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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Selective Host-Guest Interaction between Metal Ions and Metal-Organic Frameworks Using Dynamic Nuclear Polarization Enhanced Solid-State NMR Spectroscopy
The host–guest interaction between metal ions (Pt²⁺ and Cu²⁺) and a zirconium metal–organic framework (UiO-66-NH₂) was explored using dynamic nuclear polarization-enhanced ¹⁵N{¹H} CPMAS NMR spectroscopy supported by X-ray absorption spectroscopy and density functional calculations. The combined experimental results conclude that each Pt²⁺ coordinates with two NH₂ groups from the MOF and two Cl⁻ from the metal precursor, whereas Cu²⁺ do not form chemical bonds with the NH₂ groups of the MOF framework. Density functional calculations reveal that Pt²⁺ prefers a square-planar structure with the four ligands and resides in the octahedral cage of the MOF in either cis or trans configurations.
Application-level regression testing framework using Jenkins
Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integrate with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.
Spectroelectrochemical Sensor for Spectroscopically Hard-to-detect Metals by in situ Formation of a Luminescent Complex Using Ru(II) as a Model Compound
Fast, robust, and cost-effective means of detecting spectroscopically inactive metal species are necessary for field detection and applications within a variety of areas including industry and the nuclear safeguards fields. A sensor based on spectroelectrochemistry is an excellent candidate to meet these needs as it provides improved selectivity for specifically quantifying metal ions by simultaneously monitoring at least two physio-chemical properties. Ruthenium was chosen as a model system for this study due to its spectroscopic and electrochemical characteristics as well as its relevance within the fuel cycle and industrial fields. Aqueous Ru displays multiple redox couples in which all available oxidation states have poor sensitivity for detection by visible absorption spectroscopy because of the low molar absorptivities. Ru can, however, form complexes with sensitizing ligands such as 2,2'-bipyridine, where the resulting [Ru(ligand)3]2+ complex displays a red luminescence with a high quantum yield of emission. This significantly improves detection limits for Ru and allows for the spectroelectrochemical detection of the otherwise hard-to-detect metal ion. This work explores the in-situ generation of Ru(bpy)3 complexes in simulated field samples and their subsequent spectroelectrochemical sensing using our sensor methodology.
A localized artificial diffusivity method to simulate compressible multiphase flows using the stiffened gas equation of state: A localized artificial diffusivity method to simulate compressible multiphase flows using the stiffened gas equation of state
The development of numerical approaches to perform direct numerical simulations of compressible multiphase flows has been an active field of research for several years. Proper treatment of fluid interfaces is crucial as important physics occur in this infinitesimally small region. Furthermore, the compressibility of the fluid requires proper treatment of discontinuities. Artificial diffusivity is among a number of methods widely used for compressible flows. This study develops a general form of consistent artificial diffusion fluxes and extends the localized artificial diffusivity method for high-order central schemes to solve multiphase flows with an interface-capturing method. These fluxes ensure an oscillation-free interface for pressure, velocity, and temperature without employing a sharpening technique. Moreover, the high-order representation of all scales in the flow helps capture the wide range of instabilities inherent in these flows. The goal is to develop an approach capable of performing high-fidelity simulations supported by physics-driven validation. lastly, this is achieved by solving the five-equation model with the stiffened-gas equation of state using the proposed method for multicomponent and multiphase flows on a variety of 1D and 2D problems.
Monitoring deformation at the Geysers Geothermal Field, California using C-band and X-band interferometric synthetic aperture radar
In this study, we resolve deformation at The Geysers Geothermal Field using two distinct sets of interferometric synthetic aperture radar (InSAR) data. The first set of observations utilize archived European Space Agency C-band synthetic aperture radar data from 1992 through 1999 to image the long-term and large-scale subsidence at The Geysers. The peak range velocity of approximately 50 mm/year agrees with previous estimates from leveling and global positioning system observations. Data from a second set of measurements, acquired by TerraSAR-X satellites, extend from May 2011 until April 2012 and overlap the C-band data spatially but not temporally. These X-band data, analyzed using a combined permanent and distributed scatterer algorithm, provide a higher density of scatterers (1122 per square kilometer) than do the C-band data (12 per square kilometer). The TerraSAR-X observations resolve 1 to 2 cm of deformation due to water injection into a Northwest Geysers enhanced geothermal system well, initiated on October 2011. Lastly, the temporal variation of the deformation is compatible with estimates from coupled numerical modeling.
Oxidative Hydrophenylation of Ethylene Using a Cationic Ru(II) Catalyst: Styrene Production with Ethylene as the Oxidant
The complex [(MeOTTM)Ru(P(OCH 2 ) 3 CEt)(NCMe)Ph][BAr' 4 ] (MeOTMM = 4,4',4"-(methoxymethanetriyl)-tris(1-benzyl-1H-1,2,3-triazole), BAr' 4 = tetrakis[3,5-bis(trifluoromethyl)phenyl]borate) is used to catalyze the hydrophenylation of ethylene to produce styrene and ethylbenzene. The selectivity of styrene versus ethylbenzene varies as a function of ethylene pressure, and replacing the MeOTTM ligand with tris(1-phenyl-1H-1,2,3-triazol-4-yl)methanol reduces the selectivity toward styrene. For styrene production ethylene serves as the oxidant to produce ethane, as determined by both 1 H NMR spectroscopy and GC-MS. The Ru(III/II) potentials of [(MeOTTM)Ru[P(OCH 2 ) 3 CEt](NCMe)Ph][BAr' 4 ] (0.86 V) and [(HC(pz 5 ) 3 )Ru[P(OCH 2 ) 3 CEt](NCMe)Ph][BAr' 4 ] (0.82 V) (HC(pz 5 ) 3 = tris(5-methyl-pyrazolyl)methane) are nearly identical. Since catalytic conversion of ethylene and benzene by [(HC(pz 5 ) 3 )Ru[P(OCH 2 ) 3 CEt](NCMe)Ph][BAr' 4] is known to selectively produce ethylbenzene, the formation of styrene using [(MeOTTM)Ru[P(OCH 2 ) 3 CEt](NCMe)Ph][BAr' 4 ] is attributed to the substituents on the triazole rings of the MeOTTM ligand.
Technical Note: Iterative megavoltage CT (MVCT) reconstruction using block-matching 3D-transform (BM3D) regularization
Not provided.
Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes
This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on an embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.
A Literal Elytral Rainbow: Tunable Structural Colors Using Single Diamond Biophotonic Crystals in Pachyrrhynchus congestus Weevils
Abstract not provided
Efficient Cytosolic Delivery Using Crystalline Nanoflowers Assembled from Fluorinated Peptoids
The design and synthesis of biocompatible nanomaterials as cargoes for the intracellular delivery of therapeutic proteins or genes have attracted intense attention because of their promise for use in therapeutics. Despite the advances in this area, very few nanomaterials can be efficiently delivered to the cytosol. To address these challenges, we designed and synthesized crystalline nanoflower-like particles from fluorinated sequence-defined peptoids; the crystallinity and fluorination of these particles enabled highly efficient cytosolic delivery with minimal cytotoxicity. We delivered these particles, 80% appear to diffuse in the cytosol. Furthermore, these nanocrystals can carry mRNA for instance and effectively delivered into cytosol for gene transfection, demonstrating the generality of our nanocrystals. Our results indicate that self-assembly of crystalline nanomaterials from fluorinated peptoids paves a new way toward development of nanocargoes with efficient cytosol gene delivery. Y. Song and M. Wang contributed equally to this work. This work was supported by start-up funds from Washington State University. Peptoid synthesis work was supported by the Materials Synthesis and Simulation Across Scales (MS3) Initiative through the LDRD fund at Pacific Northwest National Laboratory (PNNL). Assembly of peptoid particles and their structural characterizations were supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Biomolecular Materials Program at PNNL. XRD work was conducted at the Advanced Light Source with support from the Molecular Foundry, at Lawrence Berkeley National Laboratory, both of which are supported by the Office of Science, under Contrast No. DE-AC02-05CH11231. PNNL is multi-program national laboratory operated for Department of Energy by Battelle under Contract No. DE-AC05-76RL01830.
Integrated Design of Downwind Land-Based Wind Turbines using Analytic Gradients
Wind turbines are complex systems where component-level changes can have significant system-level effects. Effective wind turbine optimization generally requires an integrated analysis approach with a large number of design variables. Optimizing across large variable sets is orders of magnitude more efficient with gradient-based methods as compared with gradient-free method, particularly when using exact gradients. We have developed a wind turbine analysis set of over 100 components where 90% of the models provide numerically exact gradients through symbolic differentiation, automatic differentiation, and adjoint methods. This framework is applied to a specific design study focused on downwind land-based wind turbines. Downwind machines are of potential interest for large wind turbines where the blades are often constrained by the stiffness required to prevent a tower strike. The mass of these rotor blades may be reduced by utilizing a downwind configuration where the constraints on tower strike are less restrictive. The large turbines of this study range in power rating from 5-7MW and in diameter from 105m to 175m. The changes in blade mass and power production have important effects on the rest of the system, and thus the nacelle and tower systems are also optimized. For high-speed wind sites, downwind configurations do not appear advantageous. The decrease in blade mass (10%) is offset by increases in tower mass caused by the bending moment from the rotor-nacelle-assembly. For low-wind speed sites, the decrease in blade mass is more significant (25-30%) and shows potential for modest decreases in overall cost of energy (around 1-2%).
Efficient Breadth First Search on Multi-GPU Systems Using GPU-Centric OpenSHMEM
NVSHMEM is an implementation of OpenSHMEM for NVIDIA GPUs which allows communication to be issued from inside CUDA kernels. In this work, we present an implementation of Breadth First Search for multi-GPU systems using NVSHMEM. We analyze the benefits and bottlenecks of moving fine-grained communication into CUDA kernels. Using our implementation of BFS, we achieve up to 75% improvement in performance compared to a CUDA-aware MPI-based implementation, in the best case.
Measurement of the top quark pair production charge asymmetry in proton-proton collisions at $ \sqrt{s} $ = 7 TeV using the ATLAS detector
This paper presents a measurement of the top quark pair ($ t\bar{t} $) production charge asymmetry AC using 4.7 fb -1 of proton-proton collisions at a centre-of-mass energy $ \sqrt{s} $ = 7 TeV collected by the ATLAS detector at the LHC. A $ t\bar{t} $-enriched sample of events with a single lepton (electron or muon), missing transverse momentum and at least four high transverse momentum jets, of which at least one is tagged as coming from a b-quark, is selected. A likelihood fit is used to reconstruct the $ t\bar{t} $ event kinematics. A Bayesian unfolding procedure is employed to estimate AC at the parton-level. The measured value of the $ t\bar{t} $ production charge asymmetry is AC = 0.006 ± 0.010, where the uncertainty includes both the statistical and the systematic components. Differential AC measurements as a function of the invariant mass, the rapidity and the transverse momentum of the $ t\bar{t} $ system are also presented. In addition, AC is measured for a subset of events with large $ t\bar{t} $ velocity, where physics beyond the Standard Model could contribute. All measurements are consistent with the Standard Model predictions.
Search for anomalous production of prompt same-sign lepton pairs and pair-produced doubly charged Higgs bosons with $ \sqrt{s}=8 $ TeV pp collisions using the ATLAS detector
A low-background inclusive search for new physics in events with same-sign dileptons is presented. The search uses proton-proton collisions corresponding to 20.3 fb -1 of integrated luminosity taken in 2012 at a centre-of-mass energy of 8 TeV with the ATLAS detector at the LHC. Pairs of isolated leptons with the same electric charge and large transverse momenta of the type e ± e ± , e ± μ ± , and μ ± μ ± are selected and their invariant mass distribution is examined. No excess of events above the expected level of Standard Model background is found. The results are used to set upper limits on the cross-sections for processes beyond the Standard Model. Limits are placed as a function of the dilepton invariant mass within a fiducial region corresponding to the signal event selection criteria. Exclusion limits are also derived for a specific model of doubly charged Higgs boson production.[Figure not available: see fulltext.]
Search for new resonances in mass distributions of jet pairs using 139 fb(-1) of pp collisions at root s=13TeV with the ATLAS detector
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