. In this model, transport through metal-oxide interfaces occurs by electron tunneling between the metal electrodes and oxide defect states. Transport in the oxide bulk is dominated by hopping, modeled as a series of tunneling events that alter the electron occupancy of defect states. Electron transport in the oxide conduction band is treated by the drift–diffusion formalism and defect chemistry reactions link all the various transport mechanisms. It is shown that the current-limiting effect of the interface band offsets is a function of the defect vacancy concentration. These results provide insight into the underlying physical mechanisms of leakage currents in oxide-based capacitors and steady-state electron transport in resistive random access memory (ReRAM) MIM devices. Finally, an explanation of ReRAM bipolar switching behavior based on these results is proposed.

The purpose of the project was to facilitate joint Sandia/ExxonMobil collaborative research activities of mutual interest in the area of atomistic simulation of materials behavior using Sandia's LAMMPS molecular dynarnics software package. Work began in late 2013 and ended in early 2017. Initially, the main focus was on the development of a spatially-dependent hybridization capability for interatomic potentials in LAMMPS. Later, attention shifted to modeling and simulation of phase transformation kinetics in iron. Other research activities involved a variety of LAMMPS functionality, including interatomic potentials, Monte Carlo sampling, and energy minimization.

Sandia National Laboratories (Sandia) and Carestream Health, Inc. (CHI) collaborated on the development of a grating-based X-ray Phase Contrast Imaging (XPCI) system at Sandia. The purpose of the agreement was to share research and development knowledge, resources, and capabilities in the advancement of XPCI that would be mutually beneficial to CHI and Sandia. In the course of this agreement Sandia designed and built an XPCI apparatus including opto-mechanical design, source and x-ray detector selection, software interface, hardware assembly, and system alignment. Data acquisition and image reconstruction were demonstrated at both CHI and Sandia. XPCI is a new imaging modality that enables non-destructive inspection of low density materials not previously possible with conventional x-ray. The technique fills a capability gap valuable to both the industry partner in their technical portfolio and in national security applications important to Sandia and the DOE mission space.

The major goal of this project was to develop an ionization-based detector that could be integrated into the portable gas chromatography systems currently produced by Defiant Technologies. This new detector would allow Defiant to analyze a broader range of analytes and enter new markets. There was also an interest in testing the new ionization source in an ion mobility spectrometer (IMS) that is produced by Sandia National Laboratories. Not only could this eliminate the need for a radioactive material in the IMS, it would offer Defiant the opportunity to add a whole new product line to their chemical analysis systems. Significant progress was made in the development of a thermionic ionization source (TIS) and detector. Using a MEMs heater was an attractive concept, but it proved to be an unfruitful approach because of the fragility of the devices at elevated temperatures. A rugged alternative heater was developed using nichrome wire and alumina tubes. These heaters are simple to make, and, for low quantity production, will be considerably cheaper to construct than MEMs devices. This work has provided a firm basis for follow-on projects. There is now a solid concept for constructing heater elements where, prior to this work, there was only the hope that MEMs heaters would work. In addition, the electrometer that was developed works better than the commercial rack-mounted system that was originally used in this study. Overcoming these two obstacles provides a clear technical approach for product development. There will be follow on efforts at Defiant Technologies to refine the development of the thermal ionization detector. Designs are being made to combine the TIS and electrometer electronics into a single package with a simple-to-replace TIS element. Further work will also focus on integrating this new detector into portable gas chromatography products and testing to optimize the performance.

The purpose of this PTS was to conduct work with ASU, specifically to further develop Spectroradiometricbased technology that has potential to function as early warning of the active presence of predators and pathogens in outdoor algal ponds. Chlorella sorokiniana and the pathogen, Vampirovibrio chlorellavorus were selected for investigation because they had previously been implicated in several pond crashes at ASU's Arizona Center for Algal Technology and Innovation (AzCATI). Sandia conducted small-scale laboratory experiments comparing control and infected cultures of C. sorokiniana. Spectrally-resolved reflectivity data, as well as optical density, and pulse amplitude modulated fluorescence (PAM) were collected and analyzed to identify the spectral response of active V. chlorellavorus infection. The results of this limited, yet robust, experiment confirmed the initial hypothesis that signature V. chlorellavorus infection of C. sorokiniana could be identified based on the presence of a chlorophyll metabolites generated when the algal chlorophyll is degraded by the pathogen.

The purpose of this PTS was for Sandia National Laboratories (Sandia) to conduct collaborative research with Arizona Board of Regents for and on behalf of Arizona State University (ASU) to further develop algae growth and computational fluid dynamics (CFO) models that can predict and optimize pond design and cultivation methods to improve algal yield in outdoor algal ponds.

The goal of the DOE OE ESS Safety Roadmap is to foster confidence in the safety and reliability of energy storage systems.

This memo consists of a manuscript draft that was never published, but was prepared in 2002 at Sandia. It is used as a user-guide for running simulations of laser welding with Sandia's Goma 6.0 software.

This monthly report is intended to communicate the status of North Slope ARM facilities managed by Sandia National Labs. Report covers budget, safety, instrument status, and North Slope facilities.

The SNL ATDM Data and Visualization project is developing data management software to improve how applications store and exchange large datasets efficiently on Exascale platforms. The data portion of this project is composed of two related efforts: (1) production work focused on improving Sandia's IOSS library for mesh datasets and (2) research work focused on developing new communication software named FAODEL that enables applications in a workflow to exchange data more efficiently.

Materials aging is a high-consequence failure mode in electronic systems. Such mechanisms can degrade the electrical properties of connectors, relays, wire bonds, and other interconnections. Lost performance will impact, not only that of the device, but also the function and reliability of next-level assemblies and the weapons system as a whole. The detections of changes to materials surfaces at the nanometer-scale resolution, provides a means to identify aging processes at their early stages before they manifest into latent failures that affect system-level performance and reliability. Diffusion will be studied on thin films that undergo accelerated aging using the nanometer scale characterization technique of Frequency Modulated Kelvin Probe Force Microscopy (FM-KPFM). The KPFM provides a relatively easy, non-destructive methodology that does not require high-vacuum facilities to obtain nanometer spatial resolution of surface chemistry changes. The KPFM method can provide the means to measure surface, and near-surface, elemental concentrations that allow the determination of diffusion rate kinetics. These attributes will be illustrated by assessing diffusion in a thin film couple. Validation data will obtained from traditional techniques: (a) Auger electron spectroscopy (AES), x-ray fluorescence (XRF), and xray photoelectron spectroscopy (XPS).

Wind energy development in the United States has been steadily growing over the past decade. This trend has resulted in the expansion of wind energy into areas that have a good wind resource but may have other deployment barriers being looked at more closely. One such barrier is that of the potential impact that wind turbines pose to radar systems. Wind turbines located within the line-of-sight of radar systems can cause clutter and interference and can result in performance degradation. Mitigation of any interference that wind turbines have on radar systems begins with the understanding of the potential those impacts to radar systems through modeling and simulation. The intent of this document is to catalog and provide the reader with a list of the modeling and simulation capabilities along with enabling databases for wind turbine — radar interference and related issues that are currently in use in various government agencies as well as those tools that are available to the public for free or fee. A brief description of the tool is given along with other pertinent characteristics of the tool including the owner, developers, user, classification, status, and the point-of-contact. This document does not provide an exhaustive description of the tools' capabilities nor does it include tools that were developed privately.

RAZORBACK is a research reactor transient analysis computer code designed to simulate the operation of a research reactor (such as Sandia National Laboratories' Annular Core Research Reactor (ACRR)). The code provides a coupled numerical solution of the point reactor kinetics equations, the energy conservation equation for fuel element heat transfer, the equation of motion for fuel element thermal expansion, and the mass, momentum, and energy conservation equations for the water cooling of the fuel elements. This Software Design and Development Report describes how the code is designed to implement the functional requirements established in the Software Requirements Specification document for RAZORBACK. The description presents the physical model equations used in the design, and how these equations are set up to be solved numerically. This report also provides an evaluation of how the software design meets each of the functional requirements.

AC/DC Adapters model# JCY-1250 that were received with LED light strip kits have been electrically altered and reconfigured with wiring of a lesser grade that is not capable of carrying the anticipated amperage and voltage for the items use. The two items received from TBI Corp per the DOE definition are considered suspect/counterfeit.

This document outlines the preliminary analysis of the 2D Challenge 2.0 images. They currently consist of a new Star pattern series of images created by Benoît Blaysat. Another image set may be created by Phillip with an unknown displacement field based on Sample 14 from the 2D Challenge 1.0.

This document outlines the preliminary analysis of the Stereo-DIC Challenge Plate translation test images.

Phase noise is the instability of an oscillator/clock signal source with respect to frequency and phase. It is an undesirable but unavoidable characteristic that adversely affects the performance of range-Doppler radar systems, including Synthetic Aperture Radar (SAR) and Ground-Moving Target Indicator (GMTI) radar. In short, phase noise effects cannot be neglected in high performance radar designs, will limit performance, and should influence design approaches.

The SNL ATDM Data and Visualization work consolidates existing ATDM activities in scalable data management and visualization. Part of the responsibilities of the SNL ATDM Data and Visualization Project is the maintenance and development of visualization resources for ATDM applications on Exascale platforms. The ATDM Scalable Visualization project provides visualization and analysis required to satisfy the needs of the ASC/ATDM applications on next-generation, many-core platforms. This involves many activities including the re-engineering of visualization algorithms, services, and tools that enable ASC customers to carry out data analysis on ASC systems and ACES platforms. Current tools include scalable data analysis software released open source through ParaView, VTK, and Catalyst. We are also both leveraging and contributing to VTK-m, a many-core visualization library, to satisfy our visualization needs on advanced architectures. The scope of the Scalable Visualization under ATDM at SNL is R&D for the programming model and implementation of visualization code for ASC/ATDM projects and ASC/ATDM application support.

This monthly report is intended to communicate the status of North Slope ARM facilities managed by Sandia National Labs and includes: budget, safety, instrument status, and North Slope facilities.

Accelerated testing is a form of testing commonly employed in industry, especially at Sandia National Laboratories, in order to extract information about product lifetime behavior that cannot be acquired under normal operating conditions due to the extensive durations of the intended life- times. As of the writing of this report, there is no known guideline for the design of accelerated tests at the laboratories and yet there is an entire field in the statistical literature on the optimal design of accelerated tests covering a wide range of limitations and constraints available for reference. A potential roadblock to incorporating this knowledge is the common difficulty at Sandia of having severely limited data available for such testing. Nearly all of the methodology presented in the statistical literature is based on asymptotic or large-sample theory and so may not be appropriate for the testing conditions present at Sandia. This report investigates optimal accelerated test plans derived based on small-sample or exact methodology for both a basic test setting as well as a more realistic setting and compares the resulting test plans to those derived based on the large- sample methodology from the literature. It is shown that the large-sample test plans are actually quite robust to the presence of limited data and are generally more flexible than the small-sample test plans.

This report presents the questions and responses to a nationwide survey of U.S. residents taken May 2017. The focus of the 2017 survey is public perceptions on (1) nuclear energy and new nuclear technology, such as small modular reactors; (2) the risks and benefits of nuclear energy; (3) different options for managing spent nuclear fuel (SNF); and (4) the role of individuals, organizations and elected officials in locating SNF facilities. Highlights of survey results related to nuclear energy found the U.S. public (1) wants nuclear energy to continue to contribute 20% of total electrical power produced for the next 20 years; (2) is more supportive of adding new reactors at existing sites than at new sites; and (3) is more supportive of small modular reactors than traditional reactors. Highlights related to risks and benefits of nuclear energy include (1) the public believes that terrorist attacks are the greatest threat and that energy independence is the greatest benefit; (2) 56% of the public believes that nuclear power has both high benefit and high risk; (3) the 2011 accident at the Fukushima nuclear facility continues to negatively influence the perceived benefits and risks of nuclear energy except for those who perceive nuclear power as low risk and high benefit; (4) building new reactors is supported by those who perceive nuclear power as low risk and high benefit, and opposed by those who perceive it as high risk and low benefit. Highlights related to SNF management options include (1) support remains higher for permanent disposal than either consolidated interim storage or continued on-site storage; (2) support for private initiatives for interim storage in New Mexico and Texas are higher than generic storage and disposal options; (3) the general public is more likely to increase support if a majority of the local and state residents support an SNF facility. Highlights related to the role of individuals, organizations, and elected officials include (1) 54% of the public agrees that if an SNF facility is deemed safe by regulators, political considerations should not derail the location; (2) 47% of the US public agrees that non-governmental organizations should be able to provide input to locating an SNF facility; (3) 36% of the public believes that the federal government should lead siting of an SNF facility while 25% believes private companies should lead; (4) 81% of the public believes local residents and farmers/ranchers should have a say in the final decision on locating a SNF facility and 56% believe that they should have veto power; and (5) only 27% of the public believes the state governor should have a say and veto power.

We investigate the electric penetration case of the first principles multipole-based cable braid electromagnetic penetration model reported in the Progress in Electromagnetics Research B 66, 63-89 (2016). We first analyze the case of a 1-D array of wires: this is a problem which is interesting on its own, and we report its modeling based on a multipole-conformal mapping expansion and extension by means of Laplace solutions in bipolar coordinates. We then compare the elastance (inverse of capacitance) results from our first principles cable braid electromagnetic penetration model to that obtained using the multipole-conformal mapping bipolar solution. These results are found in a good agreement up to a radius to half spacing ratio of 0.6, demonstrating a robustness needed for many commercial cables. We then analyze realistic cable implementations without dielectrics and compare the results from our first principles braid electromagnetic penetration model to the semiempirical results reported by Kley in the IEEE Transactions on Electromagnetic Compatibility 35, 1-9 (1993). Although we find results on the same order of magnitude of Kley's results, the full dependence on the actual cable geometry is accounted for only in our proposed multipole model which, in addition, enables us to treat perturbations from those commercial cables measured.

Harsh environments pose materials durability challenges across the automotive, aerospace, and manufacturing sectors, and beyond. While amorphous carbon materials have been used as coatings in many environmentally-demanding applications owing to their unique mechanical, electrical, and optical properties, their limited thermal stability and high reactivity in oxidizing environments have impeded their use in many technologies. Silicon- and oxygen-containing hydrogenated amorphous carbon (a-C:H:Si:O) films are promising for several applications because of their higher thermal stability and lower residual stress compared to hydrogenated amorphous carbon (a-C:H). However, an understanding of their superior thermo-oxidative stability compared to a-C:H is lacking, as it has been inhibited by the intrinsic challenge of characterizing an amorphous, multi-component material. Here, we show that introducing silicon and oxygen in a-C:H slightly enhances the thermal stability in vacuum, but tremendously increases the thermo-oxidative stability and the resistance to degradation upon exposure to the harsh conditions of low Earth orbit (LEO). The latter is demonstrated by having mounted samples of a-C:H:Si:O on the exterior of the International Space Station via the Materials International Space Station (MISSE) mission 7b. Exposing lightly-doped a-C:H:Si:O to elevated temperatures under aerobic conditions or to LEO causes carbon volatilization in the near-surface region, producing a silica surface layer that protects the underlying carbon from further removal. These findings provide a novel physically-based understanding of the superior stability of a-C:H:Si:O in harsh environments compared to a-C:H.

A new model for determining band gaps for elastic wave propagation in a periodic composite beam structure is developed using a non-classical Bernoulli–Euler beam model that incorporates the microstructure, surface energy and rotational inertia effects. The Bloch theorem and transfer matrix method for periodic structures are employed in the formulation. The new model reduces to the classical elasticity-based model when both the microstructure and surface energy effects are not considered. The band gaps predicted by the new model depend on the microstructure and surface elasticity of each constituent material, the unit cell size, the rotational inertia, and the volume fraction. To quantitatively illustrate the effects of these factors, a parametric study is conducted. The numerical results reveal that the band gap predicted by the current non-classical model is always larger than that predicted by the classical model when the beam thickness is very small, but the difference is diminishing as the thickness becomes large. Also, it is found that the first frequency for producing the band gap and the band gap size decrease with the increase of the unit cell length according to both the current and classical models. In addition, it is observed that the effect of the rotational inertia is larger when the exciting frequency is higher and the unit cell length is smaller. Furthermore, it is seen that the volume fraction has a significant effect on the band gap size, and large band gaps can be obtained by tailoring the volume fraction and material parameters.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilities come closer to production level.

Charge-transfer materials based on the self-assembly of aromatic donor–acceptor complexes enable a modular organic-synthetic approach to develop and fine-tune electronic and optical properties, and thus these material systems stand to impact a wide range of technologies. Through laser-induction of temperature gradients, in this paper, user-defined patterning of strongly dichroic and piezoelectric organic thin films composed of donor–acceptor columnar liquid crystals is shown. Finally, fine, reversible control over isotropic versus anisotropic regions in thin films is demonstrated, enabling noncontact writing/rewriting of micropolarizers, bar codes, and charge-transfer based devices.

We introduce quiho, a framework for profiling application performance that can be used in automated performance regression tests. quiho profiles an application by applying sensitivity analysis, in particular statistical regression analysis (SRA), using application-independent performance feature vectors that characterize the performance of machines. The result of the SRA, feature importance specifically, is used as a proxy to identify hardware and low-level system software behavior. The relative importance of these features serve as a performance profile of an application (termed inferred resource utilization profile or IRUP), which is used to automatically validate performance behavior across multiple revisions of an application's code base without having to instrument code or obtain performance counters. We demonstrate that quiho can successfully discover performance regressions by showing its effectiveness in profiling application performance for synthetically introduced regressions as well as those found in real-world applications.

Morphology and microstructure of organic explosive films formed using physical vapor deposition (PVD) processes strongly depends on local surface temperature during deposition. Currently, there is no accurate means of quantifying the local surface temperature during PVD processes in the deposition chambers. This study focuses on using a multiphysics computational fluid dynamics tool, STARCCM+, to simulate pentaerythritol tetranitrate (PETN) deposition. The PETN vapor and solid phase were simulated using the volume of fluid method and its deposition in the vacuum chamber on spinning silicon wafers was modeled. The model also included the spinning copper cooling block where the wafers are placed along with the chiller operating with forced convection refrigerant. Implicit time-dependent simulations in two- and three-dimensional were performed to derive insights in the governing physics for PETN thin film formation. PETN is deposited at the rate of 14 nm/s at 142.9 °C on a wafer with an initial temperature of 22 °C. The deposition of PETN on the wafers was calculated at an assumed heat transfer coefficient (HTC) of 400 W/m² K. This HTC proved to be the most sensitive parameter in determining the local surface temperature during deposition. Previous experimental work found noticeable microstructural changes with 0.5 mm fused silica wafers in place of silicon during the PETN deposition. This work showed that fused silica slows initial wafer cool down and results in ~10 °C difference for the surface temperature at 500 μm PETN film thickness. It was also found that the deposition surface temperature is insensitive to the cooling power of the copper block due to the copper block's very large heat capacity and thermal conductivity relative to the heat input from the PVD process. Future work should incorporate the addition of local stress during PETN deposition. Lastly, based on simulation results, it is also recommended to investigate the impact of wafer surface energy on the PETN microstructure and morphology formation.

Aided by its 17 National Laboratories, the U.S. Department of Energy (DOE) carries out a mission to, ‘‘ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions,’’ in arenas ranging from the digital information omniverse and electric power grid to the nuclear cycle. Although DOE research, development, and applications (RD&A) have traditionally drawn from the physical sciences, a complementary understanding is emerging in the lab complex of the human dimension.

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The purpose of this memo is to highlight the findings of an extensive literature survey and interviews with experts on the behavior of polymers in super-critical CO2 energy conversion systems that demonstrate foremost that there are critical knowledge gaps in this area that need to be addressed to improve design, reliability and lifetimes of system components. There are two brief discussions presented here: 1. SCO2 effects in polymers and associated mechanisms of failure, and 2. Summary of knowledge gaps identified in polymer/SCO2 interactions and science-based R&D to address the same.

Here, we present experimental results on axially magnetized (B_z = 0.5 – 2.0 T), thin-foil (400 nm-thick) cylindrical liner-plasmas driven with ~600 kA by the Michigan Accelerator for Inductive Z-Pinch Experiments, which is a linear transformer driver at the University of Michigan. We show that: (1) the applied axial magnetic field, irrespective of its direction (e.g., parallel or anti-parallel to the flow of current), reduces the instability amplitude for pure magnetohydrodynamic (MHD) modes [defined as modes devoid of the acceleration-driven magneto-Rayleigh-Taylor (MRT) instability]; (2) axially magnetized, imploding liners (where MHD modes couple to MRT) generate m = 1 or m = 2 helical modes that persist from the implosion to the subsequent explosion stage; (3) the merging of instability structures is a mechanism that enables the appearance of an exponential instability growth rate for a longer than expected time-period; and (4) an inverse cascade in both the axial and azimuthal wavenumbers, k and m, may be responsible for the final m = 2 helical structure observed in our experiments. Laslty, these experiments are particularly relevant to the magnetized liner inertial fusion program pursued at Sandia National Laboratories, where helical instabilities have been observed.

Dynamic material properties experiments provide access to the most extreme temperatures and pressures attainable in a laboratory setting; the data from these experiments are often used to improve our understanding of material models at these extreme conditions. We apply Bayesian model calibration to dynamic material property applications where the experimental output is a function: velocity over time. This framework can accommodate more uncertainties and facilitate analysis of new types of experiments relative to techniques traditionally used to analyse dynamic material experiments. However, implementation of Bayesian model calibration requires more sophisticated statistical techniques, because of the functional nature of the output as well as parameter and model discrepancy identifiability. We propose a novel Bayesian model calibration process to simplify and improve the estimation of the material property calibration parameters. Specifically, we propose scaling the likelihood function by an effective sample size rather than modelling the auto–correlation function to accommodate the functional output. Additionally, we propose sensitivity analyses by using the notion of 'modularization' to assess the effect of experiment–specific nuisance input parameters on estimates of the physical parameters. Furthermore, the Bayesian model calibration framework proposed is applied to dynamic compression of tantalum to extreme pressures, and we conclude that the procedure results in simple, fast and valid inferences on the material properties for tantalum.

The formation and closure of aqueous pores in lipid bilayers is a key step in various biophysical processes. Large pores are well described by classical nucleation theory, but the free-energy landscape of small, biologically relevant pores has remained largely unexplored. The existence of small and metastable "prepores" was hypothesized decades ago from electroporation experiments, but resolving metastable prepores from theoretical models remained challenging. Using two complementary methods - atomistic simulations and self-consistent field theory of a minimal lipid model - we determine the parameters for which metastable prepores occur in lipid membranes. Both methods consistently suggest that pore metastability depends on the relative volume ratio between the lipid head group and lipid tails: lipids with a larger head-group volume fraction (or shorter saturated tails) form metastable prepores, whereas lipids with a smaller head-group volume fraction (or longer unsaturated tails) form unstable prepores.

We have developed a physics-based transmission-line-circuit model of the Z pulsed-power accelerator. The 33-m-diameter Z machine generates a peak electrical power as high as 85 TW, and delivers as much as 25 MA to a physics load. The circuit model is used to design and analyze experiments conducted on Z. The model consists of 36 networks of transmission-line-circuit elements and resistors that represent each of Zs 36 modules. The model of each module includes a Marx generator, intermediate-energy-storage capacitor, laser-triggered gas switch, pulse-forming line, self-break water switches, and tri-plate transmission lines. The circuit model also includes elements that represent Zs water convolute, vacuum insulator stack, four parallel outer magnetically insulated vacuum transmission lines (MITLs), double-post-hole vacuum convolute, inner vacuum MITL, and physics load. Within the vacuum-transmission-line system the model conducts analytic calculations of current loss. To calculate the loss, the model simulates the following processes: (i) electron emission from MITL cathode surfaces wherever an electric-field threshold has been exceeded; (ii) electron loss in the MITLs before magnetic insulation has been established; (iii) flow of electrons emitted by the outer-MITL cathodes after insulation has been established; (iv) closure of MITL anode-cathode (AK) gaps due to expansion of cathode plasma; (v) energy loss to MITL conductors operated at high lineal current densities; (vi) heating of MITL-anode surfaces due to conduction current and deposition of electron kinetic energy; (vii) negative-space-charge-enhanced ion emission from MITL anode surfaces wherever an anode-surface-temperature threshold has been exceeded; and (viii) closure of MITL AK gaps due to expansion of anode plasma. The circuit model is expected to be most accurate when the fractional current loss is small. We have performed circuit simulations of 52 Z experiments conducted with a variety of accelerator configurations and load-impedance time histories. For these experiments, the apparent fractional current loss varies from 0% to 20%. Results of the circuit simulations agree with data acquired on 52 shots to within 2%.

The (EHS) Health Action Plan initiative targets the key health risks identified through the 8-15-80 model by engaging employees to change their own healthcare story. (EHS) identified the most prevalent of the health risks amongst our population through Health Risk Assessment (HRA) and used that data to build Health Action Plans. Our 2017 Health Action Plans addressed inadequate sleep, increasing energy, stress, weight management, physical inactivity, hypertension, dyslipidemia, managing and preventing diabetes, managing low back pain, allergies & asthma, digestive health, tobacco use, and living well or maintaining low risk for those individuals who do not have a chronic condition to manage. These plans connect employees with our onsite registered dietitians, fitness professionals, health coaches, physical therapists and physicians as appropriate. In addition to addressing the physical aspects of health, the plans also emphasized pre/post-assessments to encourage building behavioral and emotional skills that promote health and facilitate lifestyle changes over a minimum of three months - just one risk reduction or behavior change to make an impact on their Division as well as Sandia's overall risk levels and ultimately healthcare costs.

The (EHS) Health Action Plan initiative targets the key health risks identified through the 8-15-80 model by engaging employees to change their own healthcare story. (EHS) identified the most prevalent of the health risks amongst our population through Health Risk Assessment (HRA) and used that data to build Health Action Plans. Our 2017 Health Action Plans addressed inadequate sleep, increasing energy, stress, weight management, physical inactivity, hypertension, dyslipidemia, managing and preventing diabetes, managing low back pain, allergies & asthma, digestive health, tobacco use, and living well or maintaining low risk for those individuals who do not have a chronic condition to manage. These plans connect employees with our onsite registered dietitians, fitness professionals, health coaches, physical therapists and physicians as appropriate. In addition to addressing the physical aspects of health, the plans also emphasized pre/post-assessments to encourage building behavioral and emotional skills that promote health and facilitate lifestyle changes over a minimum of three months - just one risk reduction or behavior change to make an impact on their Division as well as Sandia's overall risk levels and ultimately healthcare costs.

Postdeposition CdCl2 treatment of polycrystalline CdTe is known to increase the photovoltaic device efficiency. However, the precise chemical, structural, and electronic changes that underpin this improvement are still debated. In this study, spectroscopic photoemission electron microscopy was used to spatially map the vacuum level and ionization energy of CdTe films, enabling the identification of electronic structure variations between grains and grain boundaries (GBs). In vacuo preparation and inert transfer of oxide-free CdTe surfaces isolated the separate effects of CdCl2 treatment and ambient oxygen exposure. Qualitatively, grain boundaries displayed lower work function and downward band bending relative to grain interiors, but only after air exposure of CdCl2-treated CdTe. Analysis of numerous space charge regions at grain boundaries showed an average depletion width of 290 nm and an average band bending magnitude of 70 meV, corresponding to a GB trap density of 1011 cm-2 and a net carrier density of 1015 cm-3. These results suggest that both CdCl2 treatment and oxygen exposure may be independently tuned to enhance the CdTe photovoltaic performance by engineering the interface and bulk electronic structure.

Optical communication systems increasingly require electrooptical modulators that deliver high modulation speeds across a large optical bandwidth with a small device footprint and a CMOS-compatible fabrication process. Although silicon photonic modulators based on transparent conducting oxides (TCOs) have shown promise for delivering on these requirements, modulation speeds to date have been limited. Here, we describe the design, fabrication, and performance of a fast, compact electroabsorption modulator based on TCOs. The modulator works by using bias voltage to increase the carrier density in the conducting oxide, which changes the permittivity and hence optical attenuation by almost 10 dB. Under bias, light is tightly confined to the conducting oxide layer through nonresonant epsilon-near-zero (ENZ) effects, which enable modulation over a broad range of wavelengths in the telecommunications band. Our approach features simple integration with passive silicon waveguides, the use of stable inorganic materials, and the ability to modulate both transverse electric and magnetic polarizations with the same device design. Using a 4-μm-long modulator and a drive voltage of 2 Vpp, we demonstrate digital modulation at rates of 2.5 Gb/s. We report broadband operation with a 6.5 dB extinction ratio across the 1530–1590 nm band and a 10 dB insertion loss. This work verifies that high-speed ENZ devices can be created using conducting oxide materials and paves the way for additional technology development that could have a broad impact on future optical communications systems.

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function as a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.

Here, we report on the results of theoretical and experimental studies of photoluminescense of silicon nanocrystals in the proximity to plasmonic modes of different types. In the studied samples, the type of plasmonic mode is determined by the filling ratio of a one-dimensional array of gold stripes which covers the thin film with silicon nanocrystals on a quartz substrate. We analyze the extinction, photoluminesce spectra and decay kinetics of silicon nanocrystals and show that the incident and emitted light is coupled to the corresponding plasmonic mode. We demonstrate the modification of the extinction and photoluminesce spectra under the transition from wide to narrow gold stripes. The experimental extinction and photoluminescense spectra are in good agreement with theoretical calculations performed by the rigorous coupled wave analysis. Finally, we study the contribution of individual silicon nanocrystals to the overall photoluminescense intensity, depending on their spacial position inside the structure.

Efficient lignin valorization could add more than 10-fold the value gained from burning it for energy and is critical for economic viability of future biorefineries. However, lignin-derived aromatics from biomass pretreatment are known to be potent fermentation inhibitors in microbial production of fuels and other value-added chemicals. In addition, isopropyl-β-D-1-thiogalactopyranoside and other inducers are routinely added into fermentation broth to induce the expression of pathway enzymes, which further adds to the overall process cost. An autoregulatory system that can diminish the aromatics' toxicity as well as be substrate-inducible can be the key for successful integration of lignin valorization into future lignocellulosic biorefineries. Toward that goal, in this study an autoregulatory system is demonstrated that alleviates the toxicity issue and eliminates the cost of an external inducer. Specifically, this system is composed of a catechol biosynthesis pathway coexpressed with an active aromatic transporter CouP under induction by a vanillin self-inducible promoter, ADH7, to effectively convert the ligninderived aromatics into value-added chemicals using Escherichia coli as a host. The constructed autoregulatory system can efficiently transport vanillin across the cell membrane and convert it to catechol. Compared with the system without CouP expression, the expression of catechol biosynthesis pathway with transporter CouP significantly improved the catechol yields about 30% and 40% under promoter pTrc and ADH7, respectively. This study demonstrated an aromaticinduced autoregulatory system that enabled conversion of ligninderived aromatics into catechol without the addition of any costly, external inducers, providing a promising and economically viable route for lignin valorization.

Single-photon detectors have achieved impressive performance and have led to a number of new scientific discoveries and technological applications. Existing models of photodetectors are semiclassical in that the field-matter interaction is treated perturbatively and time-separated from physical processes in the absorbing matter. An open question is whether a fully quantum detector, whereby the optical field, the optical absorption, and the amplification are considered as one quantum system, could have improved performance. Here we develop a theoretical model of such photodetectors and employ simulations to reveal the critical role played by quantum coherence and amplification backaction in dictating the performance. We show that coherence and backaction lead to trade-offs between detector metrics and also determine optimal system designs through control of the quantum-classical interface. Importantly, we establish the design parameters that result in a ideal photodetector with 100% efficiency, no dark counts, and minimal jitter, thus paving the route for next-generation detectors.

We study the enhancement of cooperativity in the atom-light interface near a nanophotonic waveguide for application to quantum nondemolition (QND) measurement of atomic spins. Here the cooperativity per atom is determined by the ratio between the measurement strength and the decoherence rate. Counterintuitively, we find that by placing the atoms at an azimuthal position where the guided probe mode has the lowest intensity, we increase the cooperativity. This arises because the QND measurement strength depends on the interference between the probe and scattered light guided into an orthogonal polarization mode, while the decoherence rate depends on the local intensity of the probe. Thus, by proper choice of geometry, the ratio of good-to-bad scattering can be strongly enhanced for highly anisotropic modes. We apply this to study spin squeezing resulting from QND measurement of spin projection noise via the Faraday effect in two nanophotonic geometries, a cylindrical nanofiber and a square waveguide. We find that, with about 2500 atoms and using realistic experimental parameters, ∼6.3 and ∼13 dB of squeezing can be achieved on the nanofiber and square waveguide, respectively.

Elastic and thermodynamic properties of negative thermal expansion (NTE) αα-ZrW2O8 have been calculated using PBEsol and PBE exchange-correlation functionals within the framework of density functional perturbation theory (DFPT). Measured elastic constants are reproduced within ~2% with PBEsol and 6% with PBE. The thermal evolution of the Grüneisen parameter computed within the quasi-harmonic approximation exhibits negative values below the Debye temperature, consistent with observation. The standard molar heat capacity is predicted to be C $O\atop{P}$=192.2 and 193.8 J mol^-1K^-1 with PBEsol and PBE, respectively. These results suggest superior accuracy of DFPT/PBEsol for studying the lattice dynamics, elasticity and thermodynamics of NTE materials.

Consortium for Advance Simulation of Light Water Reactors (CASL) is a Department of Energy Innovation Hub whose mission is the following, "CASL is a collaboration of the nation's leading scientists, institutions, and supercomputers, with an aggressive 10-year mission to confidently predict the performance of existing and next-generation commercial nuclear reactors through comprehensive, science-based modeling and simulation." The CASL program to date has focused on developing the necessary predictive capability. Rightly so, it is characterized by many as a research project. As a matter of intent, the first 6 years of CASL focused on developing and demonstrating the prediction capability of a suite of independent physics codes: MPACT (neutronics), CTH (thermal hydraulics in the core), BISON (fuel performance), and MAMBA (CRUD and boron uptake on fuel rod surfaces) The last 4 years focused on initial attempts to couple the codes and to demonstrate those capabilities through a series of challenge problems aligned to 3 key issues of interest to the nuclear power industry.

The complex physical phenomenon of shock wave interaction with material heterogeneities has significant importance and nevertheless remains little understood. In many materials, the observed macroscale response to shock loading is governed by characteristics of the microstructure. Yet, the majority of computational studies aimed at predicting phenomena affected by these processes, such as the initiation and propagation of detonation waves in explosives or shock propagation in geological materials, employ continuum material and reactive burn model treatment. In an effort to highlight the grain-scale processes that underlie the observable effects in an energetic system, a grain-scale model for hexanitrostilbene (HNS) has been developed. The measured microstructures were used to produce synthetic computational representations of the pore structure, and a density functional theory molecular dynamics derived equation of state (EOS) was used for the fully dense HNS matrix. The explicit inclusion of the microstructure along with a fully dense EOS resulted in close agreement with historical shock compression experiments. More recent experiments on the dynamic reaction threshold were also reproduced by inclusion of a global kinetics model. The complete model was shown to reproduce accurately the expected response of this heterogeneous material to shock loading. Mesoscale simulations were shown to provide a clear insight into the nature of threshold behavior and are a way to understand complex physical phenomena.

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.

Despite the advances in the methods for fabricating nanoscale materials, critical issues remain, such as the difficulties encountered in anchoring, and the deterioration in their stability after integration with other components. These issues need to be addressed to further increase the scope of their applicability. In this study, using epitaxial mesoscopic host matrices, materials are spatially confined at the nanoscale, and are supported, anchored, and stabilized. They also exhibit properties distinct from the bulk counterparts proving their high quality nanoscale nature. ZnFe2O4 and SrTiO3 are used as the model confined material and host matrix, respectively. The ZnFe2O4 phases are spatially confined by the SrTiO3 mesoscopic matrix and have strongly enhanced ferrimagnetic properties as compared to bulk and plain thin films of ZnFe2O4, with a Curie temperature of ≈500 K. The results of a series of control experiments and characterization measurements indicate that cationic inversion, which originates from the high interface-to-volume ratio of the ZnFe2O4 phase in the ZnFe2O4–SrTiO3 nanocomposite film, is responsible for the magnetization enhancement. An exchange bias is observed, owing to the coexistence of ferrimagnetic and antiferromagnetic regions in the confined ZnFe2O4 phase. The magnetic properties are dependent on the ZnFe2O4 crystallite size, which can be controlled by the growth conditions.

Li metal is the preferred anode material for all-solid-state Li batteries. However, a stable plating and stripping of Li metal at the anode-solid electrolyte interface remains a significant challenge particularly at practically feasible current densities. This problem usually relates to high and/or inhomogeneous Li-electrode-electrolyte interfacial impedance and formation and growth of high-aspect-ratio dendritic Li deposits at the electrode-electrolyte interface, which eventually shunt the battery. To better understand details of Li metal plating, we use operando electron microscopy and Auger spectroscopy to probe nucleation, growth, and stripping of Li metal during cycling of a model solid-state Li battery as a function of current density and oxygen pressure. We find a linear correlation between the nucleation density of Li clusters and the charging rate in an ultrahigh vacuum, which agrees with a classical nucleation and growth model. Moreover, the trace amount of oxidizing gas (≈10-6 Pa of O2) promotes the Li growth in a form of nanowires due to a fine balance between the ion current density and a growth rate of a thin lithium-oxide shell on the surface of the metallic Li. Interestingly, increasing the partial pressure of O2 to 10-5 Pa resumes Li plating in a form of 3D particles. Our results demonstrate the importance of trace amounts of preexisting or ambient oxidizing species on lithiation processes in solid-state batteries.

Chairman Smith, Ranking Member Johnson, and distinguished members of the Committee on Science, Space, and Technology, I thank you for the opportunity to testify today on the role of science, engineering, and research at Sandia National Laboratories, one of the nation’s premiere national labs and the nation’s largest Federally Funded Research and Development Center (FFRDC) laboratory. I am Dr. Susan Seestrom, Sandia’s Associate Laboratories Director for Advanced Science & Technology (AST) and Chief Research Officer (CRO). As CRO I am responsible for research strategy, Laboratory Directed Research & Development (LDRD), partnerships strategy, and technology transfer. As director and line manager for AST I manage capabilities and mission delivery across a variety of the physical and mathematical sciences and engineering disciplines, such as pulsed power, radiation effects, major environmental testing, high performance computing, and modeling and simulation.

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.

Control and manipulation of polarization is an important topic for imaging and light matter interactions. In the infrared regime, the large wavelengths make wire grid polarizers a viable option, as it is possible to create periodic arrays of metallic wires at that scale. The recent advent of metamaterials has spurred an increase in non-traditional polarizer motifs centred around more complicated repeat units, which potentially provide more functionality. In this paper we explore the use of two-dimensional (2D) arrays of single and back-to-back vertically oriented cross dipoles arranged in a cubic in-plane silicon matrix. Here, we show that both single and back-to-back versions have higher rejection ratios and larger bandwidths than either wire grid polarizers or 2D arrays of linear dipoles.

Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, at high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.

Many important chemical and biochemical processes in the condensed phase are notoriously difficult to simulate numerically. Often, this difficulty arises from the complexity of simulating dynamics resulting from coupling to structured, mesoscopic baths, for which no separation of time scales exists and statistical treatments fail. A prime example of such a process is vibrationally assisted charge or energy transfer. A quantum simulator, capable of implementing a realistic model of the system of interest, could provide insight into these processes in regimes where numerical treatments fail. We take a first step towards modeling such transfer processes using an ion-trap quantum simulator. By implementing a minimal model, we observe vibrationally assisted energy transport between the electronic states of a donor and an acceptor ion augmented by coupling the donor ion to its vibration. We tune our simulator into several parameter regimes and, in particular, investigate the transfer dynamics in the nonperturbative regime often found in biochemical situations.

The burning core of an inertial confinement fusion (ICF) plasma produces bright x-rays at stagnation that can directly diagnose core conditions essential for comparison to simulations and understanding fusion yields. These x-rays also backlight the surrounding shell of warm, dense matter, whose properties are critical to understanding the efficacy of the inertial confinement and global morphology. In this work, we show that the absorption and fluorescence spectra of mid-Z impurities or dopants in the warm dense shell can reveal the optical depth, temperature, and density of the shell and help constrain models of warm, dense matter. This is illustrated by the example of a high-resolution spectrum collected from an ICF plasma with a beryllium shell containing native iron impurities. Lastly, analysis of the iron K-edge provides model-independent diagnostics of the shell density (2.3 × 10²⁴ e/cm³) and temperature (10 eV), while a 12-eV red shift in Kβ and 5-eV blue shift in the K-edge discriminate among models of warm dense matter: Both shifts are well described by a self-consistent field model based on density functional theory but are not fully consistent with isolated-atom models using ad-hoc density effects.

The shock Hugoniot for full-density and porous CeO2 was investigated in the liquid regime using ab initio molecular dynamics (AIMD) simulations with Erpenbeck's approach based on the Rankine-Hugoniot jump conditions. The phase space was sampled by carrying out NVT simulations for isotherms between 6000 and 100 000 K and densities ranging from ρ=2.5 to 20g/cm3. The impact of on-site Coulomb interaction corrections +U on the equation of state (EOS) obtained from AIMD simulations was assessed by direct comparison with results from standard density functional theory simulations. Classical molecular dynamics (CMD) simulations were also performed to model atomic-scale shock compression of larger porous CeO2 models. Results from AIMD and CMD compression simulations compare favorably with Z-machine shock data to 525 GPa and gas-gun data to 109 GPa for porous CeO2 samples. Using results from AIMD simulations, an accurate liquid-regime Mie-Grüneisen EOS was built for CeO2. In addition, a revised multiphase SESAME-Type EOS was constrained using AIMD results and experimental data generated in this work. This study demonstrates the necessity of acquiring data in the porous regime to increase the reliability of existing analytical EOS models.

Two dimensional SiC-air phononic crystals have been modeled, fabricated, and tested with a measured bandgap ranging from 665 to 693 MHz. Snowflake air inclusions on a hexagonal lattice were used for the phononic crystal. By manipulating the phononic crystal lattice and inserting circular inclusions, a waveguide was created at 680 MHz. The combined insertion loss and propagation loss for the waveguide is 8.2 dB, i.e., 39% of the energy is guided due to the high level of the confinement afforded by the phononic crystal. The SiC-air phononic crystals and waveguides were fabricated using a CMOS-compatible process, which allows for seamless integration of these devices into wireless communication systems operating at microwave frequencies.

Traditional (macro-) economic impact analysis has a role in the long-run analysis of the effects of changes in resilience, since in the long-run the economy adjusts to the microeconomic impacts through various mechanisms (Kunreuther & Roth, 1998). However, measures of economic health, growth, or expansion are not sufficient for measuring resilience. The majority of infrastructure in the United States is privately owned and operated or is managed through some private-public arrangement. Most effects from changes in resilience should be assessed through short-run microeconomic analysis since the actions of firms will be spurred by internal economic decisionmaking that will have immediate impacts on local economies. Any forthcoming efforts to include resilience in the economic impacts of long duration EP outages must accommodate the private and simultaneously public nature of the EP infrastructure as well as its role as lifeline infrastructure. Resilience metrics and methodologies will only be helpful to stakeholders if these metrics help them understand the value of improvements to the resilience of communities, infrastructures, or industries. In their paper, Schellenberg et al. (2018) have provided a well thought out "lay of the lane of the common methods of estimating the economic costs of EP disruptions, which includes discussion of the difference between costs of outage and regional economic modeling, strengths and weaknesses of methods, the difficulty in incorporating resilience, data collection and availability issues, and recommendations for future research.

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditions can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.

Using combined experimental and computational approaches, we show that at 43 GPa and 1300 K gallium phosphide adopts the super-Cmcm structure, here indicated with its Pearson notation oS24. First-principles enthalpy calculations demonstrate that this structure is more thermodynamically stable above ∼20 GPa than previously proposed polymorphs. In contrast to other polymorphs, the oS24 phase shows a strong bonding differentiation and distorted fivefold coordination geometries of both P atoms. The shortest bond of the phase is a single covalent P-P bond measuring 2.171(11) Å at synthesis pressure. Phosphorus dimerization in GaP sheds light on the nature of the super-Cmcm phase and provides critical new insights into the high-pressure polymorphism of octet semiconductors. Bond directionality and anisotropy explain the relatively low symmetry of this high-pressure phase.

Fatigue crack growth rate (FCGR) data were measured in high pressure hydrogen gas versus stress intensity factor range (ΔK) in specimens removed from a X100 welded steel pipe. Three distinct regions of the pipe weld were examined: base metal, weld fusion zone, and heat affected zone. Tests were performed at a load ratio (R) of 0.5, frequency of 1 Hz, and at a hydrogen gas pressure of 21 MPa. Tests were also performed in air at 10 Hz as a reference. Fatigue crack growth rates were observed to be over an order of magnitude higher for tests performed in hydrogen compared to the rates from tests in air. Residual stress measurements were collected on identical specimens cut from the base metal, weld, and heat affected zone to account for their influence on measured FCGR data. The slitting method provided residual stress and residual stress intensity factor (K_res), the effect of which was removed from the FCGR data using K_norm in order to provide a more direct comparison of crack growth resistance of the base metal, weld and heat affected zone. Prior to accounting for residual stress, FCGR in hydrogen gas appeared to be highest in the weld fusion zone. Furthermore, after accounting for residual stress effects, the weld fusion zone FCGR data converged to the base metal FCGR data, which underscores the importance of accounting for residual stress effects when assessing fatigue performance.

Various technologies presented herein relate to enhancing mixing inside a combustion chamber to form one or more locally premixed mixtures comprising fuel and charge-gas with low peak fuel to charge-gas ratios to enable minimal, or no, generation of soot and other undesired emissions during ignition and subsequent combustion of the locally premixed mixtures. To enable sufficient mixing of the fuel and charge-gas, a jet of fuel can be directed to pass through a bore of a duct causing charge-gas to be drawn into the bore creating turbulence to mix the fuel and the drawn charge-gas. The duct can be located proximate to an opening in a tip of a fuel injector. The duct can comprise of one or more holes along its length to enable charge-gas to be drawn into the bore, and further, the duct can cool the fuel and/or charge-gas prior to combustion.

Rare-earth (RE) coordination polymers are infinitely tailorable to yield luminescent materials for various applications. Here we described the synthesis of a heterometallic rare-earth coordination compound ((CH3)2SO)3(RE)NbO(C2O4)3 ((CH3)2SO) = dimethylsulfoxide, DMSO, (C2O2 = oxalate), (RE=La, Ce, Pr, Nd, Sm, Eu, Gd, Tb). The structure was obtained from single crystal X-ray diffraction of the La analogue. The Nb˭O and DMSO terminal-bonding character guides assembly of an open framework structure with noncentrosymmetric RE-coordination geometry, and large spacing between the RE centers. A second structure was observed by PXRD for the smaller rare earths (Dy, Ho, Er, Yb); this structure has not yet been determined. The materials were further characterized using FTIR, and photoluminescence measurements. Characteristic excitation and emission transitions were observed for RE = Nd, Sm, Eu, and Tb. Quantum yield (QY) measurements were performed by exciting Eu and Tb analoges at 394 nm (QY 66%) and 464 nm (QY 71%) for Eu; and 370 nm (QY=40%) for Tb. We attribute the high QY and bright luminescence to two main structure-function properties of the system; namely the absence of water in the structure, and absence of concentration quenching.

Wettability of the oil/brine/rock system is an essential petro-physical parameter which governs subsurface multiphase flow behaviour and the distribution of fluids, thus directly affecting oil recovery. Recent studies [1–3] show that manipulation of injected brine composition can enhance oil recovery by shifting wettability from oil-wet to water-wet. However, what factor(s) control system wettability has not been completely elucidated due to incomplete understanding of the geochemical system. To isolate and identify the key factors at play we used SO42—free solutions to examine the effect of salinity (formation brine/FB, 10 times diluted formation brine/10 dFB, and 100 times diluted formation brine/100 dFB) on the contact angle of oil droplets at the surface of calcite. We then compared contact angle results with predictions of surface complexation by low salinity water using PHREEQC software. We demonstrate that the conventional dilution approach likely triggers an oil-wet system at low pH, which may explain why the low salinity water EOR-effect is not always observed by injecting low salinity water in carbonated reservoirs. pH plays a fundamental role in the surface chemistry of oil/brine interfaces, and wettability. Our contact angle results show that formation brine triggered a strong water-wet system (35°) at pH 2.55, yet 100 times diluted formation brine led to a strongly oil-wet system (contact angle = 175°) at pH 5.68. Surface complexation modelling correctly predicted the wettability trend with salinity; the bond product sum ([>CaOH2+][–COO−] + [>CO3−][–NH+] + [>CO3−][–COOCa+]) increased with decreasing salinity. At pH < 6 dilution likely makes the calcite surface oil-wet, particularly for crude oils with high base number. Yet, dilution probably causes water wetness at pH > 7 for crude oils with high acid number.

Absolute Hugoniot measurements for empty plastic foams at ∼10% of solid polystyrene density and supporting rad-hydro simulation results are reported. Planar foam slabs, ∼400 μm thick and ∼500 μm wide, some of which were covered with a 10 μm solid plastic ablator, were directly driven by 4 ns long Nike krypton-fluoride 248 nm wavelength laser pulses that produced strong shock waves in the foam. The shock and mass velocities in our experiments were up to 104 km/s and 84 km/s, respectively, and the shock pressures up to ∼9 Mbar. The motion of the shock and ablation fronts was recorded using side-on monochromatic x-ray imaging radiography. The steadiness of the observed shock and ablation fronts within ∼1% has been verified. The Hugoniot data inferred from our velocity measurements agree with the predictions of the SESAME and CALEOS equation-of-state models near the highest pressure ∼9 Mbar and density compression ratio ∼5. In the lower pressure range 2-5 Mbar, a lower shock density compression is observed than that predicted by the models. Possible causes for this discrepancy are discussed.

A finite element numerical analysis model has been constructed that consists of a mesh that effectively captures the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multimechanism deformation (M-D) salt constitutive model using the daily data of actual wellhead pressure and oil–brine interface location. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt are limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used as the field baseline measurement. The structure factor, A2, and transient strain limit factor, K0, in the M-D constitutive model are used for the calibration. The value of A2, obtained experimentally from BC salt, and the value of K0, obtained from Waste Isolation Pilot Plant salt, are used for the baseline values. To adjust the magnitude of A2 and K0, multiplication factors A2F and K0F are defined, respectively. The A2F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict behaviors of the salt dome, caverns, caprock, and interbed layers. The geotechnical concerns associated with the BC site from this analysis will be explained in a follow-up paper.

We demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynoldsaveraged Navier-Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscosity model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models ("curve-fits"). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. We find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.

This paper presents the application of a theoretically developed method that provides plasma parameter solution space information from measured RF attenuation that occurs during reentry. The purpose is to provide reentry plasma parameter information from the communication signal attenuation. The theoretical development centers around the attenuation and the complex index of refraction. The methodology uses an imaginary index of the refraction matching algorithm with a tolerance to find suitable solutions that satisfy the theory. The imaginary matching terms are then used to determine the real index of refraction resulting in the complex index of refraction. Then a filter is used to reject nonphysical solutions. Signal attenuation-based plasma parameter properties investigated include the complex index of refraction, plasma frequency, electron density, collision frequency, propagation constant, attenuation constant, phase constant, complex plasma conductivity, and electron mobility. RF plasma thickness attenuation is investigated and compared to the literature. Similar plasma thickness for a specific signal attenuation can have different plasma properties.

We consider the utilization of a computational model to guide the optimal acquisition of experimental data to inform the stochastic description of model input parameters. Our formulation is based on the recently developed consistent Bayesian approach for solving stochastic inverse problems, which seeks a posterior probability density that is consistent with the model and the data in the sense that the push-forward of the posterior (through the computational model) matches the observed density on the observations almost everywhere. Given a set of potential observations, our optimal experimental design (OED) seeks the observation, or set of observations, that maximizes the expected information gain from the prior probability density on the model parameters. We discuss the characterization of the space of observed densities and a computationally efficient approach for rescaling observed densities to satisfy the fundamental assumptions of the consistent Bayesian approach. Numerical results are presented to compare our approach with existing OED methodologies using the classical/statistical Bayesian approach and to demonstrate our OED on a set of representative partial differential equations (PDE)-based models.

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.

Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate its usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.

The delocalization of x-ray signals limits the spatial resolution in atomic-scale elemental mapping by scanning transmission electron microscopy (STEM) using energy-dispersive x-ray spectroscopy (EDS). In this study, using a SrTiO 3 [001] single crystal, we show that the x-ray localization to atomic columns is strongly dependent on crystal thickness, and a thin crystal is critical for improving the spatial resolution in atomic-scale EDS mapping. A single-frame scanning technique is used in this study instead of the multiple-frame technique to avoid peak broadening due to tracking error. The strong thickness dependence is realized by measuring the full width at half maxima (FWHM) as well as the peak-to-valley (P/V) ratio of the EDS profiles for Ti K and Sr K + L, obtained at several crystal thicknesses. A FWHM of about 0.16 nm and a P/V ratio of greater than 7.0 are obtained for Ti K for a crystal thickness of less than 20 nm. With increasing crystal thickness, the FWHM and P/V ratio increases and decreases, respectively, indicating the advantage of using a thin crystal for high-resolution EDS mapping.

This paper explores the viability of using counterfactual reasoning for impact analyses when understanding and responding to "beyond-design-basis" nuclear power plant accidents. Currently, when a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines. However, the current guidelines are limited in scope and depth: for certain types of accidents, plant operators would have to work to mitigate the damage with limited experience and guidance for the particular situation. We aim to fill the need for comprehensive accident support by using a dynamic Bayesian network to aid in the diagnosis of a nuclear reactor's state and to analyze the impact of possible response measures. The dynamic Bayesian network, DBN, offers an expressive representation of the components and relationships that make up a complex causal system. For this reason, and for its tractable reasoning, the DBN supports a functional model for the intricate operations of nuclear power plants. In this domain, it is also pertinent that a Bayesian network can be composed of both probabilistic and knowledge-based components. Though probabilities can be calculated from simulated models, the structure of the network, as well as the value of some parameters, must be assigned by human experts. Since dynamic Bayesian network-based systems are capable of running better-than-real-time situation analyses, they can support both current event and alternate scenario impact analyses.

Dennard scaling has ended. Lowering the voltage supply (Vdd) to sub-volt levels causes intermittent losses in signal integrity, rendering further scaling (down) no longer acceptable as a means to lower the power required by a processor core. However, it is possible to correct the occasional errors caused due to lower Vddin an efficient manner and effectively lower power. By deploying the right amount and kind of redundancy, we can strike a balance between overhead incurred in achieving reliability and energy savings realized by permitting lower Vdd. One promising approach is the Redundant Residue Number System (RRNS) representation. Unlike other error correcting codes, RRNS has the important property of being closed under addition, subtraction and multiplication, thus enabling computational error correction at a fraction of an overhead compared to conventional approaches. We use the RRNS scheme to design a Computationally-Redundant, Energy-Efficient core, including the microarchitecture, Instruction Set Architecture (ISA) and RRNS centered algorithms. From the simulation results, this RRNS system can reduce the energy-delay-product by about 3× for multiplication intensive workloads and by about 2× in general, when compared to a non-error-correcting binary core.

Molecular dynamics (MD) simulations and experimental evaporation were applied to study the growth of evaporated (Cu)ZnTe on mono- and polycrystalline CdTe. The simulated structures show polytypism and polycrystallinity, including texturing and grain boundaries, diffusion, and other phenomena in excellent qualitative agreement with experimental atomic probe tomography, transmission electron microscope, and secondary ion mass spectrometry. Results show formation of Cu clusters in nonstoichiometric growths even at early stages of deposition. Results also show significantly faster diffusion along defected regions (uncorrelated CdTe grain boundaries) as compared with more highly crystalline areas (high-symmetry grain boundaries and pristine regions). Activation energies and pre-exponential factors of Cu, Zn, and Te diffusion were determined using simulation. The MD model captures crystal growth phenomena with a high degree of fidelity.

This paper presents the model-based design and evaluation of an instrument that estimates incident neutron direction using the kinematics of neutron scattering by hydrogen-1 nuclei in an organic scintillator. The instrument design uses a single, nearly contiguous volume of organic scintillator that is internally subdivided only as necessary to create optically isolated pillars, i.e., long, narrow parallelepipeds of organic scintillator. Scintillation light emitted in a given pillar is confined to that pillar by a combination of total internal reflection and a specular reflector applied to the four sides of the pillar transverse to its long axis. The scintillation light is collected at each end of the pillar using a photodetector, e.g., a microchannel plate photomultiplier (MCP-PM) or a silicon photomultiplier (SiPM). In this optically segmented design, the (x,y) position of scintillation light emission (where the x and y coordinates are transverse to the long axis of the pillars) is estimated as the pillar's (x,y) position in the scintillator “block”, and the z-position (the position along the pillar's long axis) is estimated from the amplitude and relative timing of the signals produced by the photodetectors at each end of the pillar. The neutron's incident direction and energy is estimated from the (x,y,z)-positions of two sequential neutron–proton scattering interactions in the scintillator block using elastic scatter kinematics. For proton recoils greater than 1 MeV, we show that the (x,y,z)-position of neutron–proton scattering can be estimated with < 1 cm root-mean-squared [RMS] error and the proton recoil energy can be estimated with < 50 keV RMS error by fitting the photodetectors’ response time history to models of optical photon transport within the scintillator pillars. Finally, we evaluate several alternative designs of this proposed single-volume scatter camera made of pillars of plastic scintillator (SVSC-PiPS), studying the effect of pillar dimensions, scintillator material (EJ-204, EJ-232Q and stilbene), and photodetector (MCP-PM vs. SiPM) response vs. time. We demonstrate that the most precise estimates of incident neutron direction and energy can be obtained using a combination of scintillator material with high luminosity and a photodetector with a narrow impulse response. Specifically, we conclude that an SVSC-PiPS constructed using EJ-204 (a high luminosity plastic scintillator) and an MCP-PM will produce the most precise estimates of incident neutron direction and energy.

Directed energy deposited (DED) and forged austenitic stainless steels possess dissimilar microstructures but can exhibit similar mechanical properties. In this study, annealing was used to evolve the microstructure of both conventional wrought and DED type 304L austenitic stainless steels, and significant differences were observed. In particular, the density of geometrically necessary dislocations and hardness were used to probe the evolution of the microstructure and properties. Forged type 304L exhibited the expected decrease in measured dislocation density and hardness as a function of annealing temperature. The more complex microstructure–property relationship observed in the DED type 304L material is attributed to compositional heterogeneities in the solidification microstructure.

Diffusion of point defects during irradiation is simulated via a two-way coupling between mechanical stress and defect diffusion in iron. This diffusion is based on a modified chemical potential that includes not only the local concentration of radiation-induced defects, but also the influence of the residual stress field from both the microstructure (i.e. dislocations or grain boundaries) and the eigenstrain caused by the defects themselves. Defect flux and concentration rates are derived from this chemical potential using Fick's first and second laws. Mean field rate theory is incorporated to model the annihilation of Frenkel pairs, and increased annihilation near grain boundaries is included based on the elastic energy of each grain boundary. Mechanical equilibrium is coupled with diffusion by computing eigenstrain from point defects and adding this to the total strain. Intrinsic stresses associated with the dislocations and grain boundaries are calculated using dislocation and disclination mechanics. Through this two-way-coupled model, regions of low concentration are seen near grain boundaries, and sink efficiency is calculated for different types of microstructure. The results show that the two-way mechanical coupling has a strong influence on sink efficiency for dislocation loops. The results also suggest that misorientation is a poor metric for determining sink efficiency, with sink density and elastic energy being much more informative.

Presented are the results from the liner ablation experiments conducted at 550 kA on the Michigan Accelerator for Inductive Z-Pinch Experiments. These experiments were performed to evaluate a hypothesis that the electrothermal instability (ETI) is responsible for the seeding of magnetohydrodynamic instabilities and that the cumulative growth of ETI is primarily dependent on the material-specific ratio of critical temperature to melting temperature. This ratio is lower in refractory metals (e.g., tantalum) than in non-refractory metals (e.g., aluminum or titanium). The experimental observations presented herein reveal that the plasma-vacuum interface is remarkably stable in tantalum liner ablations. This stability is particularly evident when contrasted with the observations from aluminum and titanium experiments. These results are important to various programs in pulsed-power-driven plasma physics that depend on liner implosion stability. Examples include the magnetized liner inertial fusion (MagLIF) program and the cylindrical dynamic material properties program at Sandia National Laboratories, where liner experiments are conducted on the 27-MA Z facility.

The properties of hot, dense plasmas generated by the irradiation of GaAs targets by the Titan laser at Lawrence Livermore National Laboratory were determined by the analysis of high resolution K shell spectra in the 9 keV to 11 keV range. The laser parameters, such as relatively long pulse duration and large focal spot, were chosen to produce a steady-state plasma with minimal edge gradients, and the time-integrated spectra were compared to non-LTE steady state spectrum simulations using the FLYCHK and NOMAD codes. The bulk plasma streaming velocity was measured from the energy shifts of the Ga He-like transitions and Li-like dielectronic satellites. The electron density and the electron energy distribution, both the thermal and the hot non-thermal components, were determined from the spectral line ratios. After accounting for the spectral line broadening contributions, the plasma turbulent motion was measured from the residual line widths. The ionization balance was determined from the ratios of the He-like through F-like spectral features. The detailed comparison of the experimental Ga spectrum and the spectrum simulated by the FLYCHK code indicates two significant discrepancies, the transition energy of a Li-like dielectronic satellite (designated t) and the calculated intensity of a He-like line (x), that should lead to improvements in the kinetics codes used to simulate the X-ray spectra from highly-charged ions.

Criegee intermediates (CIs), carbonyl oxides formed in ozonolysis of alkenes, play key roles in the troposphere. The decomposition of CIs can be a significant source of OH to the tropospheric oxidation cycle especially during nighttime and winter months. A variety of model-measurement studies have estimated surface-level stabilized Criegee intermediate (sCI) concentrations on the order of 1 × 104 cm-3 to 1 × 105 cm-3, which makes a non-negligible contribution to the oxidising capacity in the terrestrial boundary layer. The reactions of sCI with the water monomer and the water dimer have been found to be the most important bimolecular reactions to the tropospheric sCI loss rate, at least for the smallest carbonyl oxides; the products from these reactions (e.g. hydroxymethyl hydroperoxide, HMHP) are also of importance to the atmospheric oxidation cycle. The sCI can oxidise SO2 to form SO3, which can go on to form a significant amount of H2SO4 which is a key atmospheric nucleation species and therefore vital to the formation of clouds. The sCI can also react with carboxylic acids, carbonyl compounds, alcohols, peroxy radicals and hydroperoxides, and the products of these reactions are likely to be highly oxygenated species, with low vapour pressures, that can lead to nucleation and SOA formation over terrestrial regions.

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The design, fabrication, and performance of InGaAs and InGaP/GaAs microcells are presented. These cells are integrated with a Si wafer providing a path for insertion in hybrid concentrated photovoltaic modules. Comparisons are made between bonded cells and cells fabricated on their native wafer. The bonded cells showed no evidence of degradation in spite of the integration process that involved significant processing including the removal of the III-V substrate.

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A measurement instrument utilizing dual, chromatic, confocal, distance sensors has been jointly developed by General Atomics and Sandia National Laboratories (SNL) for thickness and flatness measurement of target components used in dynamic materials properties (DMP) experiments on the SNL Z-Machine (Z). Compared to previous methods used in production of these types of targets, the tool saves time and yields a 4× reduction in thickness uncertainty which is one of the largest sources of error in equation of state measurements critical to supporting the National Nuclear Security Administration Stockpile Stewardship program and computer modeling of high energy density experiments. It has numerous differences from earlier instruments operating on the dual confocal sensor principle to accommodate DMP components including larger lateral travel, longer working distance, ability to measure flatness in addition to thickness, built-in thickness calibration standards for quickly checking calibration before and after each measurement, and streamlined operation. Thickness and flatness of 0.2- to 3.3-mm-thick sections of diamond-machined copper and aluminum can be measured to submicron accuracy. Sections up to 6 mm thick can be measured with as-yet undetermined accuracy. Samples must have one surface which is flat to within 300 µm, lateral dimensions of no more than 50 ×50 mm, and height less than 40 mm.

Grid operators are increasingly turning to advanced grid-support functions in distributed energy resources (DER) to assist with distribution circuit voltage regulation, bulk system frequency control, and power system protection. The U.S. DER certification standard, Underwriters Laboratories (UL) 1741, was revised in September 2016 to add test procedures for multiple grid-support functions. Sandia National Laboratories, SunSpec Alliance, and growing community of collaborators have undertaken a multiyear effort to create an open-source system validation platform (SVP) that automates DER interconnection and interoperability test procedures by communicating with grid simulators, photovoltaic (PV) simulators, data acquisition systems, and interoperable equipment under test. However, the power hardware required for generating the test conditions may be untenable for many organizations. Herein, we discuss development of the SVP testing capabilities for UL 1741 tests utilizing a controller hardware-in-The-loop testbed that precludes the need for power hardware using a 34.5 kW Austrian Institute of Technology smart grid controller. Analysis of normal ramp rate, soft start ramp rate, specified power factor, volt-VAr, and frequency-watt advanced grid functions, and the effectiveness of the UL 1741 test protocols are included.

This study shows fuel film measurements in a spark-ignited direct injection engine using refractive index matching (RIM). The RIM technique is applied to measure the fuel impingement of a high research octane number gasoline fuel with 30 vol% ethanol content at two intake pressures and coolant temperatures. Measurements are conducted for an alkylate fuel at one operating case, as well. It is shown that the fuel volume on the piston surface increases for lower intake pressure and lower coolant temperature and that the alkylate fuel shows very little spray impingement. The fuel films can be linked to increased soot emissions. A detailed description of the calibration technique is provided and measurement uncertainties are discussed. The dependency of the RIM signal on refractive index changes is measured. The RIM technique provides quantitative film thickness measurements up to 0.9 µm in this engine. For thicker films, semi-quantitative results of film thickness can be utilized to study the distribution of impinged fuel.

This review article is dedicated to the Dynamic Behavior of Materials Technical Division for celebrating the 75th anniversary of the Society for Experimental Mechanics (SEM). Understanding dynamic behavior of geomaterials is critical for analyzing and solving engineering problems of various applications related to underground explosions, seismic, airblast, and penetration events. Determining the dynamic tensile response of geomaterials has been a great challenge in experiments due to the nature of relatively low tensile strength and high brittleness. Various experimental approaches have been made in the past century, especially in the most recent half century, to understand the dynamic behavior of geomaterials in tension. In this review paper, we summarized the dynamic tensile experimental techniques for geomaterials that have been developed. The major dynamic tensile experimental techniques include dynamic direct tension, dynamic split tension, and spall tension. All three of the experimental techniques are based on Hopkinson or split Hopkinson (also known as Kolsky) bar techniques and principles. Uniqueness and limitations for each experimental technique are also discussed.

Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-termaveraging/long-termaveraging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveformmethod to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.

A novel adaptive time stepping scheme for fluid-structure interaction (FSI) problems is proposed that allows for controlling the accuracy of the time-discrete solution. Furthermore, it eases practical computations by providing an efficient and very robust time step size selection. This has proven to be very useful, especially when addressing new physical problems, where no educated guess for an appropriate time step size is available. The fluid and the structure field, but also the fluid-structure interface are taken into account for the purpose of a posteriori error estimation, rendering it easy to implement and only adding negligible additional cost. The adaptive time stepping scheme is incorporated into a monolithic solution framework, but can straightforwardly be applied to partitioned solvers as well. The basic idea can be extended to the coupling of an arbitrary number of physical models. Accuracy and efficiency of the proposed method are studied in a variety of numerical examples ranging from academic benchmark tests to complex biomedical applications like the pulsatile blood flow through an abdominal aortic aneurysm. The demonstrated accuracy of the time-discrete solution in combination with reduced computational cost make this algorithm very appealing in all kinds of FSI applications.

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. This article explores the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

Zirconium tetrachloride, ZrCl4, is a strategic material with wide-ranging applications. Until now, only one crystallographic study on ZrCl4 has been reported [Krebs (1970). Z. Anorg. Allg. Chem.378, 263-272] and that was more than 40 years ago. The compound used for the previous determination was prepared from ZrO2 and Cl2-CCl4, and single-crystal X-ray diffraction (SCXRD) studies on ZrCl4 obtained from Zr metal have not yet been reported. In this context, we prepared ZrCl4 from the reaction of Zr metal and Cl2 gas in a sealed tube and investigated its structure at 100, 150, 200, 250, and 300 K. At 300 K, the SCXRD analysis indicates that ZrCl4 crystallizes in the orthorhombic space group Pca21 [a = 6.262 (9), b = 7.402 (11), c = 12.039 (17) Å, and V = 558.0 (14) Å3] and consists of infinite zigzag chains of edge-sharing ZrCl6 octahedra. This chain motif is similar to that observed previously in ZrCl4, but the structural parameters and space group differ. In the temperature range 100-300 K, no phase transformation was identified, while elongation of intra-chain Zr...Zr [3.950 (1) Å at 100 K and 3.968 (5) Å at 300 K] and inter-chain Cl...Cl [3.630 (3) Å at 100 K and 3.687 (9) Å at 300 K] distances occurred.ZrCl4 has been prepared from the reaction of Zr metal and Cl2 gas in a sealed tube and its structure determined at 100, 150, 200, 250, and 300 K. The chain motif is similar to that observed previously in ZrCl4, but the structural parameters and space group differ.

Flow batteries are an attractive technology for energy storage of grid-scale renewables. However, performance issues related to ion-exchange membrane (IEM) fouling and crossover of species have limited the success of flow batteries. In this work we propose the use of the solid-state sodium-ion conductor NaSICON as an IEM to fully eliminate active species crossover in room temperature, aqueous, neutral pH flow batteries. We measure the room temperature conductivity of NaSICON at 2.83–4.67 mS cm−1 and demonstrate stability of NaSICON in an aqueous electrolyte with conductivity values remaining near 2.5 mS cm−1 after 66 days of exposure. Charge and discharge of a full H-cell battery as well as symmetric cycling in a flow battery configuration using NaSICON as an IEM in both cases demonstrates the capability of the solid-state IEM. Extensive analysis of aged cells through electrochemical impedance spectroscopy (EIS) and UV–vis spectroscopy show no contaminant species having crossed over the NaSICON membrane after 83 days of exposure, yielding an upper limit to the permeability of NaSICON of 4 × 10−10 cm2 min−1. The demonstration of NaSICON as an IEM enables a wide new range of chemistries for application to flow batteries that would previously be impeded by species crossover and associated degradation.

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Sandia National Laboratories has tested and evaluated two Guralp Affinity digitizers. The Affinity digitizers are intended to record sensor output for seismic and infrasound monitoring applications. The purpose of this digitizer evaluation is to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self- noise, dynamic range, system noise, response, passband, and timing. The Affinity digitizers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO).

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Suppose Tom is working to develop a rocket. Susan is very interested in knowing what Tom is doing but cannot directly observe his testing of the rocket propulsion system. Specifically, she would like to know if Tom has the ability to launch a heavy rocket or a light rocket. She thinks she can learn about Tom’s capability by learning about what type of rocket engine Tom is using, and the number of rockets in the design. She is considering buying a special sensor that can observe flashes from the rocket firing up during the tests and indicate if the rockets fire in a sufficiently narrow window of time such that they would successfully lift a heavy rocket.

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