Publications

There is a great deal of debate concerning the benefits of working memory (WM) training and whether that training can transfer to other tasks. Although a consistent finding is that WM training programs elicit a short-term near-transfer effect (i.e., improvement in WM skills), results are inconsistent when considering persistence of such improvement and far transfer effects. In this study, we compared three groups of participants: a group that received WM training, a group that received training on how to use a mental imagery memory strategy, and a control group that received no training. Although the WM training group improved on the trained task, their posttraining performance on nontrained WM tasks did not differ from that of the other two groups. In addition, although the imagery training group’s performance on a recognition memory task increased after training, the WM training group’s performance on the task decreased after training. Participants’ descriptions of the strategies they used to remember the studied items indicated that WM training may lead people to adopt memory strategies that are less effective for other types of memory tasks. These results indicate that WM training may have unintended consequences for other types of memory performance.

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among agents. However, agent-based models are often not developed explicitly for prediction, and are generally not validated as such. We therefore present a novel data-driven agent-based modeling framework, in which individual behavior model is learned by machine learning techniques, deployed in multi-agent systems and validated using a holdout sequence of collective adoption decisions. We apply the framework to forecasting individual and aggregate residential rooftop solar adoption in San Diego county and demonstrate that the resulting agent-based model successfully forecasts solar adoption trends and provides a meaningful quantification of uncertainty about its predictions. Meanwhile, we construct a second agent-based model, with its parameters calibrated based on mean square error of its fitted aggregate adoption to the ground truth. Our result suggests that our data-driven agent-based approach based on maximum likelihood estimation substantially outperforms the calibrated agent-based model. Seeing advantage over the state-of-the-art modeling methodology, we utilize our agent-based model to aid search for potentially better incentive structures aimed at spurring more solar adoption. Although the impact of solar subsidies is rather limited in our case, our study still reveals that a simple heuristic search algorithm can lead to more effective incentive plans than the current solar subsidies in San Diego County and a previously explored structure. Finally, we examine an exclusive class of policies that gives away free systems to low-income households, which are shown significantly more efficacious than any incentive-based policies we have analyzed to date.

In this work we investigate a method that confirms the operability of neutron detectors requiring neither radiological sources nor radiation-generating devices. This is desirable when radiological sources are not available, but confidence in the functionality of the instrument is required. The “source”, based on the production of neutrons in high-Z materials by muons, provides a tagged, low-background and consistent rate of neutrons that can be used to check the functionality of or calibrate a detector. Using a Monte Carlo guided optimization, an experimental apparatus was designed and built to evaluate the feasibility of this technique. Through a series of trial measurements in a variety of locations we show that gated muon-induced neutrons appear to provide a consistent source of neutrons (35.9 ± 2.3 measured neutrons/10,000 muons in the instrument) under normal environmental variability (less than one statistical standard deviation for 10,000 muons) with a combined environmental + statistical uncertainty of ~18% for 10,000 muons. This is achieved in a single 21-22 minute measurement at sea level.

Through various means of structural and synaptic plasticity enabling online learning, neural networks are constantly reconfiguring their computational functionality. Neural information content is embodied within the configurations, representations, and computations of neural networks. To explore neural information content, we have developed metrics and computational paradigms to quantify neural information content. We have observed that conventional compression methods may help overcome some of the limiting factors of standard information theoretic techniques employed in neuroscience, and allows us to approximate information in neural data. To do so we have used compressibility as a measure of complexity in order to estimate entropy to quantitatively assess information content of neural ensembles. Using Lempel-Ziv compression we are able to assess the rate of generation of new patterns across a neural ensemble's firing activity over time to approximate the information content encoded by a neural circuit. As a specific case study, we have been investigating the effect of neural mixed coding schemes due to hippocampal adult neurogenesis.

Resistive memories enable dramatic energy reductions for neural algorithms. We propose a general purpose neural architecture that can accelerate many different algorithms and determine the device properties that will be needed to run backpropagation on the neural architecture. To maintain high accuracy, the read noise standard deviation should be less than 5% of the weight range. The write noise standard deviation should be less than 0.4% of the weight range and up to 300% of a characteristic update (for the datasets tested). Asymmetric nonlinearities in the change in conductance vs pulse cause weight decay and significantly reduce the accuracy, while moderate symmetric nonlinearities do not have an effect. In order to allow for parallel reads and writes the write current should be less than 100 nA as well.

Electrical performance and characterization of deep levels in vertical GaN P-i-N diodes grown on low threading dislocation density (∼104 - 106cm-2) bulk GaN substrates are investigated. The lightly doped n drift region of these devices is observed to be highly compensated by several prominent deep levels detected using deep level optical spectroscopy at Ec-2.13, 2.92, and 3.2 eV. A combination of steady-state photocapacitance and lighted capacitance-voltage profiling indicates the concentrations of these deep levels to be Nt = 3 × 1012, 2 × 1015, and 5 × 1014cm-3, respectively. The Ec-2.92 eV level is observed to be the primary compensating defect in as-grown n-type metal-organic chemical vapor deposition GaN, indicating this level acts as a limiting factor for achieving controllably low doping. The device blocking voltage should increase if compensating defects reduce the free carrier concentration of the n drift region. Understanding the incorporation of as-grown and native defects in thick n-GaN is essential for enabling large VBD in the next-generation wide-bandgap power semiconductor devices. Thus, controlling the as-grown defects induced by epitaxial growth conditions is critical to achieve blocking voltage capability above 5 kV.

The systematic design, fabrication, and characterization of an isolated, single-mode, 90° bend phononic crystal (PnC) waveguide are presented. A PnC consisting of a 2D square array of circular air holes in an aluminum substrate is used, and waveguides are created by introducing a line defect in the PnC lattice. A high transmission coefficient is observed (-1 dB) for the straight sections of the waveguide, and an overall 2.3 dB transmission loss is observed (a transmission coefficient of 76%) for the 90° bend. Further optimization of the structure may yield higher transmission efficiencies. This manuscript shows the complete design process for an engineered 90° bend PnC waveguide from inception to experimental demonstration.

This Field Implementation Plan (FIP) was prepared by Sandia National Laboratories, New Mexico (SNL/NM) and provides instruction on conducting a series of in-situ bioremediation (ISB) tests as described in the Revised Treatability Study Work Plan for In-Situ Bioremediation at the Technical Area-V Groundwater Area of Concern, referred to as the Revised Work Plan in this FIP. The Treatability Study is designed to gravity inject an electron-donor substrate and bioaugmentation bacteria into groundwater via three injection wells to perform bioremediation of the constituents of concern (COCs), nitrate and trichloroethene (TCE), in the regions with the highest concentrations at the Technical Area-V Groundwater (TAVG) Area of Concern (AOC). The Treatability Study will evaluate the effectiveness of bioremediation solution delivery and COC treatment over time. This FIP is designed for SNL/NM work planning and management. It is not intended to be submitted for regulator’s approval. The technical details presented in this FIP are subject to change based on field conditions, availability of equipment and materials, feasibility, and inputs from Sandia personnel and Aboveground Injection System contractor.

Photoelectron Photoion Coincidence (PEPICO) spectroscopy holds the promise of a universal, isomer-selective, and sensitive analytical technique for time-resolved quantitative analysis of bimolecular chemical reactions. Unfortunately, its low dynamic range of ∼103 has largely precluded its use for this purpose, where a dynamic range of at least 105 is generally required. This limitation is due to the false coincidence background common to all coincidence experiments, especially at high count rates. Electron/ion pairs emanating from separate ionization events but arriving within the ion time of flight (TOF) range of interest constitute the false coincidence background. Although this background has uniform intensity at every m/z value, the Poisson scatter in the false coincidence background obscures small signals. In this paper, temporal ion deflection coupled with a position-sensitive ion detector enables suppression of the false coincidence background, increasing the dynamic range in the PEPICO TOF mass spectrum by 2-3 orders of magnitude. The ions experience a time-dependent electric deflection field at a well-defined fraction of their time of flight. This deflection defines an m/z- and ionization-time dependent ion impact position for true coincidences, whereas false coincidences appear randomly outside this region and can be efficiently suppressed. When cold argon clusters are ionized, false coincidence suppression allows us to observe species up to Ar9+, whereas Ar4+ is the largest observable cluster under traditional operation. This advance provides mass-selected photoelectron spectra for fast, high sensitivity quantitative analysis of reacting systems.

Single crystal lithium fluoride (LiF), oriented [100], was shock loaded and subsequently shocklessly compressed in two experiments at the Z Machine. Velocimetry measurements were employed to obtain an impactor velocity, shock transit times, and in-situ particle velocities for LiF samples up to ∼1.8 mm thick. A dual thickness Lagrangian analysis was performed on the in-situ velocimetry data to obtain the mechanical response along the loading path of these experiments. An elastic response was observed on one experiment during initial shockless compression from 100 GPa before yielding. The relatively large thickness differences utilized for the dual sample analyses (up to ∼1.8 mm) combined with a relative timing accuracy of ∼0.2 ns resulted in an uncertainty of less than 1% on density and stress at ∼200 GPa peak loading on one experiment and <4% on peak loading at ∼330 GPa for another. The stress-density analyses from these experiments compare favorably with recent equation of state models for LiF.

Nanomedicines have significant potential for cancer treatment. Although the majority of nanomedicines currently tested in clinical trials utilize simple, biocompatible liposome-based nanocarriers, their widespread use is limited by non-specificity and low target site concentration and thus, do not provide a substantial clinical advantage over conventional, systemic chemotherapy. In the past 20 years, we have identified specific receptors expressed on the surfaces of tumor endothelial and perivascular cells, tumor cells, the extracellular matrix and stromal cells using combinatorial peptide libraries displayed on bacteriophage. These studies corroborate the notion that unique receptor proteins such as IL-11Rα, GRP78, EphA5, among others, are differentially overexpressed in tumors and present opportunities to deliver tumor-specific therapeutic drugs. By using peptides that bind to tumor-specific cell-surface receptors, therapeutic agents such as apoptotic peptides, suicide genes, imaging dyes or chemotherapeutics can be precisely and systemically delivered to reduce tumor growth in vivo, without harming healthy cells. Given the clinical applicability of peptide-based therapeutics, targeted delivery of nanocarriers loaded with therapeutic cargos seems plausible. We propose a modular design of a functionalized protocell in which a tumor-targeting moiety, such as a peptide or recombinant human antibody single chain variable fragment (scFv), is conjugated to a lipid bilayer surrounding a silica-based nanocarrier core containing a protected therapeutic cargo. The functionalized protocell can be tailored to a specific cancer subtype and treatment regimen by exchanging the tumor-targeting moiety and/or therapeutic cargo or used in combination to create unique, theranostic agents. In this review, we summarize the identification of tumor-specific receptors through combinatorial phage display technology and the use of antibody display selection to identify recombinant human scFvs against these tumor-specific receptors. We compare the characteristics of different types of simple and complex nanocarriers, and discuss potential types of therapeutic cargos and conjugation strategies. The modular design of functionalized protocells may improve the efficacy and safety of nanomedicines for future cancer therapy.

Accurate rational approximations of the Fermi-Dirac distribution are a useful component in many numerical algorithms for electronic structure calculations. The best known approximations use O(log(βΔ)log(-1)) poles to achieve an error tolerance at temperature β-1 over an energy interval Δ. We apply minimax approximation to reduce the number of poles by a factor of four and replace Δ with Δocc, the occupied energy interval. This is particularly beneficial when Δ ≫ Δocc, such as in electronic structure calculations that use a large basis set.

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality.

An understanding of the mechanical and optical properties of lithium fluoride (LiF) is essential to its use as a transparent tamper and window for dynamic materials experiments. In order to improve models for this material, we applied iterative Lagrangian analysis to ten independent sets of data from magnetically driven planar shockless compression experiments on single crystal [100] LiF to pressures as high as 350 GPa. We found that the compression response disagreed with a prevalent tabular equation of state for LiF that is commonly used to interpret shockless compression experiments. We also present complementary data from ab initio calculations performed using the diffusion quantum Monte Carlo method. The agreement between these two data sets lends confidence to our interpretation. In order to aid in future experimental analysis, we have modified the tabular equation of state to match the new data. We have also extended knowledge of the optical properties of LiF via shock-compression and shockless compression experiments, refining the transmissibility limit, measuring the refractive index to ∼300 GPa, and confirming the nonlinear dependence of the refractive index on density. We present a new model for the refractive index of LiF that includes temperature dependence and describe a procedure for correcting apparent velocity to true velocity for dynamic compression experiments.

The increasing complexity of both scientific simulations and high-performance computing system architectures are driving the need for adaptive workflows, in which the composition and execution of computational and data manipulation steps dynamically depend on the evolutionary state of the simulation itself. Consider, for example, the frequency of data storage. Critical phases of the simulation should be captured with high frequency and with high fidelity for postanalysis; however, we cannot afford to retain the same frequency for the full simulation due to the high cost of data movement. We can instead look for triggers, indicators that the simulation will be entering a critical phase, and adapt the workflow accordingly. In this paper, we present a methodology for detecting triggers and demonstrate its use in the context of direct numerical simulations of turbulent combustion using S3D. We show that chemical explosive mode analysis (CEMA) can be used to devise a noise-tolerant indicator for rapid increase in heat release. However, exhaustive computation of CEMA values dominates the total simulation, and thus is prohibitively expensive. To overcome this computational bottleneck, we propose a quantile sampling approach. Our sampling-based algorithm comes with provable error/confidence bounds, as a function of the number of samples. Most importantly, the number of samples is independent of the problem size, and thus our proposed sampling algorithm offers perfect scalability. Our experiments on homogeneous charge compression ignition and reactivity controlled compression ignition simulations show that the proposed method can detect rapid increases in heat release, and its computational overhead is negligible. Our results will be used to make dynamic workflow decisions regarding data storage and mesh resolution in future combustion simulations.

Independent verification and quantification of fossil fuel (FF) emissions constitutes a considerable scientific challenge. By coupling atmospheric observations of CO2 with models of atmospheric transport, inverse models offer the possibility of overcoming this challenge. However, disaggregating the biospheric and FF flux components of terrestrial fluxes from CO2 concentration measurements has proven to be difficult, due to observational and modeling limitations. In this study, we propose a statistical inverse modeling scheme for disaggregating winter time fluxes on the basis of their unique error covariances and covariates, where these covariances and covariates are representative of the underlying processes affecting FF and biospheric fluxes. The application of the method is demonstrated with one synthetic and two real data prototypical inversions by using in situ CO2 measurements over North America. Inversions are performed only for the month of January, as predominance of biospheric CO2 signal relative to FF CO2 signal and observational limitations preclude disaggregation of the fluxes in other months. The quality of disaggregation is assessed primarily through examination of a posteriori covariance between disaggregated FF and biospheric fluxes at regional scales. Findings indicate that the proposed method is able to robustly disaggregate fluxes regionally at monthly temporal resolution with a posteriori cross covariance lower than 0.15 µmolm-2 s-1 between FF and biospheric fluxes. Error covariance models and covariates based on temporally varying FF inventory data provide a more robust disaggregation over static proxies (e.g., nightlight intensity and population density). However, the synthetic data case study shows that disaggregation is possible even in absence of detailed temporally varying FF inventory data.

Single phase performance and appealing thermo-physical properties make supercritical carbon dioxide (s-CO2) a good heat transfer fluid candidate for concentrating solar power (CSP) technologies. The development of a solar receiver capable of delivering s-CO2 at outlet temperatures ∼973 K is required in order to merge CSP and s-CO2 Brayton cycle technologies. A coupled optical and thermal-fluid modeling effort for a tubular receiver is undertaken to evaluate the direct tubular s-CO2 receiver's thermal performance when exposed to a concentrated solar power input of ∼0.3–0.5 MW. Ray tracing, using SolTrace, is performed to determine the heat flux profiles on the receiver and computational fluid dynamics (CFD) determines the thermal performance of the receiver under the specified heating conditions. An in-house MATLAB code is developed to couple SolTrace and ANSYS Fluent. CFD modeling is performed using ANSYS Fluent to predict the thermal performance of the receiver by evaluating radiation and convection heat loss mechanisms. Understanding the effects of variation in heliostat aiming strategy and flow configurations on the thermal performance of the receiver was achieved through parametric analyses. A receiver thermal efficiency ∼85% was predicted and the surface temperatures were observed to be within the allowable limit for the materials under consideration.

A supercritical carbon dioxide (sCO2) Brayton cycle is an emerging high energy-density cycle undergoing extensive research due to the appealing thermo-physical properties of sCO2 and single phase operation. Development of a solar receiver capable of delivering sCO2 at 20 MPa and 700 °C is required for implementation of the high efficiency (∼50%) solar powered sCO2 Brayton cycle. In this work, extensive candidate materials are review along with tube size optimization using the ASME Boiler and Pressure Vessel Code. Temperature and pressure distribution obtained from the thermal-fluid modeling (presented in a complementary publication) are used to evaluate the thermal and mechanical stresses along with detailed creep-fatigue analysis of the tubes. The resulting body stresses were used to approximate the lifetime performance of the receiver tubes. A cyclic loading analysis is performed by coupling the Strain-Life approach and the Larson-Miller creep model. The structural integrity of the receiver was examined and it was found that the stresses can be withstood by specific tubes, determined by a parametric geometric analysis. The creep-fatigue analysis displayed the damage accumulation due to cycling and the permanent deformation on the tubes showed that the tubes can operate for the full lifetime of the receiver.

In this paper, we argue that information theoretic measures may provide a robust, broadly applicable, repeatable metric to assess how a system enables people to reduce high-dimensional data into topically relevant subsets of information. Explosive growth in electronic data necessitates the development of systems that balance automation with human cognitive engagement to facilitate pattern discovery, analysis and characterization, variously described as "cognitive augmentation" or "insight generation." However, operationalizing the concept of insight in any measurable way remains a difficult challenge for visualization researchers. The "golden ticket" of insight evaluation would be a precise, generalizable, repeatable, and ecologically valid metric that indicates the relative utility of a system in heightening cognitive performance or facilitating insights. Unfortunately, the golden ticket does not yet exist. In its place, we are exploring information theoretic measures derived from Shannon's ideas about information and entropy as a starting point for precise, repeatable, and generalizable approaches for evaluating analytic tools. We are specifically concerned with needle-in-haystack workflows that require interactive search, classification, and reduction of very large heterogeneous datasets into manageable, task-relevant subsets of information. We assert that systems aimed at facilitating pattern discovery, characterization and analysis - i.e., "insight" - must afford an efficient means of sorting the needles from the chaff; and simple compressibility measures provide a way of tracking changes in information content as people shape meaning from data.

Double-shell Ar gas puff implosions driven by 16.5±0.5 MA on the Z generator at Sandia National Laboratories are very effective emitters of Ar K-shell radiation (photon energy >3 keV), producing yields of 330 ± 9% kJ (B. Jones et al., Phys. Plasmas, 22, 020706, 2015). In addition, previous simulations and experiments have reported dramatic increases in K-shell yields when adding an on-axis jet to double shell gas puffs for some configurations.

Least-squares Petrov–Galerkin (LSPG) model-reduction techniques such as the Gauss–Newton with Approximated Tensors (GNAT) method have shown promise, as they have generated stable, accurate solutions for large-scale turbulent, compressible flow problems where standard Galerkin techniques have failed. Furthermore, there has been limited comparative analysis of the two approaches. This is due in part to difficulties arising from the fact that Galerkin techniques perform optimal projection associated with residual minimization at the time-continuous level, while LSPG techniques do so at the time-discrete level. This work provides a detailed theoretical and computational comparison of the two techniques for two common classes of time integrators: linear multistep schemes and Runge–Kutta schemes. We present a number of new findings, including conditions under which the LSPG ROM has a time-continuous representation, conditions under which the two techniques are equivalent, and time-discrete error bounds for the two approaches. Perhaps most surprisingly, we demonstrate both theoretically and computationally that decreasing the time step does not necessarily decrease the error for the LSPG ROM; instead, the time step should be ‘matched’ to the spectral content of the reduced basis. In numerical experiments carried out on a turbulent compressible-flow problem with over one million unknowns, we show that increasing the time step to an intermediate value decreases both the error and the simulation time of the LSPG reduced-order model by an order of magnitude.

A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that the effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.

One of the greatest challenges with lithium-oxygen batteries involves identifying catalysts that facilitate the growth and evolution of cathode species on an oxygen electrode. Heterogeneous solid catalysts cannot adequately address the problematic overpotentials when the surfaces become passivated. However, there exists a class of biomolecules which have been designed by nature to guide complex solution-based oxygen chemistries. Here, we show that the heme molecule, a common porphyrin cofactor in blood, can function as a soluble redox catalyst and oxygen shuttle for efficient oxygen evolution in non-aqueous Li-O2 batteries. The heme's oxygen binding capability facilitates battery recharge by accepting and releasing dissociated oxygen species while benefiting charge transfer with the cathode. We reveal the chemical change of heme redox molecules where synergy exists with the electrolyte species. This study brings focus to the rational design of solution-based catalysts and suggests a sustainable cross-link between biomolecules and advanced energy storage.

ConspectusA nanometer thick passivation layer will spontaneously form on Li-metal in battery applications due to electrolyte reduction reactions. This passivation layer in rechargeable batteries must have "selective" transport properties: blocking electrons from attacking the electrolytes, while allowing Li+ ion to pass through so the electrochemical reactions can continue. The classical description of the electrochemical reaction, Li+ + e → Li0, occurring at the Li-metal|electrolyte interface is now complicated by the passivation layer and will reply on the coupling of electronic and ionic degrees of freedom in the layer. This passivation layer is called "solid electrolyte interphase (SEI)" and is considered as "the most important but the least understood in rechargeable Li-ion batteries," partly due to the lack of understanding of its structure-property relationship. Predictive modeling, starting from the ab initio level, becomes an important tool to understand the nanoscale processes and materials properties governing the interfacial charge transfer reaction at the Li-metal|SEI|electrolyte interface.Here, we demonstrate pristine Li-metal surfaces indeed dissolve in organic carbonate electrolytes without the SEI layer. Based on joint modeling and experimental results, we point out that the well-known two-layer structure of SEI also exhibits two different Li+ ion transport mechanisms. The SEI has a porous (organic) outer layer permeable to both Li+ and anions (dissolved in electrolyte), and a dense (inorganic) inner layer facilitate only Li+ transport. This two-layer/two-mechanism diffusion model suggests only the dense inorganic layer is effective at protecting Li-metal in electrolytes. This model suggests a strategy to deconvolute the structure-property relationships of the SEI by analyzing an idealized SEI composed of major components, such as Li2CO3, LiF, Li2O, and their mixtures. After sorting out the Li+ ion diffusion carriers and their diffusion pathways, we design methods to accelerate the Li+ ion conductivity by doping and by using heterogonous structure designs. We will predict the electron tunneling barriers and connect them with measurable first cycle irreversible capacity loss. Finally, we note that the SEI not only affects Li+ and e- transport, but it can also impose a potential drop near the Li-metal|SEI interface. Our challenge is to fully describe the electrochemical reactions at the Li-metal|SEI|electrolyte interface. This will be the subject of ongoing efforts.

Here, the Criegee intermediate acetone oxide, (CH₃)₂COO, is formed by laser photolysis of 2,2-diiodopropane in the presence of O₂ and characterized by synchrotron photoionization mass spectrometry and by cavity ring-down ultraviolet absorption spectroscopy. The rate coefficient of the reaction of the Criegee intermediate with SO₂ was measured using photoionization mass spectrometry and pseudo-first-order methods to be (7.3 ± 0.5) × 10^–11 cm³ s^–1 at 298 K and 4 Torr and (1.5 ± 0.5) × 10^–10 cm³ s^–1 at 298 K and 10 Torr (He buffer). These values are similar to directly measured rate coefficients of anti-CH₃CHOO with SO₂, and in good agreement with recent UV absorption measurements. The measurement of this reaction at 293 K and slightly higher pressures (between 10 and 100 Torr) in N₂ from cavity ring-down decay of the ultraviolet absorption of (CH₃)₂COO yielded even larger rate coefficients, in the range (1.84 ± 0.12) × 10^–10 to (2.29 ± 0.08) × 10^–10 cm³ s^–1. Photoionization mass spectrometry measurements with deuterated acetone oxide at 4 Torr show an inverse deuterium kinetic isotope effect, k_H/k_D = (0.53 ± 0.06), for reactions with SO₂, which may be consistent with recent suggestions that the formation of an association complex affects the rate coefficient. The reaction of (CD3)2COO with NO2 has a rate coefficient at 298 K and 4 Torr of (2.1 ± 0.5) × 10^–12 cm³ s^–1 (measured with photoionization mass spectrometry), again similar to rate for the reaction of anti-CH₃CHOO with NO₂. Cavity ring-down measurements of the acetone oxide removal without added reagents display a combination of first- and second-order decay kinetics, which can be deconvolved to derive values for both the self-reaction of (CH₃)₂COO and its unimolecular thermal decay. The inferred unimolecular decay rate coefficient at 293 K, (305 ± 70) s^–1, is similar to determinations from ozonolysis. The present measurements confirm the large rate coefficient for reaction of (CH₃)₂COO with SO₂ and the small rate coefficient for its reaction with water. Product measurements of the reactions of (CH₃)₂COO with NO₂ and with SO₂ suggest that these reactions may facilitate isomerization to 2-hydroperoxypropene, possibly by subsequent reactions of association products.

A terahertz vertical-external-cavity surface-emitting-laser (VECSEL) is demonstrated using an active focusing reflectarray metasurface based on quantum-cascade gain material. The focusing effect enables a hemispherical cavity with flat optics, which exhibits higher geometric stability than a plano-plano cavity and a directive and circular neardiffraction limited Gaussian beam with M2 beam parameter as low as 1.3 and brightness of 1.86 × 106 Wsr-1m-2. This work initiates the potential of leveraging inhomogeneous metasurface and reflectarray designs to achieve high-power and high-brightness terahertz quantum-cascade VECSELs.

Internal damage has been experimentally observed in aluminum (Al)/silicon carbide (SiC) multilayer coatings subject to nanoindentation loading. Post-indentation characterization has identified that delamination at the coating/substrate interface is the most prominent form of damage. In this study the finite element method is employed to study the effect of delamination on indentation-derived hardness and Young's modulus. The model features alternating Al/SiC nanolayers above a silicon (Si) substrate, in consistence with the actual material system used in earlier experiments. Cohesive elements with a traction–separation relationship are used to facilitate delamination along the coating/substrate interface. Delamination is observed numerically to be sensitive to the critical normal and shear stresses that define the cohesive traction–separation behavior. Axial tensile stress below the edge of indentation contact is found to be the largest contributor to damage initiation and evolution. Delamination results in a decrease in both indentation-derived hardness and Young's modulus. A unique finding is that delamination can occur during the unloading process of indentation, depending on the loading condition and critical tractions.

Here, we present the results of an application of Bayesian inference and maximum entropy methods for the estimation of the joint probability density for the Arrhenius rate para meters of the rate coefficient of the H₂/O₂-mechanism chain branching reaction H + O₂ → OH + O. Available published data is in the form of summary statistics in terms of nominal values and error bars of the rate coefficient of this reaction at a number of temperature values obtained from shock-tube experiments. Our approach relies on generating data, in this case OH concentration profiles, consistent with the given summary statistics, using Approximate Bayesian Computation methods and a Markov Chain Monte Carlo procedure. The approach permits the forward propagation of parametric uncertainty through the computational model in a manner that is consistent with the published statistics. A consensus joint posterior on the parameters is obtained by pooling the posterior parameter densities given each consistent data set. To expedite this process, we construct efficient surrogates for the OH concentration using a combination of Pad'e and polynomial approximants. These surrogate models adequately represent forward model observables and their dependence on input parameters and are computationally efficient to allow their use in the Bayesian inference procedure. We also utilize Gauss-Hermite quadrature with Gaussian proposal probability density functions for moment computation resulting in orders of magnitude speedup in data likelihood evaluation. Despite the strong non-linearity in the model, the consistent data sets all res ult in nearly Gaussian conditional parameter probability density functions. The technique also accounts for nuisance parameters in the form of Arrhenius parameters of other rate coefficients with prescribed uncertainty. The resulting pooled parameter probability density function is propagated through stoichiometric hydrogen-air auto-ignition computations to illustrate the need to account for correlation among the Arrhenius rate parameters of one reaction and across rate parameters of different reactions.

A three-dimensional (3D) Dirac semimetal (DS) is an analogue of graphene, but with linear energy dispersion in all (three) momentum directions. 3D DSs have been a fertile playground in discovering novel quantum particles, for example Weyl fermions, in solid state systems. Many 3D DSs were theoretically predicted and experimentally confirmed. We report here the results in exfoliated ZrTe 5 thin flakes from the studies of aberration-corrected scanning transmission electron microscopy and low temperature magneto-transport measurements. Several unique results were observed. First, a π Berry phase was obtained from the Landau fan diagram of the Shubnikov-de Haas oscillations in the longitudinal conductivity σxx. Second, the longitudinal resistivity ρxx shows a linear magnetic field dependence in the quantum limit regime. Most surprisingly, quantum oscillations were also observed at fractional Landau level indices N = 5/3 and 7/5, demonstrating strong electron-electron interaction effects in ZrTe5.

The coupled dynamics of entangled polymers, which span broad time and length scales, govern their unique viscoelastic properties. To follow chain mobility by numerical simulations from the intermediate Rouse and reptation regimes to the late time diffusive regime, highly coarse grained models with purely repulsive interactions between monomers are widely used since they are computationally the most efficient. Here using large scale molecular dynamics simulations, the effect of including the attractive interaction between monomers on the dynamics of entangled polymer melts is explored for the first time over a wide temperature range. Attractive interactions have little effect on the local packing for all temperatures T and on the chain mobility for T higher than about twice the glass transition Tg. These results, across a broad range of molecular weight, show that to study the dynamics of entangled polymer melts, the interactions can be treated as pure repulsive, confirming a posteriori the validity of previous studies and opening the way to new large scale numerical simulations.

The interaction of solvent molecules with metallic surfaces impacts many interfacial chemical processes. We investigate the chemical and structure evolution that follows adsorption of the polar solvent dimethylformamide (DMF) on Ag(111). An Ag(DMF)2 coordination complex forms spontaneously by DMF etching of Ag(111), yielding mixed films of the complexes and DMF. Utilizing ultrahigh vacuum scanning tunneling microscopy (UHV-STM), in combination with X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) computations, we map monolayer phases from the 2-D gas regime, consisting of a binary mixture of DMF and Ag(DMF)2, through the saturation monolayer limit, in which these two chemical species phase separate into ordered islands. Structural models for the near-square DMF phase and the chain-like Ag(DMF)2 phase are presented and supported by DFT computation. Interface evolution is summarized in a surface pressure-composition phase diagram, which allows structure prediction over arbitrary experimental conditions. This work reveals new surface coordination chemistry for an important electrolyte-electrode system and illustrates how surface pressure can be used to tune monolayer phases.

This work provides new temperature-dependent mole fractions of elusive intermediates relevant to the low-temperature oxidation of dimethyl ether (DME). It extends the previous study of Moshammer et al. [J. Phys. Chem. A 2015, 119, 7361-7374 ] in which a combination of a jet-stirred reactor and molecular beam mass spectrometry with single-photon ionization via tunable synchrotron-generated vacuum-ultraviolet radiation was used to identify (but not quantify) several highly oxygenated species. Here, temperature-dependent concentration profiles of 17 components were determined in the range of 450-1000 K and compared to up-to-date kinetic modeling results. Special emphasis is paid toward the validation and application of a theoretical method for predicting photoionization cross sections that are hard to obtain experimentally but essential to turn mass spectral data into mole fraction profiles. The presented approach enabled the quantification of the hydroperoxymethyl formate (HOOCH2OCH2O), which is a key intermediate in the low-temperature oxidation of DME. The quantification of this keto-hydroperoxide together with the temperature-dependent concentration profiles of other intermediates including H2O2, HCOOH, CH3OCHO, and CH3OOH reveals new opportunities for the development of a next-generation DME combustion chemistry mechanism.

Surface and color codes are two forms of topological quantum error correction in two spatial dimensions with complementary properties. Surface codes have lower-depth error detection circuits and well-developed decoders to interpret and correct errors, while color codes have transversal Clifford gates and better code efficiency in the number of physical qubits needed to achieve a given code distance. A formal equivalence exists between color codes and folded surface codes, but it does not guarantee the transferability of any of these favorable properties. However, the equivalence does imply the existence of constant-depth circuit implementations of logical Clifford gates on folded surface codes. We achieve and improve this result by constructing two families of folded surface codes with transversal Clifford gates. This construction is presented generally for qudits of any dimension. The specific application of these codes to universal quantum computation based on qubit fusion is also discussed.

The design and engineering of the size, shape, and chemistry of photoactive building blocks enables the fabrication of functional nanoparticles for applications in light harvesting, photocatalytic synthesis, water splitting, phototherapy, and photodegradation. Here, we report the synthesis of such nanoparticles through a surfactant-assisted interfacial self-assembly process using optically active porphyrin as a functional building block. The self-assembly process relies on specific interactions such as π-π stacking and metalation (metal atoms and ligand coordination) between individual porphyrin building blocks. Depending on the kinetic conditions and type of surfactants, resulting structures exhibit well-defined one- to three-dimensional morphologies such as nanowires, nanooctahedra, and hierarchically ordered internal architectures. Specifically, electron microscopy and X-ray diffraction results indicate that these nanoparticles exhibit stable single-crystalline and nanoporous frameworks. Due to the hierarchical ordering of the porphyrins, the nanoparticles exhibit collective optical properties resulted from coupling of molecular porphyrins and photocatalytic activities such as photodegradation of methyl orange (MO) pollutants and hydrogen production.

Nanosecond electrical explosion of fine metal wires in vacuum generates calibrated, radially expanded gas cylinders of metal atoms surrounded by a low-density fast expanding plasma corona. An integrated-phase technique, based on laser interferometry, provides the dynamic dipole polarizability of metal atoms. These data were previously unavailable for tungsten atoms. An extremely high melting temperature and significant premelt electronic emission make these measurements particularly complicated for this refractory metal. Most attempts to vaporize tungsten wire by electrical current pulse result in the disintegration of the sample into macro- and microfragments. However, application of a very fast-rising current, ∼1kA/ns, can vaporize a thin 10-15 μm-diameter tungsten wire and generate a calibrated gas-plasma cylinder. Adding a dielectric coating to the wire leads to increased energy deposition to the wire core and a reduction of the surrounding plasma corona. Employing the integrated-phase technique on a fast-exploding coated tungsten wire, we find that the dynamic dipole polarizability of tungsten atoms at a wavelength of 532 nm equals 15±1.3Å3.

Surface and color codes are two forms of topological quantum error correction in two spatial dimensions with complementary properties. Surface codes have lower-depth error detection circuits and well-developed decoders to interpret and correct errors, while color codes have transversal Clifford gates and better code efficiency in the number of physical qubits needed to achieve a given code distance. A formal equivalence exists between color codes and folded surface codes, but it does not guarantee the transferability of any of these favorable properties. However, the equivalence does imply the existence of constant-depth circuit implementations of logical Clifford gates on folded surface codes. We achieve and improve this result by constructing two families of folded surface codes with transversal Clifford gates. This construction is presented generally for qudits of any dimension. Lastly, the specific application of these codes to universal quantum computation based on qubit fusion is also discussed.

We designed a dichroic beam combiner coating with 11 HfO₂/SiO₂ layer pairs and deposited it on a large substrate. It provides high transmission (HT) at 527 nm and high reflection (HR) at 1054 nm for a 22.5-deg angle of incidence (AOI), S polarization (Spol), and uses near half-wave layer thicknesses for HT at 527 nm, modified for HR at 1054 nm. The two options for the beam combiner each require that a high intensity beam be incident on the coating from within the substrate (from glass). We analyze the laser-induced damage threshold (LIDT) differences between the two options in terms of the 527- and 1054-nm E-field behaviors for air → coating and glass → coating incidences. This indicates that LIDTs should be higher for air → coating than for glass → coating incidence. LIDT tests at the use AOI, Spol with ns pulses at 532 and 1064 nm confirm this, with glass → coating LIDTs about half that of air → coating LIDTs. Lastly, these results clearly indicate that the best beam combiner option is for the high intensity 527 and 1054 nm beams to be incident on the coating from air and glass, respectively.

We present the design and expected performance of a proof-of-concept 32 channel material identification system. Our system is based on the energy-dependent attenuation of fast neutrons for four elements: hydrogen, carbon, nitrogen and oxygen. We describe a new approach to obtaining a broad range of neutron energies to probe a sample, as well as our technique for reconstructing the molar densities within a sample. The system's performance as a function of time-of-flight energy resolution is explored using a Geant4-based Monte Carlo. Our results indicate that, with the expected detector response of our system, we will be able to determine the molar density of all four elements to within a 20–30% accuracy in a two hour scan time. In many cases this error is systematically low, thus the ratio between elements is more accurate. This degree of accuracy is enough to distinguish, for example, a sample of water from a sample of pure hydrogen peroxide: the ratio of oxygen to hydrogen is reconstructed to within 8±0.5% of the true value. Finally, with future algorithm development that accounts for backgrounds caused by scattering within the sample itself, the accuracy of molar densities, not ratios, may improve to the 5–10% level for a two hour scan time.

Recent field experiments conducted in the near wake (up to 0.5 rotor diameters downwind of the rotor) of a Clipper Liberty C96 2.5 MW wind turbine using snow-based super-large-scale particle image velocimetry (SLPIV) (Hong et al., Nat. Commun., vol. 5, 2014, 4216) were successful in visualizing tip vortex cores as areas devoid of snowflakes. The so-visualized snow voids, however, suggested tip vortex cores of complex shape consisting of circular cores with distinct elongated comet-like tails. We employ large-eddy simulation (LES) to elucidate the structure and dynamics of the complex tip vortices identified experimentally. We show that the LES, with inflow conditions representing as closely as possible the state of the flow approaching the turbine when the SLPIV experiments were carried out, reproduce vortex cores in good qualitative agreement with the SLPIV results, essentially capturing all vortex core patterns observed in the field in the tip shear layer. The computed results show that the visualized vortex patterns are formed by the tip vortices and a second set of counter-rotating spiral vortices intertwined with the tip vortices. To probe the dependence of these newly uncovered coherent flow structures on turbine design, size and approach flow conditions, we carry out LES for three additional turbines: (i) the Scaled Wind Farm Technology (SWiFT) turbine developed by Sandia National Laboratories in Lubbock, TX, USA; (ii) the wind turbine developed for the European collaborative Mexico (Model Experiments in Controlled Conditions) project; and (iii) the model turbine presented in the paper by Lignarolo et al. (J. Fluid Mech., vol. 781, 2015, pp. 467-493), and the Clipper turbine under varying inflow turbulence conditions. We show that similar counter-rotating vortex structures as those observed for the Clipper turbine are also observed for the SWiFT, Mexico and model wind turbines. However, the strength of the counter-rotating vortices relative to that of the tip vortices from the model turbine is significantly weaker. We also show that incoming flows with low level turbulence attenuate the elongation of the tip and counter-rotating vortices. Sufficiently high turbulence levels in the incoming flow, on the other hand, tend to break up the coherence of spiral vortices in the near wake. To elucidate the physical mechanism that gives rise to such rich coherent dynamics we examine the stability of the turbine tip shear layer using the theory proposed by Leibovich & Stewartson (J. Fluid Mech., vol. 126, 1983, pp. 335-356). We show that for all simulated cases the theory consistently indicates the flow to be unstable exactly in the region where counter-rotating spirals emerge. We thus postulate that centrifugal instability of the rotating turbine tip shear layer is a possible mechanism for explaining the phenomena we have uncovered herein.

SIERRA/Aero is a two and three dimensional, node-centered, edge-based finite volume code that approximates the compressible Navier-Stokes equations on unstructured meshes. It is applicable to inviscid and high Reynolds number laminar and turbulent flows. Currently, two classes of turbulence models are provided: Reynolds Averaged Navier-Stokes (RANS) and hybrid methods such as Detached Eddy Simulation (DES). Large Eddy Simulation (LES) models are currently under development. The gas may be modeled either as ideal, or as a non-equilibrium, chemically reacting mixture of ideal gases. This document describes the mathematical models contained in the code, as well as certain implementation details. First, the governing equations are presented, followed by a description of the spatial discretization. Next, the time discretization is described, and finally the boundary conditions. Throughout the document, SIERRA/ Aero is referred to simply as Aero for brevity.

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment. In the definitions of the commands that follow, the term Real_Max denotes the largest floating point value that can be represented on a given computer. Int_Max is the largest such integer value.

The SIERRA Low Mach Module: Fuego along with the SIERRA Participating Media Radiation Module: Syrinx, henceforth referred to as Fuego and Syrinx, respectively, are the key elements of the ASCI fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Syrinx represents the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

The SIERRA Low Mach Module: Fuego along with the SIERRA Participating Media Radiation Module: Syrinx, henceforth referred to as Fuego and Syrinx, respectively, are the key elements of the ASCI fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Syrinx represents the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

The Encore software package is both a stand-alone application and a software library. This guide explains the syntax of Encore input, provides examples, and is a comprehensive catalog of the Encore commands. Acting as a stand-alone application, Encore provides utilities for reading solutions from files and enables solution verification, postprocessing, field transfers, and basic mesh refinement. Acting as a software library, Encore is a component of the fluid, thermal, and solid modeling applications in the Sierra Mechanics suite. As a library, Encore provides the enclosing modeling application a superset of the stand-alone capabilities—enabled by application specific information—including physics specific postprocessors and adaptive mesh refinement.

The challenge to create efficient market clearing prices in centralized day-ahead electricity markets arises from inherent non-convexities in unit commitment problems. When this aspect is ignored, marginal prices may result in economic losses to market participants who are part of the welfare maximizing solution. In this essay, we present an axiomatic approach to efficient prices and cost allocation for a revenue neutral and non-confiscatory day-ahead market. Current cost allocation practices do not adequately attribute costs based on transparent cost causation criteria. Instead we propose an ex post multi-part pricing scheme, which we refer to as the Dual Pricing Algorithm. Lastly, our approach can be incorporated into current dayahead markets without altering the market equilibrium.

This document describes the theoretical foundation of thermal analysis in Sierra Mechanics. The SIERRA Multimechanics Module: Aria, henceforth referred to as Aria for brevity, was developed at Sandia National Laboratories under the ASC program, and approximates linear and nonlinear continuum models of heat transfer. Aria uses the SIERRA Framework, which provides data management services commonly required by computational mechanics software, and facilitates the development of coupled, multi-mechanics applications for massively parallel computers. The mathematical models in Aria are based heavily on those of COYOTE, a well-established thermal analysis program that was also developed at Sandia and its ASC code predecessor, Calore. Aria, Calore and COYOTE share a significant body of numerical methods, which are described in detail by Reddy and Gartling. Throughout this document, the terms software and implementation are synonymous with the Aria thermal-fluid analysis computer program.

This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included.

Carrier transport and recombination are modeled for a heterojunction diode containing irradiation defects. Detailed attention is given to the role of band-to-trap tunneling and how it is affected by band offsets at the junction. Tunneled states are characterized by numerical solution of the one-band effective-mass envelope equation. The interaction with traps is treated assuming capture by the multi-phonon-emission mechanism. It is shown that tunneling can increase carrier recombination at defects by orders of magnitude in the presence of large band offsets. This explains why Npn InGaP/GaAs/GaAs heterojunction bipolar transistors with displacement damage from energetic-particle irradiation are observed to have high carrier recombination in the emitter-base depletion region.

A multigrid method is proposed that combines ideas from matrix dependent multigrid for structured grids and algebraic multigrid for unstructured grids. It targets problems where a three-dimensional mesh can be viewed as an extrusion of a two-dimensional, unstructured mesh in a third dimension. Our motivation comes from the modeling of thin structures via finite elements and, more specifically, the modeling of ice sheets. Extruded meshes are relatively common for thin structures and often give rise to anisotropic problems when the thin direction mesh spacing is much smaller than the broad direction mesh spacing. Within our approach, the first few multigrid hierarchy levels are obtained by applying matrix dependent multigrid to semicoarsen in a structured thin direction fashion. After sufficient structured coarsening, the resulting mesh contains only a single layer corresponding to a two-dimensional, unstructured mesh. Algebraic multigrid can then be employed in a standard manner to create further coarse levels, as the anisotropic phenomena is no longer present in the single layer problem. The overall approach remains fully algebraic, with the minor exception that some additional information is needed to determine the extruded direction. Furthermore, this facilitates integration of the solver with a variety of different extruded mesh applications.

Lead halide perovskites are increasingly considered for applications beyond photovoltaics, for example, light emission and detection, where an ability to pattern and prototype microscale geometries can facilitate the incorporation of this class of materials into devices. Here we demonstrate laser direct write of lead halide perovskites, a remarkably simple procedure that takes advantage of the inverse dependence between perovskite solubility and temperature by using a laser to induce localized heating of an absorbing substrate. We demonstrate arbitrary pattern formation of crystalline CH3NH3PbBr3 on a range of substrates and fabricate and characterize a microscale photodetector using this approach. This direct write methodology provides a path forward for the prototyping and production of perovskite-based devices.

The development of novel thermal sources that control the emission spectrum and the angular emission pattern is of fundamental importance. In this paper, we investigate the thermal emission properties of semiconductor hyperbolic metamaterials (SHMs). Our structure does not require the use of any periodic corrugation to provide monochromatic and directional emission properties. We show that these properties arise because of epsilon-near-zero conditions in SHMs. The thermal emission is dominated by the epsilon-near-zero effect in the doped quantum wells composing the SHM. Furthermore, different properties are observed for s and p polarizations, following the characteristics of the strong anisotropy of hyperbolic metamaterials.

Due to their high density of interfaces, nanostructured material are hypothesized to show a higher tolerance to radiation damage compared to conventional coarse-grained materials and are on interest for use in future nuclear reactors. In order to investigate the roles of vacancies, self-interstitials, and helium during defect accumulation, and the thermal evolution of such defects, a complex set of in situ TEM experiments were performed in nanocrystalline iron.

Sphingobium sp. SYK-6 is a soil bacterium boasting a well-studied ligninolytic pathway and the potential for development into a microbial chassis for lignin valorization. An improved understanding of its metabolism will help researchers in the engineering of SYK-6 for the production of value-added chemicals through lignin valorization. We used 13C-fingerprinting, 13C metabolic flux analysis (13C-MFA), and RNA-sequencing differential expression analysis to uncover the following metabolic traits: (i) SYK-6 prefers alkaline conditions, making it an efficient host for the consolidated bioprocessing of lignin, and it also lacks the ability to metabolize sugars or organic acids; (ii) the CO2 release (i.e., carbon loss) from the ligninolysis-based metabolism of SYK-6 is significantly greater than the CO2 release from the sugar-based metabolism of Escherichia coli; (iii) the vanillin catabolic pathway (which is the converging point of majority of the lignin catabolic pathways) is coupled with the tetrahydrofolate-dependent C1 pathway that is essential for the biosynthesis of serine, histidine, and methionine; (iv) catabolic end products of lignin (pyruvate and oxaloacetate) must enter the tricarboxylic acid (TCA) cycle first and then use phosphoenolpyruvate carboxykinase to initiate gluconeogenesis; and (v) 13C-MFA together with RNA-sequencing differential expression analysis establishes the vanillin catabolic pathway as the major contributor of NAD(P)H synthesis. Therefore, the vanillin catabolic pathway is essential for SYK-6 to obtain sufficient reducing equivalents for its healthy growth; cosubstrate experiments support this finding. This unique energy feature of SYK-6 is particularly interesting because most heterotrophs rely on the transhydrogenase, the TCA cycle, and the oxidative pentose phosphate pathway to obtain NADPH.

Our previous conference report on this instrument emphasized its use for fast-neutron imaging spectroscopy. We describe here its additional measurement capabilities, namely active interrogation, time-correlated pulse-height multiplication measurements, and gamma imaging.

Dual plane neutron scatter cameras have shown promise for localizing fast neutron sources. The condition that a neutron must scatter in both planes of the camera produces low counting efficiencies. Counting efficiency can be improved using an alternative design that uses a single, optically segmented volume of scintillation material. Using Geant4, we simulated pulses from neutron elastic scatter events at different locations throughout an EJ-204 scintillator bar. We used nonlinear regression on low light pulses to determine the position along the bar where the scatter event occurred.

Major advances in pulsed power technology and applications over the last twenty years have expanded the mission areas for pulsed power and created compelling new opportunities for the Stockpile Stewardship Program (SSP). This summary document is a forward look at the development of pulsed power science and technology (PPS&T) capabilities in support of the next 20 years of the SSP. This outlook was developed during a three month long tri-lab study on the future of PPS&T research and capabilities in support of applications to: (1) Dynamic Materials, (2) Thermonuclear Burn Physics and Inertial Confinement Fusion (ICF), and (3) Radiation Effects and Nuclear Survivability. It also considers necessary associated developments in next-generation codes and pulsed power technology as well as opportunities for academic, industry, and international engagement. The document identifies both imperatives and opportunities to address future SSP mission needs.

Tunable silicon microring resonators with small, integrated micro-heaters which exhibit a junction field effect were made using a conventional silicon-on-insulator (SOI) photonic foundry fabrication process. The design of the resistive tuning section in the microrings included a "pinched" p-n junction, which limited the current at higher voltages and inhibited damage even when driven by a pre-emphasized voltage waveform. Dual-ring filters were studied for both large (>4.9 THz) and small (850 GHz) free-spectral ranges. Thermal red-shifting was demonstrated with microsecond-scale time constants, e.g., a dual-ring filter was tuned over 25 nm in 0.6 μs 10%-90% transition time, and with efficiency of 3.2 μW/GHz.

Wind turbine loads predictions by blade-element momentum theory using the standard tip-loss correction have been shown to over-predict loading near the blade tip in comparison to experimental data. This over-prediction is theorized to be due to the assumption of light rotor loading, inherent in the standard tip-loss correction model of Glauert. A higher- order free-wake method, WindDVE, is used to compute the rollup process of the trailing vortex sheets downstream of wind turbine blades. Results obtained serve an exact correction function to the Glauert tip correction used in blade-element momentum methods. It is found that accounting for the effects of tip vortex rollup within the Glauert tip correction indeed results in improved prediction of blade tip loads computed by blade-element momentum methods.

Managing multi-level memories will require different policies from those used for cache hierarchies, as memory technologies differ in latency, bandwidth, and volatility. To this end we analyze application data allocations and main memory accesses to determine whether an application-driven approach to managing a multi-level memory system comprising stacked and conventional DRAM is viable. Our early analysis shows that the approach is viable, but some applications may require dynamic allocations (i.e., migration) while others are amenable to static allocation.

The time-correlated pulse-height (TCPH) distribution can be used to differentiate between multiplying (e.g 235U, 239Pu) and non-multiplying (e.g Am-Li, 252Cf) sources. In the past, this approach proved effective at characterizing the multiplication of alpha phase plutonium metal through a passive measurement. Recently, Sandia National Laboratories has completed a measurement campaign with its new Correlated Radiation Signature (CoRS) system involving active interrogation of highly enriched uranium (HEU) with an Am-Li source. An additional obstacle was introduced to the measurement configuration by shielding the HEU with depleted uranium (DU). Simulation results have proven Am-Li source to be a suitable interrogating source because of its relatively low-energy neutron spectrum. The TCPH distribution was successfully used to determine the presence of a multiplying medium inside DU shells. The correlation between multiplication and an empirical parameters broke down for externally driven configurations, but in all cases the presence of a multiplying source was detected.

To address the lack of knowledge of local solar variability, we have developed and deployed a low-cost solar variability datalogger (SVD). While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we present evaluation of various low-cost irradiance sensor types, describe the SVD, and present validation and comparison of the SVD collected data. The low cost and ease of use of the SVD will enable a greater understanding of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic (PV) installations and thus will encourage greater penetrations of solar energy.

We consider four-dimensional qudits as qubit pairs and their qudit Pauli operators as qubit Clifford operators. This introduces a nesting, C21 ⊂ C42 ⊂ C23, where Cmn is the nth level of the m-dimensional qudit Clifford hierarchy. If we can convert between logical qubits and qudits, then qudit Clifford operators are qubit non-Clifford operators. Conversion is achieved by qubit fusion and qudit fission using stabilizer circuits that consume a resource state. This resource is a fused qubit stabilizer state with a fault- tolerant state preparation using stabilizer circuits.

Alkali-free glasses, which exhibit high energy storage densities (~35 J/cc), present a unique opportunity to couple high temperature stability with high breakdown strength, and thus provide an avenue for capacitor applications with stringent temperature and power requirements. Realizing the potential of these materials in kilovolt class capacitors with >1 J/cc recoverable energy density requires novel packaging strategies that incorporate these extremely fragile dielectrics. In this paper, we demonstrate the feasibility of fabricating wound capacitors using 50-μm-thick glass. Two capacitors were fabricated from 2.8-m-long ribbons of thin (50 μm) glass wound into 125-140-mm-diameter spools. The capacitors exhibit a capacitance of 70-75 nF with loss tangents below 1%. The wound capacitors can operate up to 1 kV and show excellent temperature stability to 150 °C. By improving the end terminations, the self-resonance can be shifted to above 1 MHz, indicating that these materials may be useful for pulsed power applications with microsecond discharge times.

We characterize geomechanical constitutive behavior of reservoir sandstones at conditions simulating the “Cranfield” Southeast Regional Carbon Sequestration Partnership injection program. From two cores of Lower Tuscaloosa Formation, three sandstone lithofacies were identified for mechanical testing based on permeability and lithology. These include: chlorite-cemented conglomeratic sandstone (Facies A); quartz-cemented fine sandstone (Facies B); and quartz- and calcite-cemented very fine sandstone (Facies C). We performed a suite of compression tests for each lithofacies at 100 °C and pore pressure of 30 MPa, including hydrostatic compression and triaxial tests at several confining pressures. Plugs were saturated with supercritical CO2-saturated brine. Chemical environment affected the mechanical response of all three lithofacies, which experience initial plastic yielding at stresses far below estimated in situ stress. Measured elastic moduli degradation defines a secondary yield surface coinciding with in situ stress for Facies B and C. Facies A shows measurable volumetric creep strain and a failure envelope below estimates of in situ stress, linked to damage of chlorite cements by acidic pore solutions. The substantial weakening of a particular lithofacies by CO2 demonstrates a possible chemical-mechanical coupling during injection at Cranfield with implications for CO2 injection, reservoir permeability stimulation, and enhanced oil recovery.

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This monthly report is intended to communicate the status of North Slope ARM facilities managed by Sandia National Labs.

In order to accurately describe defect accumulation in heterogeneous microstructures and under complex irradiation conditions, simulation methods are needed that can explicitly account for the effect of nonhomogeneous microstructures on damage accumulation. In this project, an advanced simulation tool called spatially resolved stochastic cluster dynamics (SRSCD) is developed for this purpose. The proposed approach relies on solving spatially resolved coupled rate equations of standard cluster dynamics methods in a kinetic Monte Carlo scheme. Large-scale simulations of radiation damage in polycrystalline materials are enabled through several improvements made to this method, including a pseudo-adaptive meshing scheme for cascade implantation and implementation of this method in a synchronous parallel kinetic Monte Carlo framework.

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This Environmental Restoration Operations (ER) Consolidated Quarterly Report (ER Quarterly Report) provides the status of ongoing corrective action activities being implemented by Sandia National Laboratories, New Mexico (SNL/NM) for the April, May, and June 2016 quarterly reporting period.

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A model-scale wave tank test was conducted in the interest of improving control systems design of wave energy converters (WECs). The success of most control strategies is based directly upon the availability of a reduced-order model with the ability to capture the dynamics of the system with sufficient accuracy. For this reason, the test described in this report, which is the first in a series of planned tests on WEC controls, focused on system identification (system ID) and model validation.

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This document presents the facility-recommended characterization of the neutron, prompt gamma-ray, and delayed gamma-ray radiation fields in the Annular Core Research Reactor (ACRR) for the cadmium-polyethylene (CdPoly) bucket in the central cavity on the 32-inch pedestal at the core centerline. The designation for this environment is ACRR-CdPoly-CC-32-cl. The neutron, prompt gamma-ray, and delayed gamma-ray energy spectra, uncertainties, and covariance matrices are presented as well as radial and axial neutron and gamma-ray fluence profiles within the experiment area of the bucket. Recommended constants are given to facilitate the conversion of various dosimetry readings into radiation metrics desired by experimenters. Representative pulse operations are presented with conversion examples. Acknowledgements The authors wish to thank the Annular Core Research Reactor staff and the Radiation Metrology Laboratory staff for their support of this work. Also thanks to Drew Tonigan for helping field the activation experiments in ACRR, David Samuel for helping to finalize the drawings and get the parts fabricated, and Elliot Pelfrey for preparing the active dosimetry plots.

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Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number (Re < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

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This report documents conceptual design development for the Deep Borehole Field Test (DBFT), including test packages (simulated waste packages, not containing waste) and a system for demonstrating emplacement and retrieval of those packages in the planned Field Test Borehole (FTB). For the DBFT to have demonstration value, it must be based on conceptualization of a deep borehole disposal (DBD) system. This document therefore identifies key options for a DBD system, describes an updated reference DBD concept, and derives a recommended concept for the DBFT demonstration.

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In July, 2016, the Electric Power Research Institute and industry partners performed a field test at the Maine Yankee Nuclear Site, located near Wiscasset, Maine. The primary goal of the field test was to evaluate the use of robots in surveying the surface of an in-service interim storage canister within an overpack; however, as part of the demonstration, dust and soluble salt samples were collected from horizontal surfaces within the interim storage system. The storage system is a vertical system made by NAC International, consisting of a steel-lined concrete overpack containing a 304 stainless steel (SS) welded storage canister. The canister did not contain spent fuel but rather greater-than-class-C waste, which did not generate significant heat, limiting airflow through the storage system. The surfaces that were sampled for deposits included the top of the shield plug, the side of the canister, and a shelf at the bottom of the overpack, just below the level of the pillar on which the canister sits. The samples were sent to Sandia National Laboratories for analysis. This report summarizes the results of those analyses. Because the primary goal of the field test was to evaluate the use of robots in surveying the surface of the canister within the overpack, collection of dust samples was carried out in a qualitative fashion, using paper filters and sponges as the sampling media. The sampling focused mostly on determining the composition of soluble salts present in the dust. It was anticipated that a wet substrate would more effectively extract soluble salts from the surface that was sampled, so both the sponges and the filter paper were wetted prior to being applied to the surface of the metal. Sampling was accomplished by simply pressing the damp substrate against the metal surface for two minutes, and then removing it. It is unlikely that the sampling method quantitatively collected dust or salts from the metal surface; however, both substrates did extract a significant amount of material. The paper filters collected both particles, trapped within the cellulose fibers of the filter, and salts, while the sponges collected only the soluble salts, with very few particles. Upon delivery to Sandia, both collection media were analyzed using the same methods. The soluble salts were leached from the substrates and analyzed via ion chromatography, and insoluble minerals were analyzed by scanning electron microscopy and energy dispersive X-ray spectroscopy. The insoluble minerals were found to consist largely of terrestrially-derived mineral fragments, dominantly quartz and biotite. Large (mm-sized) aggregates of calcium carbonate, calcium silicate, and calcium aluminum silicate were also present. The aggregates had one flat, smooth surface and one well crystallized surface, and were interpreted to be efflorescence on the inside of the overpack and in the vent, formed by seepage of cement pore fluids through joints in the steel liner of the overpack. Such efflorescence was commonly observed during the boroscope inspection of the storage system at the site. The material may have flaked off and fallen to the point where the dust was collected, or may have brushed off onto the sponges when the robot was retrieved through the inlet vent. Chemical analysis showed that the soluble salts on the shield plug were Ca- and Na-rich, with lesser K and minor Mg; the anionic component was dominated by SO 4 and Cl, with minor amounts of NO 3 . The cation composition of the soluble salts from the overpack shelf and the canister surface was similar to the filter samples, but the anions differed significantly, being dominantly NO 3 with lesser Cl and only trace SO 4 . The salts appear to represent a mixture of sea-salts (probably partially converted to nitrates and sulfates by particle-gas conversion reactions) and continental salt aerosols. Ammonium, a common component in continental aerosols, was not observed and may have been lost by degassing from the canister surface or after collection during sample storage and transportation. The demonstration at Maine Yankee has shown that the robot and sampling method used for the test can successfully be used to collect soluble salts from metal surfaces within an interim storage system overpack. The results were consistent from sample to sample, suggesting that a representative sample of the soluble salts was being collected. However, it is unlikely that the salt samples collected here represent quantitative sampling of the salts on the surfaces evaluated; for that reason, chloride densities per unit area are not presented here. It should also be noted that the relevance to storage systems at the site that contain SNF may be limited, because a heat- generating canister will result in greater airflow through the overpack, affecting dust deposition rates and possibly salt compositions.

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Global nuclear energy has reached a critical juncture. The footprint of nuclear energy is growing and will continue to grow in coming decades to meet increasing global energy demands, desires for energy security, and mounting concerns about climate change. This growth includes construction of reactors in countries new to the nuclear energy enterprise, in addition to expansion of existing programs. The lack of operational experience coupled with weak regulatory systems in some countries raises the potential of a nuclear accident. The expansion of nuclear energy is also met with an increasingly complex threat environment, with threats to nuclear security from non-state actors as well as the continued risks of state proliferation. The trend towards increasingly digitized and networked nuclear facilities significantly expands operational uncertainty and adds complexity to implementing safeguards and security. These factors merit fresh consideration of potential safety, safeguards, security, and cyber (3SC) risks, as well as approaches for managing those risks in an integrated, sustainable, and internationally cooperative manner. In an effort to explore the emerging challenges and cooperative solutions to the global expansion of nuclear energy The George Washington University Elliott School of International Affairs and Sandia National Laboratories convened a group of more than thirty experts from government, national laboratories, non-government organizations, and academia on May 5th, 2016 at George Washington University to discuss these issues in a not-for-attribution environment.

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The subject of this report is the performance portability of the Aeras global atmosphere dynamical core (implemented within the Albany multi-physics code) to new and emerging architecture machines using the Kokkos library and programming model. We describe the process of refactoring the finite element assembly process for the 3D hydrostatic model in Aeras and highlight common issues associated with development on GPU architectures. After giving detailed build and execute instructions for Aeras with MPI, OpenMP and CUDA on the Shannon cluster at Sandia National Laboratories and the Titan supercomputer at Oak Ridge National Laboratory, we evaluate the per- formance of the code on a canonical test case known as the baroclinic instability problem. We show a speedup of up to 4 times on 8 OpenMP threads, but we were unable to achieve a speedup on the GPU due to memory constraints. We conclude by providing methods for improving the performance of the code for future optimization.