Showing papers by "Sandia National Laboratories published in 2008"

A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

Abstract: This work proposes and analyzes a Smolyak-type sparse grid stochastic collocation method for the approximation of statistical quantities related to the solution of partial differential equations with random coefficients and forcing terms (input data of the model). To compute solution statistics, the sparse grid stochastic collocation method uses approximate solutions, produced here by finite elements, corresponding to a deterministic set of points in the random input space. This naturally requires solving uncoupled deterministic problems as in the Monte Carlo method. If the number of random variables needed to describe the input data is moderately large, full tensor product spaces are computationally expensive to use due to the curse of dimensionality. In this case the sparse grid approach is still expected to be competitive with the classical Monte Carlo method. Therefore, it is of major practical relevance to understand in which situations the sparse grid stochastic collocation method is more efficient than Monte Carlo. This work provides error estimates for the fully discrete solution using $L^q$ norms and analyzes the computational efficiency of the proposed method. In particular, it demonstrates algebraic convergence with respect to the total number of collocation points and quantifies the effect of the dimension of the problem (number of input random variables) in the final estimates. The derived estimates are then used to compare the method with Monte Carlo, indicating for which problems the former is more efficient than the latter. Computational evidence complements the present theory and shows the effectiveness of the sparse grid stochastic collocation method compared to full tensor and Monte Carlo approaches.

Biomimetic Systems for Hydroxyapatite Mineralization Inspired By Bone and Enamel

Abstract: 1.1. Biomineralization The study of biomineralization is not only important to gain an understanding of how mineral-rich tissues are created in vivo but also because it is a great source of inspiration for the design of advanced materials.1-7 Mineralized tissues have remarkable hierarchical structures that have evolved over time to achieve great functions in a large variety of organisms. Organic phases play a key role in templating the structure of mineralized tissues; therefore, their matrices are often hybrid in composition, varying widely in the relative content of organic and inorganic substances. Understanding the complex integration of hard and soft phases that biology achieves in mineralized matrices across scales and its link to properties is knowledge of great value to materials chemistry. At the same time, the synthetic mechanisms used by biology to create mineralized matrices could also offer some useful strategies to create synthetic hybrid materials. Often, the amount of organic material utilized by Nature to modify mechanical properties of mineralized structures is vanishingly small. One example is the role of occluded proteins in the toughness of biogenic calcite.8 The study of mammalian bone and teeth in the biomineralization and biomimetic context is particularly interesting since the information derived could contribute a significant biomedical impact on therapies and strategies to repair or regenerate human mineralized tissues. This is an important area given the continually rising average life span of humans. The materials of interest could be highly sophisticated bioactive scaffolds to regenerate bone and possibly dental tissues as well. This review focuses on the formation of hydroxyapatite (HA) in synthetic systems designed primarily in the biomimetic context of bone or enamel mineralization for therapeutic approaches in repair of human tissues. Bone and enamel share the same mineral composition, HA, but have different morphologies and organic content. Enamel is almost entirely inorganic in composition, and bone has a relatively high organic composition. Knowledge acquired in this field may inspire the chemical synthesis of novel hybrid materials, including apatite-based structures for the regeneration of human bone and dental tissues.

Radiation Effects in MOS Oxides

Abstract: Electronic devices in space environments can contain numerous types of oxides and insulators. Ionizing radiation can induce significant charge buildup in these oxides and insulators leading to device degradation and failure. Electrons and protons in space can lead to radiation-induced total-dose effects. The two primary types of radiation-induced charge are oxide-trapped charge and interface-trap charge. These charges can cause large radiation-induced threshold voltage shifts and increases in leakage currents. Two alternate dielectrics that have been investigated for replacing silicon dioxide are hafnium oxides and reoxidized nitrided oxides (RNO). For advanced technologies, which may employ alternate dielectrics, radiation-induced voltage shifts in these insulators may be negligible. Radiation-induced charge buildup in parasitic field oxides and in SOI buried oxides can also lead to device degradation and failure. Indeed, for advanced commercial technologies, the total-dose hardness of ICs is normally dominated by radiation-induced charge buildup in either parasitic field oxides and/or SOI buried oxides. Heavy ions in space can also degrade the oxides in electronic devices through several different mechanisms including single-event gate rupture, reduction in device lifetime, and large voltage shifts in power MOSFETs.

ZnO nanostructures as efficient antireflection layers in solar cells.

Abstract: An efficient antireflection coating (ARC) can enhance solar cell performance through increased light coupling. Here, we investigate solution-grown ZnO nanostructures as ARCs for Si solar cells and compare them to conventional single layer ARCs. We find that nanoscale morphology, controlled through synthetic chemistry, has a great effect on the macroscopic ARC performance. Compared with a silicon nitride (SiN) single layer ARC, ZnO nanorod arrays display a broadband reflection suppression from 400 to 1200 nm. For a tapered nanorod array with average tip diameter of 10 nm, we achieve a weighted global reflectance of 6.6%, which is superior to an optimized SiN single layer ARC. Calculations using rigorous coupled wave analysis suggest that the tapered nanorod arrays behave like modified single layer ARCs, where the tapering leads to impedance matching between Si and air through a gradual reduction of the effective refractive index away from the surface, resulting in low reflection particularly at longer wavelengths and eliminating interference fringes through roughening of the air-ZnO interface. According to the calculations, we may further improve ARC performance by tailoring the thickness of the bottom fused ZnO layer and through better control of tip tapering.

Theory of enhancement of thermoelectric properties of materials with nanoinclusions

Abstract: Based on the concept of band bending at metal/semiconductor interfaces as an energy filter for electrons, we present a theory for the enhancement of the thermoelectric properties of semiconductor materials with metallic nanoinclusions. We show that the Seebeck coefficient can be significantly increased due to a strongly energy-dependent electronic scattering time. By including phonon scattering, we find that the enhancement of $ZT$ due to electron scattering is important for high doping, while at low doping it is primarily due to a decrease in the phonon thermal conductivity.

An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

Abstract: This work proposes and analyzes an anisotropic sparse grid stochastic collocation method for solving partial differential equations with random coefficients and forcing terms (input data of the model). The method consists of a Galerkin approximation in the space variables and a collocation, in probability space, on sparse tensor product grids utilizing either Clenshaw-Curtis or Gaussian knots. Even in the presence of nonlinearities, the collocation approach leads to the solution of uncoupled deterministic problems, just as in the Monte Carlo method. This work includes a priori and a posteriori procedures to adapt the anisotropy of the sparse grids to each given problem. These procedures seem to be very effective for the problems under study. The proposed method combines the advantages of isotropic sparse collocation with those of anisotropic full tensor product collocation: the first approach is effective for problems depending on random variables which weigh approximately equally in the solution, while the benefits of the latter approach become apparent when solving highly anisotropic problems depending on a relatively small number of random variables, as in the case where input random variables are Karhunen-Loeve truncations of “smooth” random fields. This work also provides a rigorous convergence analysis of the fully discrete problem and demonstrates (sub)exponential convergence in the asymptotic regime and algebraic convergence in the preasymptotic regime, with respect to the total number of collocation points. It also shows that the anisotropic approximation breaks the curse of dimensionality for a wide set of problems. Numerical examples illustrate the theoretical results and are used to compare this approach with several others, including the standard Monte Carlo. In particular, for moderately large-dimensional problems, the sparse grid approach with a properly chosen anisotropy seems to be very efficient and superior to all examined methods.

Thin-film sensing with planar terahertz metamaterials: sensitivity and limitations.

Abstract: The limiting effects of varying the thickness of a dielectric overlayer on planar double split-ring resonator (SRR) arrays are studied by terahertz time-domain spectroscopy. Uniform dielectric overlayers from 100 nm to 16 µm thick are deposited onto fixed SRR arrays in order to shift the resonance frequency of the electric response. We discuss the bounds of resonance shifting and emphasize the resulting limitations for SRR-based sensing. These results are presented in the context of typical biosensing situations and are compared to previous work and other existing sensing platforms.

Theory of enhancement of thermoelectric properties of materials with nanoinclusions.

Abstract: Based on the concept of band bending at metal/semiconductor interfaces as an energy filter for electrons, we present a theory for the enhancement of the thermoelectric properties of semiconductor materials with metallic nanoinclusions. We show that the Seebeck coefficient can be significantly increased due to a strongly energy-dependent electronic scattering time. By including phonon scattering, we find that the enhancement of $ZT$ due to electron scattering is important for high doping, while at low doping it is primarily due to a decrease in the phonon thermal conductivity.

Recent advances in single-asperity nanotribology

Abstract: As the size of electronic and mechanical devices shrinks to the nanometre regime, performance begins to be dominated by surface forces. For example, friction, wear and adhesion are known to be central challenges in the design of reliable micro- and nano-electromechanical systems (MEMS/NEMS). Because of the complexity of the physical and chemical mechanisms underlying atomic-level tribology, it is still not possible to accurately and reliably predict the response when two surfaces come into contact at the nanoscale. Fundamental scientific studies are the means by which these insights may be gained. We review recent advances in the experimental, theoretical and computational studies of nanotribology. In particular, we focus on the latest developments in atomic force microscopy and molecular dynamics simulations and their application to the study of single-asperity contact.

Scalable Tensor Decompositions for Multi-aspect Data Mining

Abstract: Modern applications such as Internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensionalities. Tensors (i.e., multi-way arrays) provide a natural representation for such data. Consequently, tensor decompositions such as Tucker become important tools for summarization and analysis. One major challenge is how to deal with high-dimensional, sparse data. In other words, how do we compute decompositions of tensors where most of the entries of the tensor are zero. Specialized techniques are needed for computing the Tucker decompositions for sparse tensors because standard algorithms do not account for the sparsity of the data. As a result, a surprising phenomenon is observed by practitioners: Despite the fact that there is enough memory to store both the input tensors and the factorized output tensors, memory overflows occur during the tensor factorization process. To address this intermediate blowup problem, we propose Memory-Efficient Tucker (MET). Based on the available memory, MET adaptively selects the right execution strategy during the decomposition. We provide quantitative and qualitative evaluation of MET on real tensors. It achieves over 1000X space reduction without sacrificing speed; it also allows us to work with much larger tensors that were too big to handle before. Finally, we demonstrate a data mining case-study using MET.

Convergence of Peridynamics to Classical Elasticity Theory

Abstract: The peridynamic model of solid mechanics is a nonlocal theory containing a length scale. It is based on direct interactions between points in a continuum separated from each other by a finite distance. The maximum interaction distance provides a length scale for the material model. This paper addresses the question of whether the peridynamic model for an elastic material reproduces the classical local model as this length scale goes to zero. We show that if the motion, constitutive model, and any nonhomogeneities are sufficiently smooth, then the peridynamic stress tensor converges in this limit to a Piola-Kirchhoff stress tensor that is a function only of the local deformation gradient tensor, as in the classical theory. This limiting Piola-Kirchhoff stress tensor field is differentiable, and its divergence represents the force density due to internal forces. The limiting, or collapsed, stress-strain model satisfies the conditions in the classical theory for angular momentum balance, isotropy, objectivity, and hyperelasticity, provided the original peridynamic constitutive model satisfies the appropriate conditions.

Transport Properties of Hydroxide and Proton Conducting Membranes

Abstract: Hydroxide anion conducting solid polymer membranes, also termed anion exchange membranes, are becoming important materials for electrochemical technology, and activity in this field, spurred by renewed interest in alkaline fuel cells, is experiencing a resurgence. Solid polymer anion exchange membranes enable alkaline electrochemistry in devices such as fuel cells and electrolyzers and serve as a counterpoint to proton exchange membranes, of which there is a large body of literature. For their seeming importance, the details of transport in alkaline exchange membranes has not been explored thoroughly. In this work, a chloromethylated polymer with a polysulfone backbone was synthesized. 1H NMR spectroscopy was performed to determine the chloromethyl content and its position on the polymer structure. The chloromethylated polymer was solution cast to form clear, creasable films, and subsequent soaking of these films in aqueous trimethylamine gave benzyltrimethylammonium groups. The resulting anion exchange m...

Communication-optimal parallel and sequential QR and LU factorizations

Abstract: We present parallel and sequential dense QR factorization algorithms that are both optimal (up to polylogarithmic factors) in the amount of communication they perform, and just as stable as Householder QR. We prove optimality by extending known lower bounds on communication bandwidth for sequential and parallel matrix multiplication to provide latency lower bounds, and show these bounds apply to the LU and QR decompositions. We not only show that our QR algorithms attain these lower bounds (up to polylogarithmic factors), but that existing LAPACK and ScaLAPACK algorithms perform asymptotically more communication. We also point out recent LU algorithms in the literature that attain at least some of these lower bounds.

Light-Extraction Enhancement of GaInN Light-Emitting Diodes by Graded-Refractive-Index Indium Tin Oxide Anti-Reflection Contact†

Abstract: tion (AR) coatings, [7–10] and optical resonators. [11] In many cases, however, the unavailability of materials with desired refractive indices, particularly materials with very low refractive indices, prevents the implementation of optical components with very high performance. In addition, the choice of a material with desired refractive index often forces a compromise in other materials properties such as optical transmittance and electrical conductivity that are also important for most optoelectronic applications. Here, we show that oblique-angle deposition can be used to tailor the refractive index of a thinfilm material that is chosen for its desired material properties other than refractive index. The unique ability to control the refractive index of thin film materials allows one to eliminate Fresnel reflection, one of the fundamental limitations in lightextraction efficiency of light-emitting diodes (LEDs), by fabricating coatings whose refractive index gradually decreases from the refractive index of the active semiconductor layer to the refractive index of the surrounding medium. As an example of this concept, we present a six-layer graded-refractiveindex (GRIN) AR coating made entirely of a single material, indium tin oxide (ITO), chosen for its high conductivity, high optical transmittance, and low contact resistance with GaN. Each layer has a refractive index that is individually tuned to form a stack with refractive index graded from its dense ITO value down to the value close to that of air for an optimum AR performance. It is shown that GaInN LEDs with a GRIN ITOAR contact achieve a light-extraction efficiency enhancement of 24.3 % compared to the LEDs with dense ITO coating due to a strongly reduced Fresnel reflection at the ITO– air interface. Oblique-angle deposition is a method of growing porous thin films, and hence thin films with low-refractive index (lown), enabled by surface diffusion and self-shadowing effects during the deposition process. [12–16] In oblique-angle deposition, a random growth fluctuation on the substrate produces a shadow region that the incident vapor flux cannot reach, and a non-shadow region where incident flux deposits preferentially, thereby creating an oriented rodlike structure with high porosity. Figure 1 shows the cross-sectional scanning-electron microscopy (SEM) image of low-n ITO, which is electrically conductive and optically transparent in visible wavelengths, COMMUNICATION

Actin restricts FcepsilonRI diffusion and facilitates antigen-induced receptor immobilization.

Abstract: The actin cytoskeleton has been implicated in restricting diffusion of plasma membrane components. Here, simultaneous observations of quantum dot-labelled FcepsilonRI motion and GFP-tagged actin dynamics provide direct evidence that actin filament bundles define micron-sized domains that confine mobile receptors. Dynamic reorganization of actin structures occurs over seconds, making the location and dimensions of actin-defined domains time-dependent. Multiple FcepsilonRI often maintain extended close proximity without detectable correlated motion, suggesting that they are co-confined within membrane domains. FcepsilonRI signalling is activated by crosslinking with multivalent antigen. We show that receptors become immobilized within seconds of crosslinking. Disruption of the actin cytoskeleton results in delayed immobilization kinetics and increased diffusion of crosslinked clusters. These results implicate actin in membrane partitioning that not only restricts diffusion of membrane proteins, but also dynamically influences their long-range mobility, sequestration and response to ligand binding.

Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

Abstract: We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a spatial or temporal field, endowed with a hierarchical Gaussian process prior. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of Markov chain Monte Carlo) and are compounded by high dimensionality of the posterior. We address these challenges by introducing truncated Karhunen-Loeve expansions, based on the prior distribution, to efficiently parameterize the unknown field and to specify a stochastic forward problem whose solution captures that of the deterministic forward model over the support of the prior. We seek a solution of this problem using Galerkin projection on a polynomial chaos basis, and use the solution to construct a reduced-dimensionality surrogate posterior density that is inexpensive to evaluate. We demonstrate the formulation on a transient diffusion equation with prescribed source terms, inferring the spatially-varying diffusivity of the medium from limited and noisy data.

Evidence for graphene growth by C cluster attachment

Abstract: Using low-energy electron microscopy (LEEM), we have measured the local concentration of mobile carbon adatoms from which graphene sheets form on a Ru(0001) surface, and simultaneously, the growth rates of individual graphene islands. Graphene crystal growth on Ru differs strikingly from that of two-dimensional metal islands on metals: (i) C adatoms experience a large energy barrier to attaching to graphene step edges, so adatom diffusion does not limit growth. (ii) The supersaturations needed for appreciable growth rates are comparable to those required to nucleate islands. (iii) The growth rate is a highly nonlinear function of supersaturation, with a large activation energy (2.0±0.1 eV). Our analysis suggests that graphene grows by adding rare clusters of about five atoms rather than adding the abundant monomers (adatoms). Knowing the growth mechanism and monitoring the supersaturation, we can control the pattern of growing graphene sheets.

The energy challenge

Abstract: Global energy consumption is expected to grow by 50% by 2030, squeezing already scarce water resources. Mike Hightower and Suzanne A. Pierce recommend ways to integrate water and energy planning. Over a billion people around the world lack access to safe drinking water and over two billion have little or no sanitation. Do we have the resources — and the will — to provide the water to support a booming population? This issue of Nature (see introduction, p. 269 and Editorial, p. 253) tackles the science, economics and politics of the global water crisis. Climate scientists say that unreliable rains and drier summer soils will become more common: Quirin Schiermeier reports on water strategies for a drier world. The pressure is on farmers to get maximum crop yields with minimum water use. As Emma Marris reports, the collaboration between plant breeders, agronomists and geneticists to that end has been far from smooth. As the population of India grows, the demand for water keeps rising. Daemon Fairless investigates an ambitious plan to redistribute the country's water supplies by linking rivers in a vast canal network. Jamie Bartram says it is time to improve the global targets for access to water and sanitation to make them relevant to all. In most countries, crop irrigation accounts for most freshwater use — more than drinking water and domestic consumption — but water use in energy production is catching up fast. Mike Hightower and Suzanne Pierce describe the measures being developed to economize on water use in the energy sector. The need for research into water purification is pressing. In an extensive Review Article, Mark Shannon et al. highlight the developing technologies that — it is hoped — can provide our drinking water in the decades ahead. Water is (almost) everywhere, yet physicists still trade theory and counter theory to explain its structure: Phil Ball explains. And Books & Arts looks at a documentary on water security, and at art inspired by water's surprising patterns. Go to http://www.nature.com/news/specials/water/index.html for the on-line start-page.

In Situ High-Resolution Neutron Radiography of Cross-Sectional Liquid Water Profiles in Proton Exchange Membrane Fuel Cells

Abstract: High-resolution neutron radiography was used to image an operating proton exchange membrane fuel cell in situ. The cross-sectional liquid water profile of the cell was quantified as a function of cell temperature, current density, and anode and cathode gas feed flow rates. Detailed information was obtained on the cross-sectional water content in the membrane electrode assembly and the gas flow channels. At low current densities, liquid water tended to remain on the cathode side of the cell. Significant liquid water in the anode gas flow channel was observed when the heat and water production of the cell were moderate, where both water diffusion from the cathode and thermal gradients play a significant role in determining the water balance of the cell. Within the membrane electrode assembly itself, the cathode side was moderately more hydrated than the anode side of the assembly from 0.1 to 1.25 A cm -2 . The total liquid water content of the membrane electrode assembly was fairly stable between current densities of 0.25 and 1.25 A cm -2 , even though the water in the gas flow channels changed drastically over this current density range. At 60°C, the water content in the center of the gas diffusion layer was depleted compared to the membrane or gas flow channel interfaces. This phenomenon was not observed at 80°C where evaporative water removal is prevalent.

Solar Thermochemical Water-Splitting Ferrite-Cycle Heat Engines

Abstract: Thermochemical cycles are a type of heat engine that utilize high-temperature heat to produce chemical work. Like their mechanical work producing counterparts, their efficiency depends on the operating temperature and on the irreversibility of their internal processes. With this in mind, we have invented innovative design concepts for two-step solar-driven thermochemical heat engines based on iron oxide and iron oxide mixed with other metal oxide (ferrites) working materials. The design concepts utilize two sets of moving beds of ferrite reactant materials in close proximity and moving in opposite directions to overcome a major impediment to achieving high efficiency-thermal recuperation between solids in efficient countercurrent arrangements. They also provide an inherent separation of the product hydrogen and oxygen and are an excellent match with a high-concentration solar flux. However, they also impose unique requirements on the ferrite reactants and materials of construction as well as an understanding of the chemical and cycle thermodynamics. In this paper, the counter-rotating-ring receiver/reactor/ recuperator solar thermochemical heat engine concept is introduced, and its basic operating principles are described. Preliminary thermal efficiency estimates are presented and discussed. Our results and development approach are also outlined.

Peridynamics for multiscale materials modeling

Abstract: The paper presents an overview of peridynamics, a continuum theory that employs a nonlocal model of force interaction Specifically, the stress/strain relationship of classical elasticity is replaced by an integral operator that sums internal forces separated by a finite distance This integral operator is not a function of the deformation gradient, allowing for a more general notion of deformation than in classical elasticity that is well aligned with the kinematic assumptions of molecular dynamics Peridynamics effectiveness has been demonstrated in several applications, including fracture and failure of composites, nanofiber networks, and polycrystal fracture These suggest that peridynamics is a viable multiscale material model for length scales ranging from molecular dynamics to those of classical elasticity

Metal Oxide Composites and Structures for Ultra-High Temperature Solar Thermochemical Cycles.

Abstract: Conceptually, thermochemical cycles are heat engines that drive endothermic chemical reactions, e.g., splitting water into hydrogen and oxygen. The two-step metal oxide cycles (typically ferrite-based) are particularly attractive since they are relatively simple, use non-corrosive materials, and involve gas–solid reactions requiring no difficult separations. Additionally, they are potentially the most efficient renewable-energy driven processes for hydrogen production. We are developing a novel concentrating solar power (CSP) driven metal-oxide-based heat engine, the CR5, at the heart of which are rings of a reactive solid that are thermally and chemically cycled to produce oxygen and hydrogen from water in separate and isolated steps. The monolithic ring structures must have high geometric surface area for gas–solid contact and for adsorption of incident solar radiation, and must maintain structural integrity and high reactivity after extensive thermal cycling to temperatures of at least 1,400 °C. We have demonstrated through laboratory and on-sun testing that cobalt ferrite/zirconia mixtures fabricated into monolithic structures suitable for the CR5 are mechanically robust and maintain productivity over tens of cycles. We have also demonstrated that carbon dioxide splitting (CDS) to carbon monoxide and oxygen is a thermodynamically favorable alternative to water splitting that can be conducted with both iron- and cerium-based materials.

Five years of operating experience at a large, utility-scale photovoltaic generating plant

Abstract: Tucson Electric Power Company (TEP), headquartered in Tucson, AZ, currently has nearly 5·0 MWdc of utility-scale grid-connected photovoltaic (PV) systems installed in its service territory. These systems have been installed through a multiyear, pay-as-you-go development of renewable energy, with kWhac energy production as a key program measurement. This PV capacity includes a total of 26 crystalline silicon collector systems, each rated at 135 kWdc for a total of 3·51 MWdc, that have been installed at the Springerville, AZ generating plant by TEP making this one of the largest PV plants in the world. This facility started operations in 2001 and recently passed the 5-year milestone of continuous operations. These systems were installed in a standardized, cookie-cutter approach whereby each uses the same array field design, mounting hardware, electrical interconnection, and inverter unit. This approach has allowed TEP to achieve a total installed system cost of $5·40/Wdc and a TEP-calculated levelized energy cost of $0·062/kWhac for PV electrical generation. This paper presents an assessment of operating experience including performance, costs, maintenance, and plant operation over this 5-year period making this one of the most detailed and complete databases of utility-scale PV systems available to the US DOE Program. Published in 2007 by John Wiley & Sons, Ltd.

Ultra‐High‐Temperature Ceramic Coatings for Oxidation Protection of Carbon–Carbon Composites

Abstract: Carbon-carbon (C-C) composites are attractive materials for hypersonic flight vehicles but they oxidize in air at temperatures >500°C and need thermal protection systems to survive aerothermal heating. We investigated using multilayers of high-temperature ceramics such as ZrB 2 and SiC to protect C-C against oxidation. Our approach combines pretreatment and processing steps to create continuous and adherent high-temperature ceramic coatings from infiltrated preceramic polymers. We tested our protective coatings at temperatures above 2600°C at the National Solar Thermal Testing Facility using controlled cold-wall heat flux profiles reaching a maximum of 680 W/cm 2 .

Characterizing application sensitivity to OS interference using kernel-level noise injection

Abstract: Operating system noise has been shown to be a key limiter of application scalability in high-end systems. While several studies have attempted to quantify the sources and effects of system interference using user-level mechanisms, there are few published studies on the effect of different kinds of kernel-generated noise on application performance at scale. In this paper, we examine the sensitivity of real-world, large-scale applications to a range of OS noise patterns using a kernel-based noise injection mechanism implemented in the Catamount lightweight kernel. Our results demonstrate the importance of how noise is generated, in terms of frequency and duration, and how this impact changes with application scale. For example, our results show that 2.5% net processor noise at 10,000 nodes can have no impact or can result in over a factor of 20 slowdown for the same application, depending solely on how the noise is generated. We also discuss how the characteristics of the applications we studied, for example computation/communication ratios, collective communication sizes, and other characteristics, related to their tendency to amplify or absorb noise. Finally, we discuss the implications of our findings on the design of new operating systems, middleware, and other system services for high-end parallel systems.

The AM05 density functional applied to solids.

Abstract: We show that the AM05 functional [Armiento and Mattsson, Phys. Rev. B 72, 085108 (2005)] has the same excellent performance for solids as the hybrid density functionals tested in Paier et al. [J. Chem. Phys. 124, 154709 (2006); 125, 249901 (2006)]. This confirms the original finding that AM05 performs exceptionally well for solids and surfaces. Hartree–Fock hybrid calculations are typically an order of magnitude slower than local or semilocal density functionals such as AM05, which is of a regular semilocal generalized gradient approximation form. The performance of AM05 is on average found to be superior to selecting the best of local density approximation and PBE for each solid. By comparing data from several different electronic-structure codes, we have determined that the numerical errors in this study are equal to or smaller than the corresponding experimental uncertainties.