Publications

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Abstract not provided.

Abstract not provided.

Numerous benchmark measurements have been performed to enable developers of neutron transport models and codes to evaluate the accuracy of their calculations. In particular, for criticality safety applications, the International Criticality Safety Benchmark Experiment Program (ICSBEP) annually publishes a handbook of critical and subcritical benchmarks. Relatively fewer benchmark measurements have been performed to validate photon transport models and codes, and unlike the ICSBEP, there is no program dedicated to the evaluation and publication of photon benchmarks. Even fewer coupled neutron-photon benchmarks have been performed. This report documents a coupled neutron-photon benchmark for plutonium metal reflected by polyethylene. A 4.5-kg sphere of ?-phase, weapons-grade plutonium metal was measured in six reflected configurations: (1) Bare; (2) Reflected by 0.5 inch of high density polyethylene (HDPE); (3) Reflected by 1.0 inch of HDPE; (4) Reflected by 1.5 inches of HDPE; (5) Reflected by 3.0 inches of HDPE; and (6) Reflected by 6.0 inches of HDPE. Neutron and photon emissions from the plutonium sphere were measured using three instruments: (1) A gross neutron counter; (2) A neutron multiplicity counter; and (3) A high-resolution gamma spectrometer. This report documents the experimental conditions and results in detail sufficient to permit developers of radiation transport models and codes to construct models of the experiments and to compare their calculations to the measurements. All of the data acquired during this series of experiments are available upon request.

We perform pressure-driven non-equilibrium molecular dynamics (MD) simulations to drive a 1.0 M NaCI electrolyte through a dipole-lined smooth nanopore of diameter 12 A penetrating a model membrane. We show that partial, about 70-80%, CI- rejection is achieved at a ~68 atmosphere pressure. At the high water flux achieved in these model nanopores, which are particularly pertinent to atomistically smooth carbon nanotube membranes that permit fast water transport, the ion rejection ratio decreases with increasing water flux. The computed potential of mean force of Cl- frozen inside the nanopore reveals a barrier of 6.4 kcal/mol in 1.0 M NaCI solution. The Cl- permeation occurs despite the barrier, and this is identified as a dynamical effect, with ions carried along by the water flux. Na +-CI- ion-pairing or aggregation near the pore entrance and inside the pore, where the dielectric screening is weaker than in bulk water, is critical to Cl- permeation. We also consider negative charges decorating the rim and the interior of the pore instead of dipoles, and find that, with sufficient pressure, CI- from a 1.0 M NaCI solution readily passes through such nanopores. © 2009 American Scientific Publishers.

Concentrating Solar Power (CSP) dish systems use a parabolic dish to concentrate sunlight, providing heat for a thermodynamic cycle to generate shaft power and ultimately, electricity. Currently, leading contenders use a Stirling cycle engine with a heat absorber surface at about 800°C. The concentrated light passes through an aperture, which controls the thermal losses of the receiver system. Similar systems may use the concentrated light to heat a thermochemical process. The concentrator system, typically steel and glass, provides a source of fuel over the service life of the system, but this source of fuel manifests as a capital cost up front. Therefore, it is imperative that the cost of the reflector assembly is minimized. However, dish systems typically concentrate light to a peak of as much as 13,000 suns, with an average geometric concentration ratio of over 3000 suns. Several recent dish-Stirling systems have incorporated reflector facets with a normally-distributed surface slope error (local distributed waviness) of 0.8 mrad RMS (1-sigma error). As systems move toward commercialization, the cost of these highly accurate facets must be assessed. However, when considering lower-cost options, any decrease in the performance of the facets must be considered in the evaluation of such facets. In this paper, I investigate the impact of randomly-distributed slope errors on the performance, and therefore the value, of a typical dish-Stirling system. There are many potential sources of error in a concentrating system. When considering facet options, the surface waviness, characterized as a normally-distributed slope error, has the greatest impact on the aperture size and therefore the thermal losses. I develop an optical model and a thermal model for the performance of a baseline system. I then analyze the impact on system performance for a range of mirror quality, and evaluate the impact of such performance changes on the economic value of the system. This approach can be used to guide the evaluation of low-cost facets that differ in performance and cost. The methodology and results are applicable to other point- and line-focus thermal systems including dish-Brayton, dish-Thermochemical, tower systems, and troughs. Copyright © 2008 by ASME.

Thermal energy storage can enhance the utility of parabolic trough solar power plants by providing the ability to match electrical output to peak demand periods. An important component of thermal energy storage system optimization is selecting the working fluid used as the storage media and/or heat transfer fluid. Large quantities of the working fluid are required for power plants at the scale of 100-MW, so maximizing heat transfer fluid performance while minimizing material cost is important. This paper reports recent developments of multi-component molten salt formulations consisting of common alkali nitrate and alkaline earth nitrate salts that have advantageous properties for applications as heat transfer fluids in parabolic trough systems. A primary disadvantage of molten salt heat transfer fluids is relatively high freeze-onset temperature compared to organic heat transfer oil. Experimental results are reported for formulations of inorganic molten salt mixtures that display freeze-onset temperatures below 100°C. In addition to phase-change behavior, several properties of these molten salts that significantly affect their suitability as thermal energy storage fluids were evaluated, including chemical stability and viscosity. These alternative molten salts have demonstrated chemical stability in the presence of air up to approximately 500°C in laboratory testing and display chemical equilibrium behavior similar to Solar Salt. The capability to operate at temperatures up to 500°C may allow an increase in maximum temperature operating capability vs. organic fluids in existing trough systems and will enable increased power cycle efficiency. Experimental measurements of viscosity were performed from near the freeze-onset temperature to about 200°C. Viscosities can exceed 100 cP at the lowest temperature but are less than 10 cP in the primary temperature range at which the mixtures would be used in a thermal energy storage system. Quantitative cost figures of constituent salts and blends are not currently available, although, these molten salt mixtures are expected to be inexpensive compared to synthetic organic heat transfer fluids. Experiments are in progress to confirm that the corrosion behavior of readily available alloys is satisfactory for long-term use. Copyright © 2008 by ASME.

Sandia National Laboratories (SNL), General Atomics Corporation (GA) and the French Commissariat a l'Energie Atomique (CEA) have been conducting laboratory-scale experiments to investigate the thermochemical production of hydrogen using the Sulfur-Iodine (S-I) process. This project is being conducted as an International Nuclear Energy Research Initiative (INERI) project supported by the CEA and US DOE Nuclear Hydrogen Initiative. In the S-I process, 1) H2SO4 is catalytically decomposed at high temperature to produce SO2, O2 and H20. 2) The S02 is reacted with H20 and I2 to produce HI and H2SO 4. The H2S04 is returned to the acid decomposer. 3) The HI is decomposed to H2 and I2. The I2 is returned to the HI production process. Each participant in this work is developing one of the three primary reaction sections. SNL is responsible for the H 2SO4 decomposition section, CEA, the primary HI production section and General Atomics, the HI decomposition section. The objective of initial testing of the S-I laboratory-scale experiment was to establish the capability for integrated operations and demonstrate H2 production from the S-I cycle. The first phase of these objectives was achieved with the successful integrated operation of the SNL acid decomposition and CEA Bunsen reactor sections and the subsequent generation of H2 in the GA HI decomposition section. This is the first time the S-I cycle has been realized using engineering materials and operated at prototypic temperature and pressure to produce hydrogen. © 2008 by ASME.

We have developed a complete process module for fabricating front end of line (FEOL) through silicon vias (TSVs). In this paper we describe the integration, which relies on using thermally deposited silicon as a sacrificial material to fill the TSV during FEOL processing, followed by its removal and replacement with tungsten after FEOL processing is complete. The uniqueness of this approach follows mainly from forming the TSVs early in the FEOL while still ultimately using metal as the via fill material. TSVs formed early in the FEOL can be formed at comparatively small diameter, high aspect ratio, and high spatial density. We have demonstrated FEOL-integrated TSVs that are 2 μm in diameter, over 45 μm deep, and on 20 μm pitch for a possible interconnect density of 250,000/cm2. Moreover, thermal oxidation of silicon can be used to form the dielectric isolation. Thermal oxidation is conformal and robust in the as-formed state. Finally, TSVs formed in the FEOL alleviate device design constraints common to vias-last integration. © 2009 IEEE.

We report the results of an LDRD effort to investigate new technologies for the identification of small-sized (mm to cm) debris in low-earth orbit. This small-yet-energetic debris presents a threat to the integrity of space-assets worldwide and represents significant security challenge to the international community. We present a nonexhaustive review of recent US and Russian efforts to meet the challenges of debris identification and removal and then provide a detailed description of joint US-Russian plans for sensitive, laser-based imaging of small debris at distances of hundreds of kilometers and relative velocities of several kilometers per second. Plans for the upcoming experimental testing of these imaging schemes are presented and a preliminary path toward system integration is identified.

This paper develops Classical and Bayesian methods for quantifying the uncertainty in reliability for a system of mixed series and parallel components for which both go/no-go and variables data are available. Classical methods focus on uncertainty due to sampling error. Bayesian methods can explore both sampling error and other knowledge-based uncertainties. To date, the reliability community has focused on qualitative statements about uncertainty because there was no consensus on how to quantify them. This paper provides a proof of concept that workable, meaningful quantification methods can be constructed. In addition, the application of the methods demonstrated that the results from the two fundamentally different approaches can be quite comparable. In both approaches, results are sensitive to the details of how one handles components for which no failures have been seen in relatively few tests.

I used supramolecular self-assembling cyanine and the polyamine spermine binding to Escherichia coli genomic DNA as a model for DNA collapse during high throughput screening. Polyamine binding to DNA converts the normally right handed B-DNA into left handed Z-DNA conformation. Polyamine binding to DNA was inhibited by the supramolecular self-assembling cyanine. Self-assembly of cyanine upon DNA scaffold was likewise competitively inhibited by spermine as signaled by fluorescence quench from DNA-cyanine ensemble. Sequence of DNA exposure to cyanine or spermine was critical in determining the magnitude of fluorescence quench. Methanol potentiated spermine inhibition by >10-fold. The IC{sub 50} for spermine inhibition was 0.35 {+-} 0.03 {micro}M and the association constant Ka was 2.86 x 10{sup -6}M. Reversibility of the DNA-polyamine interactions was evident from quench mitigation at higher concentrations of cyanine. System flexibility was demonstrated by similar spermine interactions with {lambda}DNA. The choices and rationale regarding the polyamine, the cyanine dye as well as the remarkable effects of methanol are discussed in detail. Cyanine might be a safer alternative to the mutagenic toxin ethidium bromide for investigating DNA-drug interactions. The combined actions of polyamines and alcohols mediate DNA collapse producing hybrid bio-nanomaterials with novel signaling properties that might be useful in biosensor applications. Finally, this work will be submitted to Analytical Sciences (Japan) for publication. This journal published our earlier, related work on cyanine supramolecular self-assembly upon a variety of nucleic acid scaffolds.

This report describes a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to identify socially situated relationships between individuals which, though subtle, are highly influential. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized. This report outlines the philosophical antecedents of SLNA, the mechanics of preprocessing, processing, and post-processing stages, and some example results obtained by applying this approach to a 15-month corporate discussion archive.

Staggered bioterrorist attacks with aerosolized pathogens on population centers present a formidable challenge to resource allocation and response planning. The response and planning will commence immediately after the detection of the first attack and with no or little information of the second attack. In this report, we outline a method by which resource allocation may be performed. It involves probabilistic reconstruction of the bioterrorist attack from partial observations of the outbreak, followed by an optimization-under-uncertainty approach to perform resource allocations. We consider both single-site and time-staggered multi-site attacks (i.e., a reload scenario) under conditions when resources (personnel and equipment which are difficult to gather and transport) are insufficient. Both communicable (plague) and non-communicable diseases (anthrax) are addressed, and we also consider cases when the data, the time-series of people reporting with symptoms, are confounded with a reporting delay. We demonstrate how our approach develops allocations profiles that have the potential to reduce the probability of an extremely adverse outcome in exchange for a more certain, but less adverse outcome. We explore the effect of placing limits on daily allocations. Further, since our method is data-driven, the resource allocation progressively improves as more data becomes available.

Understanding charge transport processes at a molecular level using computational techniques is currently hindered by a lack of appropriate models for incorporating anistropic electric fields in molecular dynamics (MD) simulations. An important technological example is ion transport through solid-electrolyte interphase (SEI) layers that form in many common types of batteries. These layers regulate the rate at which electro-chemical reactions occur, affecting power, safety, and reliability. In this work, we develop a model for incorporating electric fields in MD using an atomistic-to-continuum framework. This framework provides the mathematical and algorithmic infrastructure to couple finite element (FE) representations of continuous data with atomic data. In this application, the electric potential is represented on a FE mesh and is calculated from a Poisson equation with source terms determined by the distribution of the atomic charges. Boundary conditions can be imposed naturally using the FE description of the potential, which then propagates to each atom through modified forces. The method is verified using simulations where analytical or theoretical solutions are known. Calculations of salt water solutions in complex domains are performed to understand how ions are attracted to charged surfaces in the presence of electric fields and interfering media.

Fiber-optic gas phase surface plasmon resonance (SPR) detection of several contaminant gases of interest to state-of-health monitoring in high-consequence sealed systems has been demonstrated. These contaminant gases include H{sub 2}, H{sub 2}S, and moisture using a single-ended optical fiber mode. Data demonstrate that results can be obtained and sensitivity is adequate in a dosimetric mode that allows periodic monitoring of system atmospheres. Modeling studies were performed to direct the design of the sensor probe for optimized dimensions and to allow simultaneous monitoring of several constituents with a single sensor fiber. Testing of the system demonstrates the ability to detect 70mTorr partial pressures of H{sub 2} using this technique and <280 {micro}Torr partial pressures of H{sub 2}S. In addition, a multiple sensor fiber has been demonstrated that allows a single fiber to measure H{sub 2}, H{sub 2}S, and H{sub 2}O without changing the fiber or the analytical system.

Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closer to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.

The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution.

A number of codes have been developed in the past for safeguards analysis, but many are dated, and no single code is able to cover all aspects of materials accountancy, process monitoring, and diversion scenario analysis. The purpose of this work was to integrate a transient solvent extraction simulation module developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM), developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The SSPM was designed for materials accountancy and process monitoring analyses, but previous versions of the code have included limited detail on the chemical processes, including chemical separations. The transient solvent extraction model is based on the ORNL SEPHIS code approach to consider solute build up in a bank of contactors in the PUREX process. Combined, these capabilities yield a more robust transient separations and safeguards model for evaluating safeguards system design. This coupling and initial results are presented. In addition, some observations toward further enhancement of separations and safeguards modeling based on this effort are provided, including: items to be addressed in integrating legacy codes, additional improvements needed for a fully functional solvent extraction module, and recommendations for future integration of other chemical process modules.

This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effort to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.

The effect of composition on the elastic responses of alumina particle-filled epoxy composites is examined using isotropic elastic response models relating the average stresses and strains in a discretely reinforced composite material consisting of perfectly bonded and uniformly distributed particles in a solid isotropic elastic matrix. Responses for small elastic deformations and large hydrostatic and plane-strain compressions are considered. The response model for small elastic deformations depends on known elastic properties of the matrix and particles, the volume fraction of the particles, and two additional material properties that reflect the composition and microstructure of the composite material. These two material properties, called strain concentration coefficients, are characterized for eleven alumina-filled epoxy composites. It is found that while the strain concentration coefficients depend strongly on the volume fraction of alumina particles, no significant dependence on particle morphology and size is observed for the compositions examined. Additionally, an analysis of the strain concentration coefficients reveals a remarkably simple dependency on the alumina volume fraction. Responses for large hydrostatic and plane-strain compressions are obtained by generalizing the equations developed for small deformation, and letting the alumina volume fraction in the composite increase with compression. The large compression plane-strain response model is shown to predict equilibrium Hugoniot states in alumina-filled epoxy compositions remarkably well.

This report focuses on quantum chemistry and ab initio molecular dynamics (AIMD) calculations applied to elucidate the mechanism of the multi-step, 2-electron, electrochemical reduction of the green house gas molecule carbon dioxide (CO{sub 2}) to carbon monoxide (CO) in aqueous media. When combined with H{sub 2} gas to form synthesis ('syn') gas, CO becomes a key precursor to methane, methanol, and other useful hydrocarbon products. To elucidate the mechanism of this reaction, we apply computational electrochemistry which is a fledgling, important area of basic science critical to energy storage. This report highlights several approaches, including the calculation of redox potentials, the explicit depiction of liquid water environments using AIMD, and free energy methods. While costly, these pioneering calculations reveal the key role of hydration- and protonation-stabilization of reaction intermediates, and may inform the design of CO{sub 2}-capture materials as well as its electrochemical reduction. In the course of this work, we have also dealt with the challenges of identifying and applying electronic structure methods which are sufficiently accurate to deal with transition metal ion complex-based catalyst. Such electronic structure methods are also pertinent to the accurate modeling of actinide materials and therefore to nuclear energy research. Our multi-pronged effort towards achieving this titular goal of the LDRD is discussed.

Our LDRD research project sought to develop an analytical method for detection of chemicals used in nuclear materials processing. Our approach is distinctly different than current research involving hardware-based sensors. By utilizing the response of indigenous species of plants and/or animals surrounding (or within) a nuclear processing facility, we propose tracking 'suspicious molecules' relevant to nuclear materials processing. As proof of concept, we have examined TBP, tributylphosphate, used in uranium enrichment as well as plutonium extraction from spent nuclear fuels. We will compare TBP to the TPP (triphenylphosphate) analog to determine the uniqueness of the metabonomic response. We show that there is a unique metabonomic response within our animal model to TBP. The TBP signature can further be delineated from that of TPP. We have also developed unique methods of instrumental transfer for metabonomic data sets.

Rapid identification of aerosolized biological agents following an alarm by particle triggering systems is needed to enable response actions that save lives and protect assets. Rapid identifiers must achieve species level specificity, as this is required to distinguish disease-causing organisms (e.g., Bacillus anthracis) from benign neighbors (e.g., Bacillus subtilis). We have developed a rapid (1-5 minute), novel identification methodology that sorts intact organisms from each other and particulates using capillary electrophoresis (CE), and detects using near-infrared (NIR) absorbance and scattering. We have successfully demonstrated CE resolution of Bacillus spores and vegetative bacteria at the species level. To achieve sufficient sensitivity for detection needs ({approx}10{sup 4} cfu/mL for bacteria), we have developed fiber-coupled cavity-enhanced absorbance techniques. Using this method, we have demonstrated {approx}two orders of magnitude greater sensitivity than published results for absorbing dyes, and single particle (spore) detection through primarily scattering effects. Results of the integrated CE-NIR system for spore detection are presented.

Abstract not provided.