Publications

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Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation properties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connection. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

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The Gamma Detector Response and Analysis Software--Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

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The Light Initiated High Explosive (LIHE) facility performs high rigor, high consequence impulse testing for the nuclear weapons (NW) community. To support the facility mission, LIHE's extensive data acquisition system (DAS) is comprised of several discrete components as well as a fully integrated system. Due to the high consequence and high rigor of the testing performed at LIHE, a measurement assurance plan (MAP) was developed in collaboration with NW system customers to meet their data quality needs and to provide assurance of the robustness of the LIHE DAS. While individual components of the DAS have been calibrated by the SNL Primary Standards Laboratory (PSL), the integrated nature of this complex system requires verification of the complete system, from end-to-end. This measurement assurance plan (MAP) report documents the results of verification and validation procedures used to ensure that the data quality meets customer requirements.

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This application note describes how to model steady-state power flows and transient events in electric power grids with the SPICE-compatible Xyce™ Parallel Electronic Simulator developed at Sandia National Labs. This application notes provides a brief tutorial on the basic devices (branches, bus shunts, transformers and generators) found in power grids. The focus is on the features supported and assumptions made by the Xyce models for power grid elements. It then provides a detailed explanation, including working Xyce netlists, for simulating some simple power grid examples such as the IEEE 14-bus test case.

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As cyber-security is becoming more and more important in systems development, engineers have begun to recognize and understand the types of errors they can introduce through hurried coding technique and design. This overall trend is certainly moving the software industry in the right direction and can lead to developing higher quality software-centric systems. Unfortunately, we have barely begun to examine the results of poor architectural choices, nor do we have much insight into what secure and securable architectures look like. In this paper, based on the past 40 years of work identifying specific security principles, we create a taxonomy of principles that address the abstract cyber-security needs of systems. We then tie these principles to studies of insecure systems architectures to demonstrate applicability. We close the paper with a description of other cyber-security taxonomies, how they specifically differ from this presented taxonomy, and add new principles to address gaps shown in taxonomic comparisons.

Vascomax® maraging C250 and C300 alloys were dynamically characterized in tension with Kolsky tension bar techniques. Compared with conventional Kolsky tension bar experiments, a pair of lock nuts was used to minimize the pseudo stress peak and a laser system was applied to directly measure the specimen displacement. Dynamic engineering stress–strain curves of the C250 and C300 alloys were obtained in tension at 1000 and 3000 s−1. The dynamic yield strengths for both alloys were similar, but significantly higher than those obtained from quasi-static indentation tests. Both alloys exhibited insignificant strain-rate effect on dynamic yield strength. The C300 alloy showed approximately 10 % higher in yield strength than the C250 alloy at the same strain rates. Necking was observed in both alloys right after yield. The Bridgman correction was applied to calculate the true stress and strain at failure for both alloys. The true failure stress showed a modest strain rate effect for both alloys but no significant difference between the two alloys at the same strain rate. The C250 alloy was more ductile than the C300 alloy under dynamic loading.

Selective layer disordering in an intersubband Al0.028Ga0.972N/AlN superlattice using a silicon nitride (SiNx) capping layer is demonstrated. The SiNx capped superlattice exhibits suppressed layer disordering under high-temperature annealing. Additionally, the rate of layer disordering is reduced with increased SiNx thickness. The layer disordering is caused by Si diffusion, and the SiNx layer inhibits vacancy formation at the crystal surface and ultimately, the movement of Al and Ga atoms across the heterointerfaces. Patterning of the SiNx layer results in selective layer disordering, an attractive method to integrate active and passive III-nitride-based intersubband devices.

Multilayer coextrusion is applied to produce a tape containing layers of alternating electrical properties to demonstrate the potential for using coextrusion to manufacture capacitors. To obtain the desired properties, we develop two filled polymer systems, one for conductive layers and one for dielectric layers. We describe numerical models used to help determine the material and processing parameters that impact processing and layer stability. These models help quantify the critical ratios of densities and viscosities of the two layers to maintain stable layers, as well as the effect of increasing the flow rate of one of the two materials. The conducting polymer is based on polystyrene filled with a blend of low-melting-point eutectic metal and nickel particulate filler, as described by Mrozek et al. (2010). The appropriate concentrations of fillers are determined by balancing measured conductivity with processability in a twin screw extruder. Based on results of the numerical models and estimates of the viscosity of emulsions and suspensions, a dielectric layer composed of polystyrene filled with barium titanate is formulated. Despite the fact that the density of the dielectric filler is less than the metallic filler of the conductive phase, as well as rheological measurements that later showed that the dielectric formulation is not an ideal match to the viscosity of the conductive material, the two materials can be successfully coextruded if the flow rates of the two materials are not identical. A measurable capacitance of the layered structure is obtained.

Classical molecular dynamics (MD) provides a powerful and widely used approach to determining thermodynamic properties by integrating the classical equations of motion of a system of atoms. Time-Dependent Density Functional Theory (TDDFT) provides a powerful and increasingly useful approach to integrating the quantum equations of motion for a system of electrons. TDDFT efficiently captures the unitary evolution of a many-electron state by mapping the system into a fictitious non-interacting system. In analogy to MD, one could imagine obtaining the thermodynamic properties of an electronic system from a TDDFT simulation in which the electrons are excited from their ground state by a time-dependent potential and then allowed to evolve freely in time while statistical data are captured from periodic snapshots of the system. For a variety of systems (e.g., many metals), the electrons reach an effective state of internal equilibrium due to electron-electron interactions on a time scale that is short compared to electron-phonon equilibration. During the initial time-evolution of such systems following electronic excitation, electron-phonon interactions should be negligible, and therefore, TDDFT should successfully capture the internal thermalization of the electrons. However, it is unclear how TDDFT represents the resulting thermal state. In particular, the thermal state is usually represented in quantum statistical mechanics as a mixed state, while the occupations of the TDDFT wavefunctions are fixed by the initial state in TDDFT. We work to address this puzzle by (A) reformulating quantum statistical mechanics so that thermodynamic expectations can be obtained as an unweighted average over a set of many-body pure states and (B) constructing a family of non-interacting (single determinant) TDDFT states that approximate the required many-body states for the canonical ensemble.

Large-scale molecular dynamics simulations are used to study the internal relaxations of chains in nanoparticle (NP)/polymer composites. We examine the Rouse modes of the chains, a quantity that is closest in spirit to the self-intermediate scattering function, typically determined in an (incoherent) inelastic neutron scattering experiment. Our simulations show that for weakly interacting mixtures of NPs and polymers, the effective monomeric relaxation rates are faster than in a neat melt when the NPs are smaller than the entanglement mesh size. In this case, the NPs serve to reduce both the monomeric friction and the entanglements in the polymer melt, as in the case of a polymer-solvent system. However, for NPs larger than half the entanglement mesh size, the effective monomer relaxation is essentially unaffected for low NP concentrations. Even in this case, we observe a strong reduction in chain entanglements for larger NP loadings. Thus, the role of NPs is to always reduce the number of entanglements, with this effect only becoming pronounced for small NPs or for high concentrations of large NPs. Our studies of the relaxation of single chains resonate with recent neutron spin echo (NSE) experiments, which deduce a similar entanglement dilution effect.

Semiconductor strain engineering has become a critical feature of high-performance electronics because of the significant device performance enhancements that it enables. These improvements, which emerge from strain-induced modifications to the electronic band structure, necessitate new ultra-sensitive tools to probe the strain in semiconductors. Here, we demonstrate that minute amounts of strain in thin semiconductor epilayers can be measured using electronic Raman scattering. We applied this strain measurement technique to two different semiconductor alloy systems using coherently strained epitaxial thin films specifically designed to produce lattice-mismatch strains as small as 10 â '4. Comparing our strain sensitivity and signal strength in Al x Ga 1â 'x As with those obtained using the industry-standard technique of phonon Raman scattering, we found that there was a sensitivity improvement of 200-fold and a signal enhancement of 4 × 10 3, thus obviating key constraints in semiconductor strain metrology.

Carbon is the most widely studied material today because it exhibits special properties not seen in any other materials when in nano dimensions such as nanotube and graphene. Reduction of material defects created during synthesis has become critical to realize the full potential of carbon structures. Molecular dynamics (MD) simulations, in principle, allow defect formation mechanisms to be studied with high fidelity, and can, therefore, help guide experiments for defect reduction. Such MD simulations must satisfy a set of stringent requirements. First, they must employ an interatomic potential formalism that is transferable to a variety of carbon structures. Second, the potential needs to be appropriately parameterized to capture the property trends of important carbon structures, in particular, diamond, graphite, graphene, and nanotubes. The potential must predict the crystalline growth of the correct phases during direct MD simulations of synthesis to achieve a predictive simulation of defect formation. An unlimited number of structures not included in the potential parameterization are encountered, thus the literature carbon potentials are often not sufficient for growth simulations. We have developed an analytical bond order potential for carbon, and have made it available through the public MD simulation package LAMMPS. We also demonstrate that our potential reasonably captures the property trends of important carbon phases. As a result, stringent MD simulations convincingly show that our potential accounts not only for the crystalline growth of graphene, graphite, and carbon nanotubes but also for the transformation of graphite to diamond at high pressure.

Estimating the parameters that dictate the dynamics of a quantum system is an important task for quantum information processing and quantum metrology, as well as fundamental physics. In this paper we develop a method for parameter estimation for Markovian open quantum systems using a temporal record of measurements on the system. The method is based on system realization theory and is a generalization of our previous work on identification of Hamiltonian parameters [Phys. Rev. Lett. 113, 080401 (2014)PRLTAO0031-9007 10.1103/PhysRevLett.113.080401].

Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not be efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.

Recovery transients following blocking-state voltage stress are analyzed for two types of AlGaN/GaN HEMTs, one set of devices with thick AlGaN barrier layers and another with recessed-gate geometry and ALD SiO2 gate dielectric. Results show temperature-invariant emission processes are present in both devices. Recessed-gate devices with SiO2 dielectrics are observed to exhibit simultaneous trapping and emission processes during post-stress recovery.

The fidelity of the forward model within a spent fuel forensic analysis system was improved by using two unique methodologies. The first consisted of developing a system to create accurate one-group neutron cross-section libraries for any user specified reactor system. In such, a detailed model is developed using the depletion code MONTEBURNS. During MONTEBURNS execution, cross-section libraries are generated at every user specified burnup step in time. These libraries could be developed for many reactor systems, then housed in a database and used for analyzing unknown fuel samples. The forensic analysis system for spent fuel resulted in higher accuracy at predicting the initial uranium isotopic compositions and burnup from spent fuel samples. Using this method, the error in results was reduced from the order of 1-6% down to less than 1% when recovering a fuel sample's burnup and initial uranium isotopic composition. The second method consisted of implementing 2D/3D reactor depletion codes as the forward model within the system's framework. This method would allow the usage of potentially recoverable geometric information from an unknown sample. No predetermined cross-section library is required for the system using this method, therefore potentially reducing model error associated with the neutron flux spectrum. The accuracy of the recovered initial uranium isotopic compositions and burnup from spent fuel samples was also improved using this method, even more so than the first. For MTR reactors, the error using this method was significantly reduced and was driven to below 0.5%. However, additional research may be required to determine the ideal fission yield and recoverable energy per fission for cases where significant amounts of 239 PU are bred and burned throughout the life of the fuel.

Understanding the effect of changing stress conditions on multiphase flow in porous media is of fundamental importance for many subsurface activities including enhanced oil recovery, water drawdown from aquifers, soil confinement, and geologic carbon storage. Geomechanical properties of complex porous systems are dynamically linked to flow conditions, but their feedback relationship is often oversimplified due to the difficulty of representing pore-scale stress deformation and multiphase flow characteristics in high fidelity. In this work, we performed pore-scale experiments of single- and multiphase flow through bead packs at different confining pressure conditions to elucidate compaction-dependent characteristics of granular packs and their impact on fluid flow. A series of drainage and imbibition cycles were conducted on a water-wet, soda-lime glass bead pack under varying confining stress conditions. Simultaneously, X-ray micro-CT was used to visualize and quantify the degree of deformation and fluid distribution corresponding with each stress condition and injection cycle. Micro-CT images were segmented using a gradient-based method to identify fluids (e.g., oil and water), and solid phase redistribution throughout the different experimental stages. Changes in porosity, tortuosity, and specific surface area were quantified as a function of applied confining pressure. Results demonstrate varying degrees of sensitivity of these properties to confining pressure, which suggests that caution must be taken when considering scalability of these properties for practical modeling purposes. Changes in capillary number with confining pressure are attributed to the increase in pore velocity as a result of pore contraction. Furthermore, this increase in pore velocity was found to have a marginal impact on average phase trapping at different confining pressures.

We present transport measurements of silicon MOS split gate structures with and without Sb implants. We observe classical point contact (PC) behavior that is free of any pronounced unintentional resonances at liquid He temperatures. The implanted device has resonances superposed on the PC transport indicative of transport through the Sb donors. We fit the differential conductance to a rectangular tunnel barrier model with a linear barrier height dependence on source-drain voltage and non-linear dependence on gate bias. Effects such as Fowler-Nordheim (FN) tunneling and image charge barrier lowering (ICBL) are considered. Barrier heights and widths are estimated for the entire range of relevant biases. The barrier heights at the locations of some of the resonances for the implanted tunnel barrier are between 15-20 meV, which are consistent with transport through shallow partially hybridized Sb donors. The dependence of width and barrier height on gate voltage is found to be linear over a wide range of gate bias in the split gate geometry but deviates considerably when the barrier becomes large and is not described completely by standard 1D models such as FN or ICBL effects.

The number of cycles required to form and grow microstructurally small fatigue cracks in metals exhibits substantial variability, particularly for low applied strain amplitudes. This variability is commonly attributed to the heterogeneity of cyclic plastic deformation within the microstructure, and presents a challenge to minimum life design of fatigue resistant components. Our paper analyzes sources of variability that contribute to the driving force of transgranular fatigue cracks within nucleant grains. We also employ crystal plasticity finite element simulations that explicitly render the polycrystalline microstructure and Fatigue Indicator Parameters (FIPs) averaged over different volume sizes and shapes relative to the anticipated fatigue damage process zone. Volume averaging is necessary to both achieve description of a finite fatigue damage process zone and to regularize mesh dependence in simulations. Furthermore, results from constant amplitude remote applied straining are characterized in terms of the extreme value distributions of volume averaged FIPs. Grain averaged FIP values effectively mitigate mesh sensitivity, but they smear out variability within grains. Furthermore, volume averaging over bands that encompass critical transgranular slip planes appear to present the most attractive approach to mitigate mesh sensitivity while preserving variability within grains.

Three-dimensional phase-field simulations of GaN growth by selective area epitaxy were performed. The model includes a crystallographic-orientation-dependent deposition rate and arbitrarily complex mask geometries. The orientation-dependent deposition rate can be determined from experimental measurements of the relative growth rates of low-index crystallographic facets. Growth on various complex mask geometries was simulated on both c-plane and a-plane template layers. Agreement was observed between simulations and experiment, including complex phenomena occurring at the intersections between facets. The sources of the discrepancies between simulated and experimental morphologies were also investigated. The model provides a route to optimize masks and processing conditions during materials synthesis for solar cells, light-emitting diodes, and other electronic and opto-electronic applications.

The objective of the present study is to explore the connection between the nonlinear normal modes of an undamped and unforced nonlinear system and the isolated resonance curves that may appear in the damped response of the forced system. To this end, an energy balance technique is used to predict the amplitude of the harmonic forcing that is necessary to excite a specific nonlinear normal mode. A cantilever beam with a nonlinear spring at its tip serves to illustrate the developments. Furthermore, the practical implications of isolated resonance curves are also discussed by computing the beam response to sine sweep excitations of increasing amplitudes.

Introduced a novel contrast metric in combination with traditional metrics to evaluate quality of coherent aperture radar, data products.

We examine a silicon-germanium heterojunction bipolar transistor (HBT) for cryogenic pre-amplification of a single electron transistor (SET). The SET current modulates the base current of the HBT directly. The HBT-SET circuit is immersed in liquid helium, and its frequency response from low frequency to several MHz is measured. The current gain and the noise spectrum with the HBT result in a signal-to-noise-ratio (SNR) that is a factor of 10–100 larger than without the HBT at lower frequencies. Furthermore, the transition frequency defined by SNR = 1 has been extended by as much as a factor of 10 compared to without the HBT amplification. The power dissipated by the HBT cryogenic pre-amplifier is approximately 5 nW to 5 μW for the investigated range of operation. We found that the circuit is also operated in a single electron charge read-out configuration in the time-domain as a proof-of-principle demonstration of the amplification approach for single spin read-out.

The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method. Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.

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Large diameter multi-shell gas puffs rapidly imploded by high current (~20 MA, ~100 ns) on the Z generator of Sandia National Laboratories are able to produce high-intensity Krypton K-shell emission at ~13 keV. Efficiently radiating at these high photon energies is a significant challenge which requires the careful design and optimization of the gas distribution. To facilitate this, we hydrodynamically model the gas flow out of the nozzle and then model its implosion using a 3-dimensional resistive, radiative MHD code (GORGON). This approach enables us to iterate between modeling the implosion and gas flow from the nozzle to optimize radiative output from this combined system. Furthermore, guided by our implosion calculations, we have designed gas profiles that help mitigate disruption from Magneto-Rayleigh–Taylor implosion instabilities, while preserving sufficient kinetic energy to thermalize to the high temperatures required for K-shell emission.

We have used low-energy electron microscopy (LEEM) and diffraction (LEED) to examine the significance of lattice orientation in graphene growth on Cu(001). Individual graphene domains undergo anisotropic growth on the Cu surface, and develop into lens shapes with their long axes roughly aligned with Cu〈100〉 in-plane directions. The long axis of a lens-shaped domain is only rarely oriented along a C〈11〉 direction, suggesting that carbon attachment at "zigzag" graphene island edges is unfavorable. A kink-mediated adatom attachment process is consistent with the behavior observed here and reported in the literature. The details of the ridged moiré pattern formed by the superposition of the graphene lattice on the (001) Cu surface also evolve with the graphene lattice orientation, and are predicted well by a simple geometric model. Managing the kink-mediated growth mode of graphene on Cu(001) will be necessary for the continued improvement of this graphene synthesis technique.

This study has evaluated the technical feasibility of direct disposal in a geologic repository, of commercial spent nuclear fuel (SNF) in dual-purpose canisters (DPCs) of existing designs. The authors, representing several national laboratories, considered waste isolation safety, engineering feasibility, thermal management, and postclosure criticality control. The 3-year study concludes that direct disposal is technically feasible for most DPCs, depending on the repository host geology. Postclosure criticality control, and thermal management strategies that allow permanent disposal within 150 years, are two of the most challenging aspects. This document summarizes technical results from a series of previous reports, and describes additional studies that can be done especially if site-specific information becomes available from one or more prospective repository sites.

In magnetizing the fusion fuel in inertial confinement fusion (ICF) systems, we found that the required stagnation pressure and density can be relaxed dramatically. This happens because the magnetic field insulates the hot fuel from the cold pusher and traps the charged fusion burn products. This trapping allows the burn products to deposit their energy in the fuel, facilitating plasma self-heating. Here, we report on a comprehensive theory of this trapping in a cylindrical DD plasma magnetized with a purely axial magnetic field. Using this theory, we are able to show that the secondary fusion reactions can be used to infer the magnetic field-radius product, BR, during fusion burn. This parameter, not ρR, is the primary confinement parameter in magnetized ICF. Using this method, we analyze data from recent Magnetized Liner InertialFusion experiments conducted on the Z machine at Sandia National Laboratories. Furthermore, we show that in these experiments BR ≈ 0.34(+0.14/-0.06) MG · cm, a ~ 14× increase in BR from the initial value, and confirming that the DD-fusion tritons are magnetized at stagnation. Lastly, this is the first experimental verification of charged burn product magnetization facilitated by compression of an initial seed magnetic flux.

The low-temperature oxidation of three cyclic ketones, cyclopentanone (CPO; C5H8O), cyclohexanone (CHO; C6H10O), and 2-methyl-cyclopentanone (2-Me-CPO; CH3-C5H7O), is studied between 550 and 700 K and at 4 or 8 Torr total pressure. Initial fuel radicals R are formed via fast H-abstraction from the ketones by laser-photolytically generated chlorine atoms. Intermediates and products from the subsequent reactions of these radicals in the presence of excess O2 are probed with time and isomeric resolution using multiplexed photoionization mass spectrometry with tunable synchrotron ionizing radiation. For CPO and CHO the dominant product channel in the R + O2 reactions is chain-terminating HO2-elimination yielding the conjugated cyclic coproducts 2-cyclopentenone and 2-cyclohexenone, respectively. Results on oxidation of 2-Me-CPO also show a dominant contribution from HO2-elimination. The photoionization spectrum of the co-product suggests formation of 2-methyl-2-cyclopentenone and/or 2-cyclohexenone, resulting from a rapid Dowd-Beckwith rearrangement, preceding addition to O2, of the initial (2-oxocyclopentyl)methyl radical to 3-oxocyclohexyl. Cyclic ethers, markers for hydroperoxyalkyl radicals (QOOH), key intermediates in chain-propagating and chain-branching low-temperature combustion pathways, are only minor products. The interpretation of the experimental results is supported by stationary point calculations on the potential energy surfaces of the associated R + O2 reactions at the CBS-QB3 level. The calculations indicate that HO2-elimination channels are energetically favored and product formation via QOOH is disfavored. The prominence of chain-terminating pathways linked with HO2 formation in low-temperature oxidation of cyclic ketones suggests little low-temperature reactivity of these species as fuels in internal combustion engines.

The secondary structure of peptides in the presence of interacting additives is an important topic of study, having implications in the application of peptide science to a broad range of modern technologies. Surfactants constitute a class of biologically relevant compounds that are known to influence both peptide conformation and aggregation or assembly. We have characterized the secondary structure of a linear nonapeptide composed of a hydrophobic alanine/phenylalanine core flanked by hydrophilic acid/amine units. We show that the anionic surfactant sodium dodecyl sulfate (SDS) induces the formation of β-sheets and macroscopic gelation in this otherwise unstructured peptide. Through comparison to related additives, we propose that SDS-induced secondary structure formation is the result of amphiphilicity created by electrostatic binding of SDS to the peptide. In addition, we demonstrate a novel utility of surfactants in manipulating and stabilizing peptide nanostructures. SDS is used to simultaneously induce secondary structure in a peptide and to inhibit the activity of a model enzyme, resulting in a peptide hydrogel that is impervious to enzymatic degradation. These results complement our understanding of the behavior of peptides in the presence of interacting secondary molecules and provide new potential pathways for programmable organization of peptides by the addition of such components.

Battery electrode surfaces are generally coated with electronically insulating solid films of thickness 1-50 nm. Both electrons and Li⁺ can move at the electrode-surface film interface in response to the voltage, which adds complexity to the "electric double layer" (EDL). We apply Density Functional Theory (DFT) to investigate how the applied voltage is manifested as changes in the EDL at atomic length scales, including charge separation and interfacial dipole moments. Illustrating examples include Li3PO4, Li2CO3, and LixMn2O4 thin films on Au(111) surfaces under ultrahigh vacuum conditions. Adsorbed organic solvent molecules can strongly reduce voltages predicted in vacuum. We propose that manipulating surface dipoles, seldom discussed in battery studies, may be a viable strategy to improve electrode passivation. We also distinguish the computed potential governing electrons, which is the actual or instantaneous voltage, and the "lithium cohesive energy"-based voltage governing Li content widely reported in DFT calculations, which is a slower-responding self-consistency criterion at interfaces. This distinction is critical for a comprehensive description of electrochemical activities on electrode surfaces, including Li⁺ insertion dynamics, parasitic electrolyte decomposition, and electrodeposition at overpotentials.

The growth temperature dependence of Si doping efficiency and deep level defect formation was investigated for n-type Al0.7Ga0.3N. It was observed that dopant compensation was greatly reduced with reduced growth temperature. Deep level optical spectroscopy and lighted capacitance-voltage were used to understand the role of acceptor-like deep level defects on doping efficiency. Deep level defects were observed at 2.34 eV, 3.56 eV, and 4.74 eV below the conduction band minimum. The latter two deep levels were identified as the major compensators because the reduction in their concentrations at reduced growth temperature correlated closely with the concomitant increase in free electron concentration. Possible mechanisms for the strong growth temperature dependence of deep level formation are considered, including thermodynamically driven compensating defect formation that can arise for a semiconductor with very large band gap energy, such as Al0.7Ga0.3N.

Multivalent (MV) battery architectures based on pairing a Mg metal anode with a high-voltage (∼3 V) intercalation cathode offer a realistic design pathway toward significantly surpassing the energy storage performance of traditional Li-ion-based batteries, but there are currently only few electrolyte systems that support reversible Mg deposition. Using both static first-principles calculations and ab initio molecular dynamics, we perform a comprehensive adsorption study of several salt and solvent species at the interface of Mg metal with an electrolyte of Mg²⁺ and Cl^- dissolved in liquid tetrahydrofuran (THF). Our findings not only provide a picture of the stable species at the interface but also explain how this system can support reversible Mg deposition, and as such, we provide insights in how to design other electrolytes for Mg plating and stripping. The active depositing species are identified to be (MgCl)⁺ monomers coordinated by THF, which exhibit preferential adsorption on Mg compared to possible passivating species (such as THF solvent or neutral MgCl2 complexes). Upon deposition, the energy to desolvate these adsorbed complexes and facilitate charge transfer is shown to be small (∼61-46.2 kJ mol^-1 to remove three THF from the strongest adsorbing complex), and the stable orientations of the adsorbed but desolvated (MgCl)⁺ complexes appear to be favorable for charge transfer. Finally, observations of Mg-Cl dissociation at the Mg surface at very low THF coordinations (0 and 1) suggest that deleterious Cl incorporation in the anode may occur upon plating. In the stripping process, this is beneficial by further facilitating the Mg removal reaction.

We predict that within next 15 years a fundamental down-scaling limit for CMOS technology and other Field-Effect Transistors (FETs) will be reached. Specifically, we show that at room temperatures all FETs, irrespective of their channel material, will start experiencing unacceptable level of thermally induced errors around 5-nm gate lengths. These findings were confirmed by performing quantum mechanical transport simulations for a variety of 6-, 5-, and 4-nm gate length Si devices, optimized to satisfy high-performance logic specifications by ITRS. Different channel materials and wafer/channel orientations have also been studied; it is found that altering channel-source-drain materials achieves only insignificant increase in switching energy, which overall cannot sufficiently delay the approaching downscaling limit. Alternative possibilities are discussed to continue the increase of logic element densities for room temperature operation below the said limit.

Developers and security analysts have been using static analysis for a long time to analyze programs for defects and vulnerabilities with some success. Generally a static analysis tool is run on the source code for a given program, flagging areas of code that need to be further inspected by a human analyst. These areas may be obvious bugs like potential bu er over flows, information leakage flaws, or the use of uninitialized variables. These tools tend to work fairly well - every year they find many important bugs. These tools are more impressive considering the fact that they only examine the source code, which may be very complex. Now consider the amount of data available that these tools do not analyze. There are many pieces of information that would prove invaluable for finding bugs in code, things such as a history of bug reports, a history of all changes to the code, information about committers, etc. By leveraging all this additional data, it is possible to nd more bugs with less user interaction, as well as track useful metrics such as number and type of defects injected by committer. This dissertation provides a method for leveraging development metadata to find bugs that would otherwise be difficult to find using standard static analysis tools. We showcase two case studies that demonstrate the ability to find 0day vulnerabilities in large and small software projects by finding new vulnerabilities in the cpython and Roundup open source projects.

Calculating operational availability (Ao) for a system of systems (SoS) presents unique challenges to reliability, availability, and maintainability (RAM) assessment, modeling, and analysis. System interdependencies and complex interrelated sustainment operations that exist in a SoS present complexities that must be accounted for in calculating or estimating Ao for the SoS. These system interdependencies affect the operating, operable, and down times of the individual systems. Both system-level and SoS-level Ao performance must be assessed within the SoS context for logistics and planning purposes. However, metrics calculated for the individual systems as part of the SoS may not be appropriate for assessing the individual system performance against their individual system requirements. In most cases, simulation modeling is required to capture the complex operating, operable, and down time hours of a SoS and the systems in the SoS, and to accurately aggregate the individual system availabilities to higher SoS levels. This paper explores some of the complexities involved in SoS Ao modeling and presents So S simulation results from a modeled SoS application.

A parallel file system (PFS) is often used to store intermediate results and checkpoint/restart files in a high performance computing (HPC) system. Multiple applications running on an HPC system often access PFSs concurrently resulting in degraded and variable I/O performance. By managing PFS accesses, these sharing induced inefficiencies can be controlled and reduced. To this end, we are exploring access control mechanisms to manage the shared PFS, so that the PFS can change its runtime behavior when it serves I/O requests from applications, e.g., provide exclusive access to a single application at a time and for a time window. In this paper, we discuss our design space exploration and also present some initial experimental results collected during the exploration. This workenables deeper exploration of our ongoing research in managing inter-application interference in a PFS.

The DOE Extreme-Scale Technology Acceleration Fast Forward Storage and IO Stack project is going to have significant impact on storage systems design within and beyond the HPC community. With phase 1 of the project complete, it is an excellent opportunity to evaluate many of the decisions made to feed into the phase 2 effort. With this paper we not only provide a timely summary of important aspects of the design specifications but also capture the underlying reasoning that is not available elsewhere. The initial effort to define a next generation storage system has made admirable contributions in architecture and design. Formalizing the general idea of data staging into burst buffers for the storage system will help manage the performance variability and offer additional data processing opportunities outside the main compute and storage system. Adding a transactional mechanism to manage faults and data visibility helps enable effective analytics without having to work around the IO stack semantics. While these and other contributions are valuable, similar efforts made elsewhere may offer attractive alternatives or differing semantics that could yield a more feature rich environment with little to no additional overhead. For example, the Doubly Distributed Transactions (D2T) protocol offers an alternative approach for incorporating transactional semantics into the data path. Another project, PreDatA, examined how to get the best throughput for data operators and may offer additional insights into further refinements of the Burst Buffer concept. This paper examines some of the choices made by the Fast Forward team and compares them with other options and offers observations and suggestions based on these other efforts. This will include some non-core contributions of other projects, such as some of the demonstration metadata and data storage components generated while implementing D2T, to make suggestions that may help the next generation design for how the IO stack works as a whole.

We use epsilon-near-zero modes in semiconductor nanolayers to design a system whose spectral properties are controlled by their interaction with multi-dipole resonances. This design flexibility renders our platform attractive for efficient nonlinear composite materials. © OSA 2015.

We develop a computationally efficient and robust algorithm to automatically extract the coefficients of doublet resonances and apply this technique to 418 resonances in ring resonator transmission data with a mean RMS deviation of 7.28 × 10-4. © OSA 2015.

Lasing is demonstrated from nonpolar III-nitride core-shell multi-quantum-well nanowires. The nanowire lasers were fabricated by coupling a top-down and bottom-up methodology and achieved lasing at wavelengths below the GaN bandedge. © OSA 2015.

A classifier-guided sampling (CGS) method is introduced for solving engineering design optimization problems with discrete and/or continuous variables and continuous and/or discontinuous responses. The method merges concepts from metamodel-guided sampling and population-based optimization algorithms. The CGS method uses a Bayesian network classifier for predicting the performance of new designs based on a set of known observations or training points. Unlike most metamodelling techniques, however, the classifier assigns a categorical class label to a new design, rather than predicting the resulting response in continuous space, and thereby accommodates non-differentiable and discontinuous functions of discrete or categorical variables. The CGS method uses these classifiers to guide a population-based sampling process towards combinations of discrete and/or continuous variable values with a high probability of yielding preferred performance. Accordingly, the CGS method is appropriate for discrete/discontinuous design problems that are ill suited for conventional metamodelling techniques and too computationally expensive to be solved by population-based algorithms alone. The rates of convergence and computational properties of the CGS method are investigated when applied to a set of discrete variable optimization problems. Results show that the CGS method significantly improves the rate of convergence towards known global optima, on average, compared with genetic algorithms.

This paper develops a two-stage stochastic program and solution procedure to optimize the selection of seismic retrofit strategies to increase the resilience of electric power systems against earthquake hazards. The model explicitly considers the range of earthquake events that are possible and, for each, an approximation of the distribution of damage experienced. This is important because electric power systems are spatially distributed and so their performance is driven by the distribution of component damage. We test this solution procedure against the nonlinear integer solver in LINGO 13 and apply the formulation and solution strategy to the Eastern Interconnection, where seismic hazard stems from the New Madrid seismic zone.

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