This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?
A wide-ranging analysis of water vulnerability across the Pacific — including the U.S., China, Russia and Japan — has identified hundreds of locations where energy production depends upon scarce water supplies. The Sandia National Laboratories study, Mapping Water Consumption for Energy Production Around the Pacific Rim, was published in Environmental Research Letters. Prepared for the Asia-Pacific Economic Corporation (APEC), the first-of-its-kind report maps out every power plant, refinery and mine in 21 Asian-Pacific economies that rely on fresh water for energy. Simultaneously, it shows the data in context to regions at high to extreme risk of drought and dwindling natural water supplies.
The diffusion through shells consisting of either a single conducting or double conducting layers are examined. Exterior drives resulting from Electromagnetic Radiation (EMR), Electromagnetic Pulse (EMP), nearby (indirect) lightning, and DC (low frequency) magnetic fields are used. Both the interior field and the induced voltage from a maximally oriented and sized single turn loop are estimated. It is shown that the loop voltage with the empty cavity bounds the case where the center region is excluded by a conducting object. The cases of interior magnetic and electric fields from an exterior magnetic drive and the interior electric field from an exterior electric drive are both solved; the magnetic interior field from an exterior magnetic drive is the only case that results in a nonzero low frequency penetration.
Use cases were reviewed with the IDC during trips in January, April and June 2016. In addition, reviews were conducted on the Thursday teleconferences between February and June 2016.
We are interested in simulating a variety of problems in 3 dimensions (3D) featuring large electric currents. While 2D simulations have been quite informative, cylindrical symmetry may interfere with a problem’s relevant physics. Specifically, all objects in the domain behave as if they are extruded 360°—turning particles into hoops. In dealing with electrical current, this can have serious ramifications on the current pathways. In 3D (r, φ, z) currents can adjust their pathways anywhere along those 360 degrees given the right conditions; however, in 2D (r, z) those pathways can be completely choked off because an insulating hoop, rather than a particle, is present.
Gamma-ray transport describes the way in which high-energy photons (gamma rays and x-rays) interact with matter. There are many well established, general purpose gamma transport calculation frameworks (such as GEANT4, MCNP, PARTISN, and GADRAS [1] [2] [3] [4]) that allow for complex generalized calculations, but they are typically not designed to be integrated into other multi-process, multi-platform applications, not designed for rapid computation, or their complexity leads to user errors. In this report, we introduce InterScatter: a deterministic simulation designed to quickly and easily calculate gamma-ray transport spectra for a 1D shielding geometry.
Extensive study of photorefractive polymeric composites photosensitized with semiconductor nanocrystals has yielded data indicating that the inclusion of such nanocrystals enhances the charge-carrier mobility, and subsequently leads to a reduction in the photorefractive response time. Unfortunately, the included nanocrystals may also act as a source of deep traps, resulting in diminished diffraction efficiencies as well as reduced two beam coupling gain coefficients. Nonetheless, previous studies indicate that this problem is mitigated through the inclusion of semiconductor nanocrystals possessing a relatively narrow band-gap. Here, we fully exploit this property by doping PbS nanocrystals into a newly formulated photorefractive composite based on molecular triphenyldiamine photosensitized with C60. Through this approach, response times of 399 μs are observed, opening the door for video and other high-speed applications. It is further demonstrated that this improvement in response time occurs with little sacrifice in photorefractive efficiency, with internal diffraction efficiencies of 72% and two-beam-coupling gain coefficients of 500 cm-1 being measured. A thorough analysis of the experimental data is presented, supporting the hypothesized mechanism of enhanced charge mobility without the accompaniment of superfluous traps. It is anticipated that this approach can play a significant role in the eventual commercialization of this class of materials.
In this formation of nano-particles during coal char combustion, the vaporization of inorganic components in char and the subsequent homogeneous particle nucleation, heterogeneous condensation, coagulation, and coalescence play decisive roles. Furthermore, conventional measurements cannot provide detailed information on the dynamics of nano-particle formation and evolution, In this study, a sophisticated intrinsic char kinetics model that considers ash effects (including ash film formation, ash dilution, and ash vaporization acting in tandem), both oxidation and gasification by CO2 and H2O, homogeneous particle nucleation, heterogeneous vapor condensation, coagulation, and and coalescence mechanisms is developed and used to compare the temporal evolution of the number and size of nano-particles during coal char particle combustion as a function of char particle size, ash content, and oxygen content in O2/N2 and O2/CO2 atmospheres .
Active participation in international R&D is crucial for achieving the UFD long-term goals of conducting “experiments to fill data needs and confirm advanced modeling approaches” (by 2015) and of having a “robust modeling and experimental basis for evaluation of multiple disposal system options” (by 2020). DOE’s Office of Nuclear Energy (NE) and its Office of Used Fuel Disposition Research and Development (UFD) have developed a strategic plan to advance cooperation with international partners. The international collaboration on the evaluation of crystalline disposal media at Sandia National Laboratories (SNL) in FY16 focused on the following four activities: (1) thermal-hydrologic-mechanical-chemical modeling single fracture evolution; (2) simulations of flow and transport in Bedrichov Tunnel, Czech Republic, (3) completion of streaming potential testing at Korean Atomic Energy Research Institute (KAERI), and (4) technical data exchange with KAERI on thermal-hydrologic-mechanical (THM) properties and specifications of bentonite buffer materials. The first two activities are part of the Development of Coupled Models and their Validation against Experiments (DECOVALEX-2015) project.
Community energy planning is a vital component of successful energy resource development and project implementation. Planning can help tribes develop a shared vision and strategies to accomplish their energy goals. This paper explores the benefits of an asset-based approach to tribal community energy planning. While a framework for community energy planning and federal funding already exists, some areas of difficulty in the planning cycle have been identified. This paper focuses on developing a planning framework that offsets those challenges. The asset-based framework described here takes inventory of a tribe’s capital assets, such as: land capital, human capital, financial capital, and political capital. Such an analysis evaluates how being rich in a specific type of capital can offer a tribe unique advantages in implementing their energy vision. Finally, a tribal case study demonstrates the practical application of an asset-based framework.
Lignin valorization is viewed as a key for the development of a cost effective lignocellulosic biorefinery, and synthetic biology tools would play an important role in the construction of an efficient chassis towards this goal. In this study, we have employed a hybrid promoter engineering approach for the construction of higher strength phenolics inducible promoters.
This paper uses molecular dynamics simulations to study surface and interface properties of PdHx that are relevant to hydrogen storage applications. In particular, surface energies, interfacial energies, surface diffusivities, and surface segregations are all determined as a function of temperature and composition. During the course of the calculations, we demonstrated robust molecular dynamics methods that can result in highly converged finite temperature properties. Challenging examples include accurate calculations of hydrogen surface diffusivities that account for all possible atomic jump mechanisms, and constructions of surface segregation composition profiles that have negligible statistical errors. Our robust calculations reveal that the Arrhenius plots of hydrogen surface diffusion is ideally linear at low compositions, and becomes nonlinear at high compositions. The fundamental cause for this behavior has been identified. This nonlinear surface diffusion behavioe is also in good agreement with available experimental data for bulk diffusion. The implication of our calculated properties on hydrogen storage application discussed.
We describe a very compact (0.9 m high, 0.4 m diameter, 40 kg) battery operable neutron scatter camera designed for field deployment. Unlike most other systems, the configuration of the sixteen liquid-scintillator detection cells are arranged to provide omnidirectional (4π) imaging with sensitivity comparable to a conventional two-plane system. Although designed primarily to operate as a neutron scatter camera for localizing energetic neutron sources, it also functions as a Compton camera for localizing gamma sources. In addition to describing the radionuclide source localization capabilities of this system, we demonstrate how it provides neutron spectra that can distinguish plutonium metal from plutonium oxide sources, in addition to the easier task of distinguishing AmBe from fission sources.
Recent advances in nanotechnology have enabled researchers to control individual quantum mechanical objects with unprecedented accuracy, opening the door for both quantum and extreme-scale conventional computing applications. As these devices become larger and more complex, the ability to design them such that they can be simply controlled becomes a daunting and computationally infeasible task. Here, motivated by ideas from compressed sensing, we introduce a protocol for the Compressed Optimization of Device Architectures (CODA). It leads naturally to a metric for benchmarking device performance and optimizing device designs, and provides a scheme for automating the control of gate operations and reducing their complexity. Because CODA is computationally efficient, it is readily extensible to large systems. As a result, we demonstrate the CODA benchmarking and optimization protocols through simulations of up to eight quantum dots in devices that are currently being developed experimentally for quantum computation.
Radiocarbon in CO2 (14CO2) measurements can aid in discriminating between fast (<1 year) and slower (>5–10 years) cycling of C between the atmosphere and the terrestrial biosphere due to the 14C disequilibrium between atmospheric and terrestrial C. However, 14CO2 in the atmosphere is typically much more strongly impacted by fossil fuel emissions of CO2, and, thus, observations often provide little additional constraints on respiratory flux estimates at regional scales. Here we describe a data set of 14CO2 observations from a tall tower in northern Wisconsin (USA) where fossil fuel influence is far enough removed that during the summer months, the biospheric component of the 14CO2 budget dominates. We find that the terrestrial biosphere is responsible for a significant contribution to 14CO2 that is 2–3 times higher than predicted by the Carnegie-Ames-Stanford approach terrestrial ecosystem model for observations made in 2010. This likely includes a substantial contribution from the North American boreal ecoregion, but transported biospheric emissions from outside the model domain cannot be ruled out. The 14CO2 enhancement also appears somewhat decreased in observations made over subsequent years, suggesting that 2010 may be anomalous. With these caveats acknowledged, we discuss the implications of the observation/model comparison in terms of possible systematic biases in the model versus short-term anomalies in the observations. Going forward, this isotopic signal could be exploited as an important indicator to better constrain both the long-term carbon balance of terrestrial ecosystems and the short-term impact of disturbance-based loss of carbon to the atmosphere.
Four sets of nonreactive solute transport experiments were conducted with micromodels. Each set consisted of three experiments with one variable, i.e., flow velocity, grain diameter, pore-aspect ratio, and flow-focusing heterogeneity. The data sets were offered to pore-scale modeling groups to test their numerical simulators. Each set consisted of two learning experiments, for which all results were made available, and one challenge experiment, for which only the experimental description and base input parameters were provided. The experimental results showed a nonlinear dependence of the transverse dispersion coefficient on the Peclet number, a negligible effect of the pore-aspect ratio on transverse mixing, and considerably enhanced mixing due to flow focusing. Five pore-scale models and one continuum-scale model were used to simulate the experiments. Of the pore-scale models, two used a pore-network (PN) method, two others are based on a lattice Boltzmann (LB) approach, and one used a computational fluid dynamics (CFD) technique. The learning experiments were used by the PN models to modify the standard perfect mixing approach in pore bodies into approaches to simulate the observed incomplete mixing. The LB and CFD models used the learning experiments to appropriately discretize the spatial grid representations. For the continuum modeling, the required dispersivity input values were estimated based on published nonlinear relations between transverse dispersion coefficients and Peclet number. Comparisons between experimental and numerical results for the four challenge experiments show that all pore-scale models were all able to satisfactorily simulate the experiments. The continuum model underestimated the required dispersivity values, resulting in reduced dispersion. The PN models were able to complete the simulations in a few minutes, whereas the direct models, which account for the micromodel geometry and underlying flow and transport physics, needed up to several days on supercomputers to resolve the more complex problems.
A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV and a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm2 rising to 5000 cm2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm2 and 2500 cm2. The multiplicity mode was found to be sensitive to the incident neutron angular distribution.
In a common electric power plant, heat is used to boil water into steam which drives a turbine. The steam from the turbine outlet is condensed with cooling water. This is the common Rankine cycle and, even after decades of development is relatively inefficient and water intensive. Alternatively, a closed Brayton cycle recirculates the working fluid, and the turbine exhaust is used in a recuperating heat exchanger to heat the turbine feed. A "supercritical cycle' is a closed Brayton cycle in which the working fluid, such as supercritical carbon dioxide (sCO2), is maintained above the critical point during the compression phase of the cycle. The key property of the fluid near its critical point is its higher gas density, closer to that of a liquid than of a gas, allowing for the pumping power in the compressor to be significantly reduced resulting in improved efficiency. Other advantages include smaller component size and the reduced use of water, not only due to the increased efficiency, but also due sensible heat rejection which facilitates dry air cooling compared to air-cooled steam condensers. A Sandia National Laboratories commercialization review concluded that the technology has applicability across various power generation applications including fossil fuels, concentrated solar power and nuclear power. In 2006, Sandia National Laboratories (SNL), recognizing the potential advantages of a higher efficiency power cycle, used internal funds to establish a testing capability and began partnering with the U.S. Department of Energy Office of Nuclear Energy to develop a laboratory-scale test assembly to show the viability of the underlying science and demonstrate system performance. Since that time, SNL has generated power, verified cycle performance, and developed cycle controls and maintenance procedures. The test assembly has successfully operated in different configurations (simple Brayton, waste heat cycle, and recompression) and tested additives to the s-CO2 working fluid. Our current focus is to partner with industry and develop cycle components and control strategies sufficient to support a successful commercial offering. This paper has been developed for the Energy Policy Institute's (EPI's) 6th Annual Energy Policy Research Conference scheduled for 8 & 9 September 2016 in Santa Fe, NM. We describe the cycle in more detail and describe specific benefits and applications. The paper will also include current technology development activities and future plans.
Alaska oil fields provide an important, but diminishing, portion of the crude oil processed by Alaska and U.S. West Coast refineries. Production of crude oil in Alaska is being stressed by declining production in mature fields, high costs for developing and producing new fields, increasing competition from tight oil production in the Lower 48 states, and low global oil prices. The National Transportation Fuel Model is a network model of petroleum infrastructure in the Lower 48 states and portions of Canada developed at Sandia National Laboratories. It provides a simulation capability for analysis of system-wide responses to stressing events. Until now, however, this model did not explicitly include the petroleum infrastructure of Alaska and the transport of crude oil by marine shipments from Alaska to West Coast refineries. This paper describes the methods and information requirements for adding Alaska infrastructure to the National Transportation Fuel Model, provides an overview of the new Alaska portion of the model, and presents an example simulation of a closure of a large San Francisco refinery.
The purpose of this paper is to investigate the structural behavior of aluminum alloys used in the aerospace industry when exposed to conditions similar to those of an accident scenario, such as a fuel fire. This study focuses on the role that the aluminum oxide layer plays in the deformation and the strength of the alloy above melting temperature. To replicate some of the thermal and atmospheric conditions that the alloys might experience in an accident scenario, aluminum rod specimens were subjected to temperatures near to or above their melting temperature in air, nitrogen, and vacuum environments. The characteristics of their deformation, such as geometry and rate of deformation, were observed. Tests were conducted by suspending aluminum rods vertically from an enclosure. This type of experiment was performed in two different environments: air and nitrogen. The change in environments allowed the effects of the oxide layer on the material strength to be analyzed by inhibiting the growth of the oxide layer. Observations were reported from imaging taken during the experiment showing creep behavior of aluminum alloys at elevated temperatures and time to failure. In addition, an example of tensile load-displacement data obtained in air and vacuum was reported to understand the effect of oxide layer on aluminum deformation and strength.
We report the successful growth of high-quality SrO films on highly-ordered pyrolytic graphite (HOPG) and single-layer graphene by molecular beam epitaxy. The SrO layers have (001) orientation as confirmed by X-ray diffraction (XRD) while atomic force microscopy measurements show continuous pinhole-free films having rms surface roughness of <1.5 Å. Transport measurements of exfoliated graphene after SrO deposition show a strong dependence between the Dirac point and Sr oxidation. Subsequently, the SrO is leveraged as a buffer layer for more complex oxide integration via the demonstration of (001) oriented SrTiO3 grown atop a SrO/HOPG stack.
Molecular dynamics simulations have been used to analyse microstructures of CdTe films grown on {112} surfaces of zinc-blende CdS. Interestingly, CdTe films grow in 331 orientations as opposed to 112 epitaxial orientations. At the CdTe-{331}/CdS-{112} interface, however, there exists an axis that is parallel to the 110 orientation of both CdS and CdTe. It is the direction orthogonal to this 110 that becomes different, being 116 for CdTe and 111 for CdS, respectively. Missing CdTe-{110} planes are found along the 110 axis, suggesting that the misfit strain is released by the conventional misfit dislocation mechanism along this axis. In the orthogonal axis, the misfit strain is found to be more effectively released by the new grain orientation mechanism. Our finding is supported by literature experimental observations of the change of growth direction when Cd0.96Zn0.04Te films are deposited on GaAs. Analyses of energetics clearly demonstrate the cause for the formation of the new orientation, and the insights gained from our studies can help understand the grain structures experimentally observed in lattice mismatched systems.
This paper presents a method for improved auscultation with an electronic stethoscope by estimating and removing the effects of unknown disturbance inputs. By replacing the single transducer in a stethoscope with a dual piezo transducer assembly, it is shown that an inverse dynamic mapping can be used to relate the two measured signals to original directional inputs acting on the stethoscope. Specifically, model inversion is used to estimate and remove physician handling noise from chest sound signals. An experimental test platform which uses a vibration shaker to simulate the desired auscultation signal is used to experimentally demonstrate the feasibility of the dual-piezo stethoscope approach in improving auscultation.
We perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understood by comparison with relevant time scales in the systems, obtained from independent calculations.
Isotropic von Mises and anisotropic Hill yield surfaces for Al 7079 were fit using experimental data gathered from 12 dog-bone specimens that captured the highly variable microstructural texture of the aluminum alloy. Strain gauges or the digital image correlation technique were utilized to determine the strain histories in the specimen as they were subjected to uniaxial tension. The final yield surface fits displayed a high degree of variability that was dependent upon how the yield functions were calculated, i.e. which size and shape information was used. The findings display that a model with a higher number of anisotropic parameters is needed to better and more consistently capture the anisotropic properties of Al 7079, such as the Barlat, Yld2004-18, model that has 20 parameters.
A method for providing non-diffuse transport of material quantities in arbitrary Lagrangian-Eulerian (ALE) dynamic solid mechanics computations is presented. ALE computations are highly desirable for simulating dynamic problems that incorporate multiple materials and large deformations. Despite the advantages of using ALE for such problems, the method is associated with diffusion of material quantities due to the advection transport step of the computational cycle. This drawback poses great difficulty for applications of material failure for which discrete features are important, but are smeared out as a result of the diffusive advection operation. The focus of this work is an ALE method that incorporates transport of variables on discrete, massless points that move with the velocity field, referred to as Lagrangian material tracers (LMT), and consequently prevents diffusion of certain material quantities of interest. A detailed description of the algorithm is provided along with discussion of its computational aspects. Simulation results include a simple proof of concept, verification using a manufactured solution, and fragmentation of a uniformly loaded thin ring that clearly demonstrates the improvement offered by the ALE LMT method.
Methods for processing recorded data and efficiently screening experimental results from ducted fuel injection (DFI) experiments for soot mitigation in diesel engines are described. Specifically, a method for locating the spray tip in natural luminosity movies is detailed. DFI implementations are analyzed and are seen to significantly lower soot levels.
Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. We subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-term treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are "keystone" OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations.
Here, a liquid bi-propellant rocket engine and supporting infrastructure has been de-signed, constructed, and tested at New Mexico Institute of Mining and Technology ina cooperative effort with Sandia National Laboratories. The modular engine designconsists of a head-end fuel-oxidizer injector, gaseous H2/02 torch ignitor, combustionchamber, and nozzle modules. The robust modular design allows for rapid config-uration changes and component replacement if damaged in testing.
We calculated the force-extension curves for a flexible polyelectrolyte chain with varying charge separations by performing Monte Carlo simulations of a 5000 bead chain using a screened Coulomb interaction. At all charge separations, the force-extension curves exhibit a Pincus-like scaling regime at intermediate forces and a logarithmic regime at large forces. As the charge separation increases, the Pincus regime shifts to a larger range of forces and the logarithmic regime starts are larger forces. We also found that force-extension curve for the corresponding neutral chain has a logarithmic regime. Decreasing the diameter of bead in the neutral chain simulations removed the logarithmic regime, and the force-extension curve tends to the freely jointed chain limit. In conclusion, this result shows that only excluded volume is required for the high force logarithmic regime to occur.
Aqueous dissolution of silicate glasses and minerals plays a critical role in global biogeochemical cycles and climate evolution. The reactivity of these materials is also important to numerous engineering applications including nuclear waste disposal. The dissolution process has long been considered to be controlled by a leached surface layer in which cations in the silicate framework are gradually leached out and replaced by protons from the solution. This view has recently been challenged by observations of extremely sharp corrosion fronts and oscillatory zonings in altered rims of the materials, suggesting that corrosion of these materials may proceed directly through congruent dissolution followed by secondary mineral precipitation. Here we show that complex silicate material dissolution behaviors can emerge from a simple positive feedback between dissolution-induced cation release and cation-enhanced dissolution kinetics. This self-accelerating mechanism enables a systematic prediction of the occurrence of sharp dissolution fronts (vs. leached surface layers), oscillatory dissolution behaviors and multiple stages of glass dissolution (in particular the alteration resumption at a late stage of a corrosion process). Our work provides a new perspective for predicting long-term silicate weathering rates in actual geochemical systems and developing durable silicate materials for various engineering applications.
An AlN barrier high electron mobility transistor (HEMT) based on the AlN/Al0.85Ga0.15N heterostructure was grown, fabricated, and electrically characterized, thereby extending the range of Al composition and bandgap for AlGaN channel HEMTs. An etch and regrowth procedure was implemented for source and drain contact formation. A breakdown voltage of 810 V was achieved without a gate insulator or field plate. Excellent gate leakage characteristics enabled a high Ion/Ioff current ratio greater than 107 and an excellent subthreshold slope of 75 mV/decade. A large Schottky barrier height of 1.74 eV contributed to these results. In conclusion, the room temperature voltage-dependent 3-terminal off-state drain current was adequately modeled with Frenkel-Poole emission.
Demonstration of Al00.3Ga0.7N PN diodes grown with breakdown voltages in excess of 1600 V is reported. The total epilayer thickness is 9.1 μm and was grown by metal-organic vapour-phase epitaxy on 1.3-mm-thick sapphire in order to achieve crack-free structures. A junction termination edge structure was employed to control the lateral electric fields. A current density of 3.5 kA/cm2 was achieved under DC forward bias and a reverse leakage current <3 nA was measured for voltages <1200 V. The differential on-resistance of 16 mΩ cm2 is limited by the lateral conductivity of the n-type contact layer required by the front-surface contact geometry of the device. An effective critical electric field of 5.9 MV/cm was determined from the epilayer properties and the reverse current–voltage characteristics. To our knowledge, this is the first aluminium gallium nitride (AlGaN)-based PN diode exhibiting a breakdown voltage in excess of 1 kV. Finally, we note that a Baliga figure of merit (Vbr2/Rspec,on) of 150 MW/cm2 found is the highest reported for an AlGaN PN diode and illustrates the potential of larger-bandgap AlGaN alloys for high-voltage devices.
Rimmed grooves, lineations and elongate craters around Mare Imbrium shape much of the nearside Moon. This pattern was coined the Imbrium Sculpture, and it was originally argued that it must have been formed by a giant oblique (∼30°) impact, a conclusion echoed by later studies. Some investigators, however, noticed that many elements of the Imbrium Sculpture are not radial to Imbrium, thereby implicating an endogenic or structural origin. Here we use these non-radial trends to conclude that the Imbrium impactor was a proto-planet (half the diameter of Vesta), once part of a population of large proto-planets in the asteroid belt. Such independent constraints on the sizes of the Imbrium and other basin-forming impactors markedly increase estimates for the mass in the asteroid belt before depletion caused by the orbital migration of Jupiter and Saturn. Moreover, laboratory impact experiments, shock physics codes and the groove widths indicate that multiple fragments (up to 2% of the initial diameter) from each oblique basin-forming impactor, such as the one that formed Imbrium, should have survived planetary collisions and contributed to the heavy impact bombardment between 4.3 and 3.8 billion years ago.
Wu, Chongzhao; Khanal, Sudeep; Reno, John L.; Kumar, Sushil
Plasmonic lasers (spasers) generate coherent surface plasmon polaritons (SPPs) and could be realized at subwavelength dimensions in metallic cavities for applications in nanoscale optics. Plasmonic cavities are also utilized for terahertz quantum-cascade lasers (QCLs), which are the brightest available solid-state sources of terahertz radiation. A long standing challenge for spasers that are utilized as nanoscale sources of radiation, is their poor coupling to the far-field radiation. Unlike conventional lasers that could produce directional beams, spasers have highly divergent radiation patterns due to their subwavelength apertures. Here, we theoretically and experimentally demonstrate a new technique for implementing distributed feedback (DFB) that is distinct from any other previously utilized DFB schemes for semiconductor lasers. The so-termed antenna-feedback scheme leads to single-mode operation in plasmonic lasers, couples the resonant SPP mode to a highly directional far-field radiation pattern, and integrates hybrid SPPs in surrounding medium into the operation of the DFB lasers. Experimentally, the antenna-feedback method, which does not require the phase matching to a well-defined effective index, is implemented for terahertz QCLs, and single-mode terahertz QCLs with a beam divergence as small as 4° × 4° are demonstrated, which is the narrowest beam reported for any terahertz QCL to date. Moreover, in contrast to a negligible radiative field in conventional photonic band-edge lasers, in which the periodicity follows the integer multiple of half-wavelengths inside the active medium, antennafeedback breaks this integer limit for the first time and enhances the radiative field of the lasing mode. Terahertz lasers with narrow-beam emission will find applications for integrated as well as standoff terahertz spectroscopy and sensing. The antenna-feedback scheme is generally applicable to any plasmonic laser with a Fabry-Perot cavity irrespective of its operating wavelength and could bring plasmonic lasers closer to practical applications.
Park, Samuel; Baranov, Dmitry; Ryu, Jisu; Jonas, David
Pump-probe polarization anisotropy measurements with 15 fs pulses are employed to investigate the electronic structure of PbS quantum dots. Here, the initial anisotropy at the bandgap is anomalously low (<0.1) and suggests large electronic couplings.
Of the non-corrupted data collected by the Orbiting Experiment (forté) satellite’s Photo-Diode Detector during the year 2001, I estimate that 7.9% of 914 894 signals are noise. My result differs dramatically from Guillen’s estimate of 96%. To arrive at this estimate, I used Gaussian mixture model (GMM) clustering–unsupervised machine learning–to aggregate the wave forms into groups based on the absolute value of the lowest 25 positive frequency discrete Fourier transform coefficients. Then, I marked several of the groups as noise by inspecting a random sampling of wave forms from each group. Marking groups as either noise or non-noise is a supervised binary classification operation. After removing the signals in noise groups from further consideration, I clustered the remaining signals into families. Again, I used a GMM, but for the familial clustering I used a Non-Negative Matrix Factorization feature vector transform. The result was 9 distinct families of lightning signals, as well as a second stage of noise filtering. To efficiently represent the entirety of the signal space, I broke each family into deciles based on their distance from the family mean. In this case, distance means the log-likelihood based on the GMM. Signals in lower deciles are more similar in shape and amplitude to their family average. I took the top 200 samples from each decile of each group, resulting in 18 000 signals. These signal approximately represent the entirety of the forté observations. To represent outliers, I also kept a zoo of the 1000 signals furthest from any family’s average. All told, the resulting data set represents the forté data with a reduction of about 51:1. To allow synthesis of an arbitrarily large number of test signals, I also captured each family’s average signal and the time-sample covariance matrix over the signals in each family. Using these two pieces of information, I can synthesize new waveforms by using a Gaussian random realization from the family average and covariance matrix. I wrote a program to test the synthesis quality. The program shows me two signals on the screen, one synthesized and one randomly drawn from the data. I attempted to identify the synthesized signal. Although the synthesis is imperfect, in an A/B comparison I only correctly chose the synthesized signal 36% of the time.
Graph algorithms are challenging to parallelize on manycore architectures due to complex data dependencies and irregular memory access. We consider the well studied problem of coloring the vertices of a graph. In many applications it is important to compute a coloring with few colors in near-lineartime. In parallel, the optimistic (speculative) coloring method by Gebremedhin and Manne is the preferred approach but it needs to be modified for manycore architectures. We discuss a range of implementation issues for this vertex-based optimistic approach. We also propose a novel edge-based optimistic approach that has more parallelism and is better suited to GPUs. We study the performance empirically on two architectures(Xeon Phi and GPU) and across many data sets (from finite element problems to social networks). Our implementation uses the Kokkos library, so it is portable across platforms. We show that on GPUs, we significantly reduce the number of colors (geometric mean 4X, but up to 48X) as compared to the widely used cuSPARSE library. In addition, our edge-based algorithm is 1.5 times faster on average than cuSPARSE, where it hasspeedups up to 139X on a circuit problem. We also show the effect of the coloring on a conjugate gradient solver using multi-colored Symmetric Gauss-Seidel method as preconditioner, the higher coloring quality found by the proposed methods reduces the overall solve time up to 33% compared to cuSPARSE.
Application performance data accounting for resource contention and other external influences is highly coveted and extremely difficult to obtain. «Why did my application's performance change from the last time it ran?» is a question shared by application developers, program analysts, and system administrators. The answer to this question impacts nearly all programmatic and R&D efforts related to high-performance computing (HPC). Lightweight, right-fidelity monitoring infrastructures that can gather relevant application and resource performance data across the entire HPC platform can help address this research topic. This short technical paper will formally define an ongoing research effort to define the needed metrics and methods that distill the vast quantities of available data to a minimum set of actionable and interpretable quantities that can be used by application developers, system administrators, production analysts, and HPC platform designers for their respective production and R&D focus areas.
Issues of High Performance Computer (HPC) system diagnosis, automated system management, and resource-aware computing, are all dependent on high fidelity, system wide, persistent monitoring. Development and deployment of an effective persistent system wide monitoring service at large-scale presents a number of challenges, particularly when collecting data at the granularities needed to resolve features of interest and obtain early indication of significant events on the system. In this paper we provide experiences from our developments on and two-year deployment of our Lightweight Distributed Metric Service (LDMS) monitoring system on NCSA's 27,648 node Blue Waters system. We present monitoring related challenges and issues and their effects on the major functional components of general monitoring infrastructures and deployments: Data Sampling, Data Aggregation, Data Storage, Analysis Support, Operations, and Data Stewardship. Based on these experiences, we providerecommendations for effective development and deployment of HPC monitoring systems.
Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
Sanchez, S.; Bonnie, A.; Van Heule, G.; Robinson, C.; Deconinck, A.; Kelly, K.; Snead, Q.; Brandt, James M.
Over the past decade, platforms at Los AlamosNational Laboratory (LANL) have experienced large increases in complexity and scale to reach computational targets. The changes to the compute platforms have presented new challenges to the production monitoring systems in which they must not only cope with larger volumes of monitoring data, but also must provide new capabilities for the management, distribution, and analysis of this data. This schema must support both real-time analysis for alerting on urgent issues, as well as analysis of historical data for understanding performance issues and trends in systembehavior. This paper presents the design of our proposed next-generation monitoring system, as well as implementation details for an initial deployment. This design takes the form of a multi-stage data processing pipeline, including a scalable cluster for data aggregation and early analysis, a message broker for distribution of this data to varied consumers, and an initial selection of consumer services for alerting and analysis. We will also present estimates of the capabilities and scale required to monitor two upcoming compute platforms at LANL.
Scalable sparse LU factorization is critical for efficient numerical simulation of circuits and electrical power grids. In this work, we present a new scalable sparse direct solver called Basker. Basker introduces a new algorithm to parallelize the Gilbert-Peierls algorithm for sparse LU factorization. As architectures evolve, there exists a need for algorithms that are hierarchical in nature to match the hierarchy in thread teams, individual threads, and vector level parallelism. Basker is designed to map well to this hierarchy in architectures. There is also a need for data layouts to match multiple levels of hierarchy in memory. Basker uses a two-dimensional hierarchical structure of sparse matrices that maps to the hierarchy in the memory architectures and to the hierarchy in parallelism. We present performance evaluations of Basker on the Intel SandyBridge and Xeon Phi platforms using circuit and power grid matrices taken from the University of Florida sparse matrix collection and from Xyce circuit simulations. Basker achieves a geometric mean speedup of 5.91× on CPU (16 cores) and 7.4× on Xeon Phi (32 cores) relative to KLU. Basker outperforms Intel MKL Pardiso (PMKL) by as much as 30× on CPU (16 cores) and 7.5× on Xeon Phi (32 cores) for low fill-in circuit matrices. Furthermore, Basker provides 5.4× speedup on a challenging matrix sequence taken from an actual Xyce simulation.
Ultrafast pure-rotational CARS is applied to an aluminized ammonium-perchlorate propellant flame. Background-free spectra were acquired in this challenging high-temperature, particle-laden environment and successfully fit for temperature and oxygen/nitrogen ratio using a simple theoretical model.
Given the unique optical properties of LiF, it is often used as an observation window in high-temperature and -pressure experiments; hence, estimates of its transmission properties are necessary to interpret observations. Since direct measurements of the thermal conductivity of LiF at the appropriate conditions are difficult, we resort to molecular simulation methods. Using an empirical potential validated against ab initio phonon density of states, we estimate the thermal conductivity of LiF at high temperatures (1000-4000 K) and pressures (100-400 GPa) with the Green-Kubo method. We also compare these estimates to those derived directly from ab initio data. To ascertain the correct phase of LiF at these extreme conditions, we calculate the (relative) phase stability of the B1 and B2 structures using a quasiharmonic ab initio model of the free energy. We also estimate the thermal conductivity of LiF in an uniaxial loading state that emulates initial stages of compression in high-stress ramp loading experiments and show the degree of anisotropy induced in the conductivity due to deformation.
Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems - enabling asynchronous data transfers, so that applications may fully utilize all CPU resources while simultaneously sharing data amongst remote nodes. We examined this network-induced memory contention (NiMC), the interactions between RDMA and the memory subsystem when applications and out-of-band services compete for memory resources, and NiMC's resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantified NiMC and show that NiMC's impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. We also evaluated three potential techniques to reduce NiMC's performance impact, namely hardware offloading, core reservation and software-based network throttling. While all three of these solutions show promise, we provide guidelines that help select the best solution for a given environment.
All many-core systems require fine-grained shared memory parallelism, however the most efficient way to extract such parallelism is far from trivial. Fine-grained parallel algorithms face various performance trade-offs related to tasking, accesses to global data-structures, and use of shared cache. While programming models provide high level abstractions, such as data and task parallelism, algorithmic choices still remain open on how to best implement irregular algorithms, such as sparse factorizations, while taking into account the trade-offs mentioned above. In this paper, we compare these performance trade-offs for task and data parallelism on different hardware architectures such as Intel Sandy Bridge, Intel Xeon Phi, and IBM Power8. We do this by comparing the scaling of a new task-parallel incomplete sparse Cholesky factorization called Tacho and a new data-parallel incomplete sparse LU factorization called Basker. Both solvers utilize Kokkos programming model and were developed within the ShyLU package of Trilinos. Using these two codes we demonstrate how high-level programming changes affect performance and overhead costs on multiple multi/many-core systems. We find that Kokkos is able to provide comparable performance with both parallel-for and task/futures on traditional x86 multicores. However, the choice of which high-level abstraction to use on many-core systems depends on both the architectures and input matrices.
Aluminized propellants produce molten particulates of variable size and temperature. In this work, sizes and three-dimensional positions are determined using digital in-line holography with a pulsed laser. Simultaneously, particle temperatures are measured using two-color pyrometry.
Digital in-line holography (DIH) quantifies the fragments formed when a drop impacts a thin film. High-speed recording allows for quantification of transient dynamics. For the viscous liquids investigated here, a multimodal size distribution is observed.
The in-situ hydrolysis and subsequent condensation reaction of the chemical agent simulant diethyl chlorophosphate (DECP) was characterized by high-resolution 31P NMR spectroscopy following the addition of water in sub-equimolar concentrations. The identification and quantification of the multiple pyrophosphate and larger polyphosphate chemical species formed through a series of self-condensation reactions are reported. The DECP hydrolysis kinetics and distribution of breakdown species was strongly influenced by the water concentration and reaction temperature.
The bearings used in energy storage flywheels dissipate a significant amount of energy and can fail catastrophically. Magnetic bearings would both reduce energy dissipation and increase flywheel reliability. The component of magnetic bearing that creates lift is a magnetically soft material embedded into a rebate cut into top of the inner annulus of the flywheel. Because the flywheels stretch about 1% as they spin up, this magnetic material must also stretch and be more compliant than the flywheel itself, so it does not part from the flywheel during spin up. At the same time, the material needs to be sufficiently stiff that it does not significantly deform in the rebate and must have a sufficiently large magnetic permeability and saturation magnetization to provide the required lift. It must also have high electrical resistivity to prevent heating due to eddy currents. In this paper we investigate whether adequately magnetic, mechanically stiff composites that have the tensile elasticity, high electrical resistivity, permeability and saturation magnetism required for flywheel lift magnet applications can be fabricated. We find the best composites are those comprised of bidisperse Fe particles in the resin G/Flex 650. The primary limiting factor of such materials is the fatigue resistance to tensile strain.
The transient transport of electrolytes in thermally-activated batteries is studied using electron probe micro-analysis (EPMA), demonstrating the robust capability of EPMA as a useful tool for studying and quantifying mass transport within porous materials, particularly in difficult environments where classical flow measurements are challenging. By tracking the mobility of bromine and potassium ions from the electrolyte stored within the separator into the lithium silicon anode and iron disulfide cathode, we are able to quantify the transport mechanisms and physical properties of the electrodes including permeability and tortuosity. Due to the micron to submicron scale porous structure of the initially dry anode, a fast capillary pressure driven flow is observed into the anode from which we are able to set a lower bound on the permeability of 10-1 mDarcy. The transport into the cathode is diffusion-limited because the cathode originally contained some electrolyte before activation. Using a transient one-dimensional diffusion model, we estimate the tortuosity of the cathode electrode to be 2.8 ± 0.8.
Durfee, Paul N.; Lin, Yu-Shen; Dunphy, Darren R.; Muniz, Ayse J.; Butler, Kimberly S.; Humphrey, Kevin R.; Lokke, Amanda J.; Agola, Jacob O.; Chou, Stanley S.; Chen, I-Ming; Wharton, Walker; Townson, Jason L.; Willman, Cheryl L.; Brinker, C.J.
Many nanocarrier cancer therapeutics currently under development, as well as those used in the clinical setting, rely upon the enhanced permeability and retention (EPR) effect to passively accumulate in the tumor microenvironment and kill cancer cells. In leukemia, where leukemogenic stem cells and their progeny circulate within the peripheral blood or bone marrow, the EPR effect may not be operative. Thus, for leukemia therapeutics, it is essential to target and bind individual circulating cells. Here in this research, we investigate mesoporous silica nanoparticle (MSN)-supported lipid bilayers (protocells), an emerging class of nanocarriers, and establish the synthesis conditions and lipid bilayer composition needed to achieve highly monodisperse protocells that remain stable in complex media as assessed in vitro by dynamic light scattering and cryo-electron microscopy and ex ovo by direct imaging within a chick chorioallantoic membrane (CAM) model. We show that for vesicle fusion conditions where the lipid surface area exceeds the external surface area of the MSN and the ionic strength exceeds 20 mM, we form monosized protocells (polydispersity index <0.1) on MSN cores with varying size, shape, and pore size, whose conformal zwitterionic supported lipid bilayer confers excellent stability as judged by circulation in the CAM and minimal opsonization in vivo in a mouse model. Having established protocell formulations that are stable colloids, we further modified them with anti-EGFR antibodies as targeting agents and reverified their monodispersity and stability. Then, using intravital imaging in the CAM, we directly observed in real time the progression of selective targeting of individual leukemia cells (using the established REH leukemia cell line transduced with EGFR) and delivery of a model cargo. In conclusion, overall we have established the effectiveness of the protocell platform for individual cell targeting and delivery needed for leukemia and other disseminated disease.
Here, transcranial direct current stimulation (tDCS) is a potent ial tool for alleviating various forms of cognitive decline, including memory loss, in older adults. However, past effects of tDCS on cognitive ability have been mixed. One important potential moderator of tDCS effects is the baseline level of cognitive performance. We tested the effects of tDCS on face-name associative memory in older adults, who suffer from performance deficits in this task relative to younger adults. Stimulation was applied to the left inferior prefrontal cortex during encoding of face-name pairs, and memory was assessed with both a recognition and recall task. As a result, face–name memory performance was decreased with the use of tDCS. This result was driven by increased false alarms when recognizing rearranged face–name pairs.
Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be defined through estimation. The objectives of this study deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. The presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.
This review focuses on the striking recent progress in solving for hydrophobic interactions between small inert molecules. We discuss several new understandings. First, the inverse temperature phenomenology of hydrophobic interactions, i.e., strengthening of hydrophobic bonds with increasing temperature, is decisively exhibited by hydrophobic interactions between atomic-scale hard sphere solutes in water. Second, inclusion of attractive interactions associated with atomic-size hydrophobic reference cases leads to substantial, nontrivial corrections to reference results for purely repulsive solutes. Hydrophobic bonds are weakened by adding solute dispersion forces to treatment of reference cases. The classic statistical mechanical theory for those corrections is not accurate in this application, but molecular quasi-chemical theory shows promise. Finally, because of the masking roles of excluded volume and attractive interactions, comparisons that do not discriminate the different possibilities face an interpretive danger.
This study introduces dual-resolution Raman spectroscopy as a novel diagnostics approach for measurements of temperature and species in flames where multiple hydrocarbons are present. Simultaneous measurement of multiple hydrocarbons is challenging because their vibrational Raman spectra in the C–H stretch region are closely overlapped and are not well known over the range of temperature encountered in flames. Overlap between the hydrocarbon spectra is mitigated by adding a second spectrometer, with a higher dispersion grating, to collect the Raman spectra in the C–H stretch region. A dual-resolution Raman spectroscopy instrument has been developed and optimized for measurements of major species (N2, O2, H2O, CO2, CO, H2, DME) and major combustion intermediates (CH4, CH2O, C2H2, C2H4 and C2H6) in DME–air flames. The temperature dependences of the hydrocarbon Raman spectra over fixed spectral regions have been determined through a series of measurements in laminar Bunsen-burner flames, and have been used to extend a library of previously acquired Raman spectra up to flame temperature. The paper presents the first Raman measurements of up to twelve species in hydrocarbon flames, and the first quantitative Raman measurements of formaldehyde in flames. Lastly, the accuracy and precision of the instrument are determined from measurements in laminar flames and the applicability of the instrument to turbulent DME–air flames is discussed.
We have developed a four-channel optically pumped atomic magnetometer for magnetoencephalography (MEG) that incorporates a passive diffractive optical element (DOE). The DOE allows us to achieve a long, 18-mm gradiometer baseline in a compact footprint on the head. Using gradiometry, the sensitivities of the channels are < 5 fT/Hz1/2, and the 3-dB bandwidths are approximately 90 Hz, which are both sufficient to perform MEG. Additionally, the channels are highly uniform, which offers the possibility of employing standard MEG post-processing techniques. This module will serve as a building block of an array for magnetic source localization.
Here, when an optical coating is damaged, deposited incorrectly, or is otherwise unsuitable, the conventional method to restore the optic often entails repolishing the optic surface, which can incur a large cost and long lead time. We propose three alternative options to repolishing, including (i) burying the unsuitable coating under another optical coating, (ii) using ion milling to etch the unsuitable coating completely from the optic surface and then recoating the optic, and (iii) using ion milling to etch through a number of unsuitable layers, leaving the rest of the coating intact, and then recoating the layers that were etched. Repairs were made on test optics with dielectric mirror coatings according to the above three options. The mirror coatings to be repaired were quarter wave stacks of HfO2 and SiO2 layers for high reflection at 1054 nm at 45 deg incidence in P-polarization. One of the coating layers was purposely deposited incorrectly as Hf metal instead of HfO2 to evaluate the ability of each repair method to restore the coating’s high laser-induced damage threshold (LIDT) of 64.0 J/cm2. The repaired coating with the highest resistance to laser-induced damage was achieved using repair method (ii) with an LIDT of 49.0 to 61.0 J/cm2.
In this study, we have developed a conceptual design of a next-generation pulsed-power accelerator that is optmized for driving megajoule-class dynamic-material-physics experiments at pressures as high as 1 TPa. The design is based on an accelerator architecture that is founded on three concepts: single-stage electrical-pulse compression, impedance matching, and transit-time-isolated drive circuits. Since much of the accelerator is water insulated, we refer to this machine as Neptune. The prime power source of Neptune consists of 600 independent impedance-matched Marx generators. As much as 0.8 MJ and 20 MA can be delivered in a 300-ns pulse to a 16-mΩ physics load; hence Neptune is a megajoule-class 20-MA arbitrary waveform generator. Neptune will allow the international scientific community to conduct dynamic equation-of-state, phase-transition, mechanical-property, and other material-physics experiments with a wide variety of well-defined drive-pressure time histories. Because Neptune can deliver on the order of a megajoule to a load, such experiments can be conducted on centimeter-scale samples at terapascal pressures with time histories as long as 1 μs.
Salt formations hold promise for eternal removal of nuclear waste from our biosphere. Germany and the United States have ample salt formations for this purpose, ranging from flat-bedded formations to geologically mature dome structures. As both nations revisit nuclear waste disposal options, the choice between bedded, domal, or intermediate pillow formations is once again a contemporary issue. For decades, favorable attributes of salt as a disposal medium have been extoled and evaluated, carefully and thoroughly. Yet, a sense of discovery continues as science and engineering interrogate naturally heterogeneous systems. Salt formations are impermeable to fluids. Excavation-induced fractures heal as seal systems are placed or natural closure progresses toward equilibrium. Engineering required for nuclear waste disposal gains from mining and storage industries, as humans have been mining salt for millennia. This great intellectual warehouse has been honed and distilled, but not perfected, for all nuances of nuclear waste disposal. Nonetheless, nations are able and have already produced suitable license applications for radioactive waste disposal in salt. A remaining conundrum is site location. Salt formations provide isolation, and geotechnical barriers reestablish impermeability after waste is placed in the geology. Between excavation and closure, physical, mechanical, thermal, chemical, and hydrological processes ensue. Positive attributes for isolation in salt have many commonalities independent of the geologic setting. In some cases, specific details of the environment will affect the disposal concept and thereby define interaction of features, events and processes, while simultaneously influencing scenario development. Here we identify and discuss high-level differences and similarities of bedded and domal salt formations. Positive geologic and engineering attributes for disposal purposes are more common among salt formations than are significant differences. Developing models, testing material, characterizing processes, and analyzing performance all have overlapping application regardless of the salt formation of interest.
Description Of Event: On June, 28, 2016, the HERMES III accelerator (TA-IV, Building 970) operations team began preparing for the third test shot of the day. Prior to the shot, operations personnel conducted the required pre-shot clearance and lock-up process. Following the shot, an operator and RCT re-entered the controlled area to perform post-shot clearance activities and found the shield door in the open position. All other control measures (interlocks and other access controls) were in place during this event and there was no personnel exposure. The test cell shield door is a six-inch thick steel door; it's principal function is to privide shielding, however, it also serves as a pedestrian entrance into the test cell. The shield door is located on the north side of the test cell and, aside from distance, is a primary control to mitigate personnel exposure to ionizing radiation.
Negatively charged nanoparticles (NPs) in 1:1, 1:2, and 1:3 electrolyte solutions are studied in a primitive ion model using molecular dynamics (MD) simulations and classical density functional theory (DFT). We determine the conditions for attractive interactions between the like-charged NPs. Ion density profiles and NP-NP interaction free energies are compared between the two methods and are found to be in qualitative agreement. The NP interaction free energy is purely repulsive for monovalent counterions, but can be attractive for divalent and trivalent counterions. Using DFT, the NP interaction free energy for different NP diameters and charges is calculated. The depth and location of the minimum in the interaction depend strongly on the NPs' charge. For certain parameters, the depth of the attractive well can reach 8-10 kBT, indicating that kinetic arrest and aggregation of the NPs due to electrostatic interactions is possible. Rich behavior arises from the geometric constraints of counterion packing at the NP surface. Layering of counterions around the NPs is observed and, as secondary counterion layers form the minimum of the NP-NP interaction free energy shifts to larger separation, and the depth of the free energy minimum varies dramatically. We find that attractive interactions occur with and without NP overcharging.
Negatively charged nanoparticles (NPs) in 1:1, 1:2, and 1:3 electrolyte solutions are studied in a primitive ion model using molecular dynamics (MD) simulations and classical density functional theory (DFT). We determine the conditions for attractive interactions between the like-charged NPs. Ion density profiles and NP-NP interaction free energies are compared between the two methods and are found to be in qualitative agreement. The NP interaction free energy is purely repulsive for monovalent counterions, but can be attractive for divalent and trivalent counterions. Using DFT, the NP interaction free energy for different NP diameters and charges is calculated. The depth and location of the minimum in the interaction depend strongly on the NPs' charge. For certain parameters, the depth of the attractive well can reach 8-10 kBT, indicating that kinetic arrest and aggregation of the NPs due to electrostatic interactions is possible. Rich behavior arises from the geometric constraints of counterion packing at the NP surface. Layering of counterions around the NPs is observed and, as secondary counterion layers form the minimum of the NP-NP interaction free energy shifts to larger separation, and the depth of the free energy minimum varies dramatically. We find that attractive interactions occur with and without NP overcharging.
We present a characterization of short-term stability of Kauffman's NK (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness.
In 1986, this author presented a paper at a conference, giving a sampling of computer and network security issues, and the tools of the day to address them. The purpose of this current paper is to revisit the topic of computer and network security, and see what changes, especially in types of attacks, have been brought about in 30 years. This paper starts by presenting a review of the state of computer and network security in 1986, along with how certain facets of it have changed. Next, it talks about today's security environment, and finally discusses some of today's many computer and network attack methods that are new or greatly updated since 1986. Many references for further study are provided. The classes of attacks that are known today are the same as the ones known in 1986, but many new methods of implementing the attacks have been enabled by new technologies and the increased pervasiveness of computers and networks in today's society. The threats and specific types of attacks faced by the computer community 30 years ago have not gone away. New threat methods and attack vectors have opened due to advancing technology, supplementing and enhancing, rather than replacing the long-standing threat methods.
Moving Target Defense (MTD) has received significant focus in technical publications. The publications describe MTD approaches that periodically change some attribute of the computer network system. The attribute that is changed, in most cases, is one that an adversary attempts to gain knowledge of through reconnaissance and may use its knowledge of the attribute to exploit the system. The fundamental mechanism an MTD uses to secure the system is to change the system attributes such that the adversary never gains the knowledge and cannot execute an exploit prior to the attribute changing value. Thus, the MTD keeps the adversary from gaining the knowledge of attributes necessary to exploit the system. Most papers conduct theoretical analysis or basic simulations to assess the effectiveness of the MTD approach. More effective assessment of MTD approaches should include behavioral characteristics for both the defensive actor and the adversary; however, limited research exists on running actual attacks against an implemented system with the objective of determining the security benefits and total cost of deploying the MTD approach. This paper explores empirical assessment through experimentation of MTD approaches. The cyber-kill chain is used to characterize the actions of the adversary and identify what classes of attacks were successfully thwarted by the MTD approach and what classes of attacks could not be thwarted In this research paper, we identify the experiment environments and where experiment fidelity should be focused to evaluate the effectiveness of MTD approaches. Additionally, experimentation environments that support contemporary technologies used in MTD approaches, such as software defined networking (SDN), are also identified and discussed.
The Republic of Estonia faced a series of cyber attacks and riots in 2007 that seemed to be highly coordinated and politically motivated, causing short-lived but substantial impact to Estonia's cyber and economic systems. Short-Term harm from these hybrid incidents led to long-Term improvements and leadership by Estonia in the cyber arena. We created a causal model of these attacks to simulate their dynamics. The model uses the DYMATICA framework, a cognitive-system dynamics structure used to quantify and simulate elicited information from subject matter experts. This historical case study underscores how cyber warfare can be a major threat to modern society, and how it can be combined with information operations and kinetic effects to create further disruption. Given states' potential vulnerability to cyber attacks, a deeper understanding of how to analyze, prevent, defend, and utilize the aftermath of these for improvement to systems is critical, as is insight into the fundamental rationale of the outcomes.
This study examined high-current events observed in Xilinx Field-Programmable Gate Arrays irradiated with heavy ions. A probable cause and proposed changes to the test methodology to prevent these high-current events is described.
In next-generation extreme-scale systems, application performance will be limited by memory performance characteristics. The first exascale system is projected to contain many petabytes of memory. In addition to the sheer volume of the memory required, device trends, such as shrinking feature sizes and reduced supply voltages, have the potential to increase the frequency of memory errors. As a result, resilience to memory errors is a key challenge. In this paper, we evaluate the viability of using memory compression to repair detectable uncorrectable errors (DUEs) in memory. We develop a software library, evaluate its performance and demonstrate that it is able to significantly compress memory of HPC applications. Further, we show that exploiting compressed memory pages to correct memory errors can significantly improve application performance on next-generation systems.
In 1986, this author presented a paper at a conference, giving a sampling of computer and network security issues, and the tools of the day to address them. The purpose of this current paper is to revisit the topic of computer and network security, and see what changes, especially in types of attacks, have been brought about in 30 years. This paper starts by presenting a review of the state of computer and network security in 1986, along with how certain facets of it have changed. Next, it talks about today's security environment, and finally discusses some of today's many computer and network attack methods that are new or greatly updated since 1986. Many references for further study are provided. The classes of attacks that are known today are the same as the ones known in 1986, but many new methods of implementing the attacks have been enabled by new technologies and the increased pervasiveness of computers and networks in today's society. The threats and specific types of attacks faced by the computer community 30 years ago have not gone away. New threat methods and attack vectors have opened due to advancing technology, supplementing and enhancing, rather than replacing the long-standing threat methods.
International Conference for High Performance Computing, Networking, Storage and Analysis, SC
Brown, W.M.; Semin, Andrey; Hebenstreit, Michael; Khvostov, Sergey; Raman, Karthik; Plimpton, Steven J.
Electrical power efficiency is a primary concern in designing modern HPC systems. Common strategies to improve CPU power efficiency rely on increased parallelism within a processor that is enabled both by an increase in the vector capabilities within the core and also the number of cores within a processor. Although many-core processors have been available for some time, achieving power-efficient performance has been challenging due to the offload model. Here, we evaluate performance of the molecular dynamics code LAMMPS on two new Intel® processors including the second generation many-core Intel® Xeon Phi™ processor that is available as a bootable CPU. We describe our approach to measure power consumption out-of-band and software optimizations necessary to achieve energy efficiency. We analyze benefits from Intel® Advanced Vector Extensions 512 instructions and demonstrate increased simulations rates with over 9X the CPU+DRAM power efficiency when compared to the unoptimized code on previous generation processors.
Predicting the long-term integrity of caprock is essential for determining the viability of carbon sequestration. Accurate prediction requires incorporating knowledge about small-scale, subcritical fracture and how they contribute to developing micro and macro-cracks. Tests such as short rod, notched three-point bending (N3PB), cylinder splitting, double torsion, etc. are used to determine the physical characteristics of material. Unlike other materials such as metals, geomaterials have different moduli in tension than compression. This study compares the effects of separate tension and compression moduli on simulations in Abaqus for the N3PB test. Previous models of N3PB created by Rhinehart et al. and Borowski have struggled to create results that accurately portrayed experimental results. Borowski found that previous models with only one value for Young's modulus improved when two moduli were used though it was difficult to determine regions of tension and compression prior to simulation. This study develops an Abaqus subroutine written in Fortran to dynamically reassign material properties as the simulation progresses and produces simulation results capable of much better replication of experimental data. However, the accuracy of the model heavily depends on accurate determination of the Young's modulus in tension.
Park, Junghyun; Stump, Brian W.; Hayward, Chris; Arrowsmith, Stephen J.; Che, Il Y.; Drob, Douglas P.
This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonably variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. This suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.
Simulations of the flow past a rectangular cavity containing a model captive store are performed using a hybrid Reynolds-averaged Navier–Stokes/large-eddy simulation model. Calculated pressure fluctuation spectra are validated using measurements made on the same configuration in a trisonic wind tunnel at Mach numbers of 0.60, 0.80, and 1.47. The simulation results are used to calculate unsteady integrated forces and moments acting on the store. Spectra of the forces and moments, along with correlations calculated for force/moment pairs, reveal that a complex relationship exists between the unsteady integrated forces and the measured resonant cavity modes, as indicated in the cavity wall pressure measurements. The structure of identified cavity resonant tones is examined by visualization of filtered surface pressure fields.
A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). The Bayesian method is also employed to characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.
Journal of the Optical Society of America B: Optical Physics
Ramasesha, Krupa; Borja, Lauren J.; Zurch, M.; Pemmaraju, C.D.; Schultze, Martin; Gandman, Andrey; Prell, James S.; Prendergast, David; Neumark, Daniel M.; Leone, Stephen R.
High-harmonic generation (HHG) produces ultrashort pulses of extreme ultraviolet radiation (XUV), which can be used for pump-probe transient absorption spectroscopy in metal oxides, semiconductors, and dielectrics. Femtosecond transient absorption on iron and cobalt oxides identifies ligand-to-metal charge transfer as the main spectroscopic transition, rather than metal-to-metal charge transfer or d-d transitions, upon photoexcitation in the visible. In silicon, attosecond transient absorption reveals that electrons tunnel into the conduction band from the valence band under strong-field excitation, to energies as high as 6 eV above the conduction band minimum. Extensions of these experiments to other semiconductors, such as germanium, and other transition metal oxides, such as vanadium dioxide, are discussed. Germanium is of particular interest because it should be possible to follow both electron and hole dynamics in a single measurement using transient XUV absorption.
Lane, Todd; Lane, Pamela; Williams, Kelly P.; Wilkenfeld, Joshua S.; Solberg, Owen D.; Fuqua, Zachary B.; Cornelius, Nina G.; Gillespie, Shaunette; Samocha, Tzachi M.; Carney, Laura T.
Productivity of algal mass culture can be severely reduced by contaminating organisms. It is, therefore, important to identify contaminants, determine their effect on productivity and, ultimately, develop countermeasures against such contamination. In the present study we utilized microbiome analysis by second-generation sequencing of small subunit rRNA genes to characterize the predator and pathogen burden of open raceway cultures of Nannochloropsis salina. Samples were analyzed from replicate raceways before and after crashes. In one culture cycle, we identified two algivorous species, the rotifer Brachionus and gastrotrich Chaetonotus, the presence of which may have contributed to the loss of algal biomass. In the second culture cycle, the raceways were treated with hypochlorite in an unsuccessful attempt to interdict the crash. Our analyses were shown to be an effective strategy for the identification of the biological contaminants and the characterization of intervention strategies.
This paper presents a statistical analysis of edge flames in a turbulent lifted flame using direct numerical simulation (DNS). To investigate the dynamics of edge flames, a theoretical framework describing the edge-flame propagation velocity as a function of propagation velocities of mixture-fraction and product-mass fraction iso-surfaces at the flame base is used. The correlations between these propagation velocities and several other variables are then studied, including iso-surface curvatures, iso-surface orientations, strain rates, scalar dissipation rate and gradients of product mass fraction. The contribution of these parameters to the overall behaviour of the edge flame is also investigated using conditional averaging on two-dimensional spatial locations at the flame base. The analysis reveals that the tangential and normal strain rates in addition to the curvatures and scalar dissipation rates have significant contributions to the overall behaviour of the edge flame. The elliptical motion of the flame base described in our earlier study [1] is extended to provide a clearer picture of how these various parameters affect the large fluctuations of edge-flame velocity observed at the flame base.
Peridynamics is a nonlocal extension of classical continuum mechanics that is well-suited for solving problems with discontinuities such as cracks. This paper extends the peridynamic formulation to decompose a problem domain into a number of smaller overlapping subdomains and to enable the use of different time steps in different subdomains. This approach allows regions of interest to be isolated and solved at a small time step for increased accuracy while the rest of the problem domain can be solved at a larger time step for greater computational efficiency. Performance of the proposed method in terms of stability, accuracy, and computational cost is examined and several numerical examples are presented to corroborate the findings.
Currently, superconducting qubits lead the way in potential candidates for quantum computing. At the same time, transferring quantum information over long distances typically relies on the use of photons as the elementary qubit. Converting between stationary electronic qubits in superconducting systems and traveling photonic qubits is a challenging yet necessary goal for the interface of quantum computing and communication. One promising path to achieving this goal appears to be the integration of superconductivity with optically active semiconductors, with quantum information being transferred between the two by means of the superconducting proximity effect. Obtaining good interfaces between superconductors and semiconductors is the next obvious step for improving these hybrid systems. Here, we report on our observation of superconductivity in a 2.3 m diameter self-assembled indium structure grown epitaxially on the surface of a semiconductor material.
Yoon, Hongkyu; Lee, Jonghyun; Kitanidis, Peter K.; Werth, Charles J.; Valocchi, Albert J.
Characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydrogeophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the principal component geostatistical approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multiphysics simulation software with independent parallel executions. In this paper, we extend PCGA to handle a large number of measurements (e.g., 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data were compressed by the zeroth temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Only about 2000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method.
Large-scale open microalgae cultivation has tremendous potential to make a significant contribution to replacing petroleum-based fuels with biofuels. Open algal cultures are unavoidably inhabited with a diversity of microbes that live on, influence, and shape the fate of these ecosystems. However, there is little understanding of the resilience and stability of the microbial communities in engineered semicontinuous algal systems. To evaluate the dynamics and resilience of the microbial communities in microalgae biofuel cultures, we conducted a longitudinal study on open systems to compare the temporal profiles of the microbiota from two multigenerational algal cohorts, which include one seeded with the microbiota from an in-house culture and the other exogenously seeded with a natural-occurring consortia of bacterial species harvested from the Pacific Ocean. From these month-long, semicontinuous open microalga Nannochloropsis salina cultures, we sequenced a time-series of 46 samples, yielding 8804 operational taxonomic units derived from 9,160,076 high-quality partial 16S rRNA sequences. We provide quantitative evidence that clearly illustrates the development of microbial community is associated with microbiota ancestry. In addition, N. salina growth phases were linked with distinct changes in microbial phylotypes. Alteromonadeles dominated the community in the N. salina exponential phase whereas Alphaproteobacteria and Flavobacteriia were more prevalent in the stationary phase. We also demonstrate that the N. salina-associated microbial community in open cultures is diverse, resilient, and dynamic in response to environmental perturbations. This knowledge has general implications for developing and testing design principles of cultivated algal systems.
Cohesive Hamaker constants of solid materials are measured via optical and dielectric properties (i.e., Lifshitz theory), inverse gas chromatography (IGC), and contact angle measurements. To date, however, a comparison across these measurement techniques for common energetic materials has not been reported. This has been due to the inability of the community to produce samples of energetic materials that are readily compatible with contact angle measurements. Here we overcome this limitation by using physical vapor deposition to produce thin films of five common energetic materials, and the contact angle measurement approach is applied to estimate the cohesive Hamaker constants and surface energy components of the materials. The cohesive Hamaker constants range from 85 zJ to 135 zJ across the different films. When these Hamaker constants are compared to prior work using Lifshitz theory and nonpolar probe IGC, the relative magnitudes can be ordered as follows: contact angle > Lifshitz > IGC. Furthermore, the dispersive surface energy components estimated here are in good agreement with those estimated by IGC. Due to these results, researchers and technologists will now have access to a comprehensive database of adhesion constants which describe the behavior of these energetic materials over a range of settings.
A three-dimensional direct numerical simulation (DNS) of a turbulent lifted dimethyl ether (DME) slot jet flame was performed at elevated pressure to study interactions between chemical reactions with low-temperature heat release (LTHR), negative temperature coefficient (NTC) reactions and shear generated turbulence in a jet in a heated coflow. By conditioning on mixture fraction, local reaction zones and local heat release rate, the turbulent flame is revealed to exhibit a "pentabrachial" structure that was observed for a laminar DME lifted flame [Krisman et al., (2015)]. The propagation characteristics of the stabilization and triple points are also investigated. Potential stabilization points, spatial locations characterized by preferred temperature and mixture fraction conditions, exhibit autoignition characteristics with large reaction rate and negligible molecular diffusion. The actual stabilization point which coincides with the most upstream samples from the pool of potential stabilization points fovr each spanwise location shows passive flame structure with large diffusion. The propagation speed along the stoichiometric surface near the triple point is compared with the asymptotic value obtained from theory [Ruetsch et al., (1995)]. At stoichiometric conditions, the asymptotic and averaged DNS values of flame displacement speed deviate by a factor of 1.7. However, accounting for the effect of low-temperature species on the local flame speed increase, these two values become comparable. This suggests that the two-stage ignition influences the triple point propagation speed through enhancement of the laminar flame speed in a configuration where abundant low-temperature products from the first stage, low-temperature ignition are transported to the lifted flame by the high-velocity jet.
The texture or patterning of soil on PV surfaces may influence light capture at various angles of incidence (AOI). Accumulated soil can be considered a microshading element, which changes with respect to AOI. Laboratory deposition of simulated soil was used to prepare test coupons for simultaneous AOI and soiling loss experiments. A mixed solvent deposition technique was used to consistently deposit patterned test soils onto glass slides. Transmission decreased as soil loading and AOI increased. Dense aggregates significantly decreased transmission. However, highly dispersed particles are less prone to secondary scattering, improving overall light collection. In order to test AOI losses on relevant systems, uniform simulated soil coatings were applied to split reference cells to further examine this effect. The measured optical transmission and area coverage correlated closely to the observed ISC. Angular losses were significant at angles as low as 25°.
III-nitride light-emitting diodes (LEDs) and laser diodes (LDs) are ultimately limited in performance due to parasitic Auger recombination. For LEDs, the consequences are poor efficiencies at high current densities; for LDs, the consequences are high thresholds and limited efficiencies. Here, we present arguments for III-nitride quantum dots (QDs) as active regions for both LEDs and LDs, to circumvent Auger recombination and achieve efficiencies at higher current densities that are not possible with quantum wells. QD-based LDs achieve gain and thresholds at lower carrier densities before Auger recombination becomes appreciable. QD-based LEDs achieve higher efficiencies at higher currents because of higher spontaneous emission rates and reduced Auger recombination. The technical challenge is to control the size distribution and volume of the QDs to realize these benefits. If constructed properly, III-nitride light-emitting devices with QD active regions have the potential to outperform quantum well light-emitting devices, and enable an era of ultra-efficient solid-state lighting. (Figure presented.) .
The emergence of Zika virus (ZIKV) infections in Latin America and Southeast Asia has created an urgent need for new, simple, yet sensitive, diagnostic tests. We highlight recent work using paper-based sensors coupled with CRISPR/Cas9 to detect ZIKV RNA as a new approach to achieve rapid development and deployment of field-ready diagnostics for emerging infectious diseases.
This document provides a methodology for the performance-based assessment of security systems designed for the protection of nuclear and radiological materials and the processes that produce and/or involve them. It is intended for use with both relatively simple installations and with highly regulated complex sites with demanding security requirements.
This document serves as the System-Level Acceptance Test (SLAT) Plan for Site Name, City, Country. This test plan is to provide independent testing of the Radiation Detection System (RDS) installed at Site Name to verify that Customs has been delivered a fully-functioning system as required by all contractual commitments. The system includes all installed hardware and software components. The SLAT plan will verify that separate components are working individually and collectively from a system perspective.