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Results for “Heterogeneous computing”

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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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Direct Simulations of Coupled Transport and Reaction on Nano-Scale X-Ray Computed Tomography Images of Platinum Group Metal-Free Catalyst Cathodes

The nano/micro-scale geometry of polymer electrolyte fuel cell (PEFC) catalyst layers critically affects cell performance. The small length scales and complex structure of these composite layers make it challenging to analyze cell performance and physics at the particle scale by experiment. We present a computational method to simulate transport and chemical reaction phenomena at the pore/particle-scale and apply it to a PEFC cathode with platinum group metal free (PGM-free) catalyst. Here, we numerically solve the governing equations for the physics with heterogeneous oxygen diffusion coefficient and proton conductivity evaluated using the actual electrode structure and ionomer distribution obtained using nano-scale resolution X-ray computed tomography (nano-CT). Using this approach, the oxygen concentration and electrolyte potential distributions imposed by the oxygen reduction reaction are solved and the impact of the catalyst layer structure on performance is evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Computational optimization of electric fields for better catalysis design

Although the ubiquitous role that long-ranged electric fields play in catalysis has been recognized, it is seldom used as a primary design parameter in the discovery of new catalytic materials. Here in this paper, we illustrate how electric fields have been used to computationally optimize biocatalytic performance of a synthetic enzyme, and how they could be used as a unifying descriptor for catalytic design across a range of homogeneous and heterogeneous catalysts. Although focusing on electrostatic environmental effects may open new routes toward the rational optimization of efficient catalysts, much more predictive capacity is required of theoretical methods to have a transformative impact in their computational design — and thus experimental relevance — when using electric field alignments in the reactive centres of complex catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2010

Green Rust Reduction of Chromium Part 2: Comparison of Heterogeneous and Homogeneous Chromate Reduction

White and green rusts are the active chemical reagents of buried scrap iron pollutant remediation. In this work, a comparison of the initial electron-transfer step for the reduction of CrO{sub 4}{sup -2} by Fe{sub (aq)}{sup 2+} and Fe(OH){sub 2}(s) is presented. Using hybrid density functional theory and Hartree-Fock cluster calculations for the aqueous reaction, the rate constant for the homogeneous reduction of chromium by ferrous iron was determined to be 5 x 10{sup -2} M{sup -1} s{sup -1} for the initial electron transfer. Using a combination of Hartree-Fock slab and cluster calculations for the heterogeneous reaction, the initial electron transfer for the heterogeneous reduction of chromium by ferrous iron was determined to be 1 x 10{sup 2} s{sup -1}. The difference in rates is driven by the respective free energies of reaction: 33.4 vs -653.2 kJ/mol. This computational result is apparently the opposite of what has been observed experimentally, but further analysis suggests that these results are fully convergent with experiment. The experimental heterogeneous rate is limited by surface passivation from slow intersheet electron transfer, while the aqueous reaction may be an autocatalytic heterogeneous reaction involving the iron oxyhydroxide product. As a result, it is possible to produce a clear model of the pollutant reduction reaction sequence for these two reactants.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Widely tunable, heterogeneously integrated quantum-dot O-band lasers on silicon

Heterogeneously integrated lasers in the O-band are a key component in realizing low-power optical interconnects for data centers and high-performance computing. Quantum-dot-based materials have been particularly appealing for light generation due to their ultralow lasing thresholds, small linewidth enhancement factor, and low sensitivity to reflections. Here, we present widely tunable quantum-dot lasers heterogeneously integrated on silicon-on-insulator substrate. The tuning mechanism is based on Vernier dual-ring geometry, and a 47 nm tuning range with 52 dB side-mode suppression ratio is observed. These parameters show an increase to 52 nm and 58 dB, respectively, when an additional wavelength filter in the form of a Mach–Zehnder interferometer is added to the cavity. The Lorentzian linewidth of the lasers is measured as low as 5.3 kHz.

Malik, Aditya (ORCID:0000000334487577)↗
DOE OSTI2011

Effects of platinum stagnation surface on the lean extinction limits of premixed methane/air flames at moderate surface temperatures

A stagnation flow reactor was used to study the effects of platinum on the lean flammability limits of atmospheric pressure premixed methane/air flames at moderate stagnation surface temperatures. Experimental and computational methods were used to quantify the equivalence ratio at the lean extinction limit ({phi}{sub ext}) and the corresponding stagnation surface temperature (T{sub s}). A range of flow rates (57-90 cm/s) and corresponding strain rates were considered. The results indicate that the gas-phase methane/air flames are sufficiently strong relative to the heterogeneous chemistry for T{sub s} conditions less than 750 K that the platinum does not affect {phi}{sub ext}. The computational results are in good agreement with the experimentally observed trends and further indicate that higher reactant flow rates (>139 cm/s) and levels of dilution (>{proportional_to}10% N{sub 2}) are required to weaken the gas-phase flame sufficiently for surface reaction to play a positive role on extending the lean flammability limits. (author)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Deformation mechanisms, defects, heat treatment, and thermal conductivity in large grain niobium

The physical and mechanical metallurgy underlying fabrication of large grain cavities for superconducting radio frequency accelerators is summarized, based on research of 1) grain orientations in ingots, 2) a metallurgical assessment of processing a large grain single cell cavity and a tube, 3) assessment of slip behavior of single crystal tensile samples extracted from a high purity ingot slice before and after annealing at 800 °C / 2 h, 4) development of crystal plasticity models based upon the single crystal experiments, and 5) assessment of how thermal conductivity is affected by strain, heat treatment, and exposure to hydrogen. Because of the large grains, the plastic anisotropy of deformation is exaggerated, and heterogeneous strains and localized defects are present to a much greater degree than expected in polycrystalline material, making it highly desirable to computationally anticipate potential forming problems before manufacturing cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Anomalous small-angle X-ray scattering of nanoporous two-phase atomistic models for amorphous silicon–germanium alloys

The present work deals with a detailed analysis of the anomalous small-angle X-ray scattering in amorphous silicon–germanium alloy using the simulation technique. We envisage the nanoporous two-phase alloy model consisting in a mixture of Ge-rich and Ge-poor domains and voids at the nanoscale. By substituting Ge atoms for Si atoms in nanoporous amorphous silicon network, compositionally heterogeneous alloys are generated with various composition-contrasts between the two phases. After relaxing the as-generated structure, we compute its radial distribution function, and then we deduce by the Fourier transform technique its anomalous X-ray scattering pattern. Using a smoothing procedure, the computed X-ray scattering patterns are corrected for the termination errors due to the finite size of the model, allowing so a rigorous quantitative analysis of the anomalous small-angle scattering. Our simulation shows that, as expected, the anomalous small-angle X-ray scattering technique is a tool of choice for characterizing compositional heterogeneities coexisting with structural inhomogeneities in an amorphous alloy. Furthermore, the sizes of the compositional nanoheterogeneities, as measured by anomalous small-angle X-ray scattering technique, are X-ray energy independent. A quantitative analysis of the separated reduced anomalous small-angle X-ray scattering, as defined in this work, provided a good estimate of their size.

36 MATERIALS SCIENCE↗
DOE OSTI2013

A pseudo-spectral method for the simulation of poro-elastic seismic wave propagation in 2D polar coordinates using domain decomposition

We present a novel numerical approach for the comprehensive, flexible, and accurate simulation of poro-elastic wave propagation in 2D polar coordinates. An important application of this method and its extensions will be the modeling of complex seismic wave phenomena in fluid-filled boreholes, which represents a major, and as of yet largely unresolved, computational problem in exploration geophysics. In view of this, we consider a numerical mesh, which can be arbitrarily heterogeneous, consisting of two or more concentric rings representing the fluid in the center and the surrounding porous medium. The spatial discretization is based on a Chebyshev expansion in the radial direction and a Fourier expansion in the azimuthal direction and a Runge–Kutta integration scheme for the time evolution. A domain decomposition method is used to match the fluid–solid boundary conditions based on the method of characteristics. This multi-domain approach allows for significant reductions of the number of grid points in the azimuthal direction for the inner grid domain and thus for corresponding increases of the time step and enhancements of computational efficiency. The viability and accuracy of the proposed method has been rigorously tested and verified through comparisons with analytical solutions as well as with the results obtained with a corresponding, previously published, and independently benchmarked solution for 2D Cartesian coordinates. Finally, the proposed numerical solution also satisfies the reciprocity theorem, which indicates that the inherent singularity associated with the origin of the polar coordinate system is adequately handled.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2017

Multiscale Characterization of Structural Compositional and Textural Heterogeneity of Nano-porous Geomaterials

The purpose of the project was to perform multiscale characterization of low permeability rocks to determine the effect of physical and chemical heterogeneity on the poromechanical and flow responses of shales and carbonate rocks with a broad range of physical and chemical heterogeneity . An integrated multiscale imaging of shale and carbonate rocks from nanometer to centimeter scales include s dual focused ion beam - scanning electron microscopy (FIB - SEM) , micro computed tomography (micro - CT) , optical and confocal microscopy, and 2D and 3D energy dispersive spectroscopy (EDS). In addition, mineralogical mapping and backscattered imaging with nanoindentation testing advanced the quantitative evaluat ion of the relationship between material heterogeneity and mechanical behavior. T he spatial distribution of compositional heterogeneity, anisotropic bedding patterns, and mechanical anisotropy were employed as inputs for brittle fracture simulations using a phase field model . Comparison of experimental and numerical simulations reveal ed that proper incorporation of additional material information, such as bedding layer thickness and other geometrical attributes of the microstructures, can yield improvements on the numerical prediction of the mesoscale fracture patterns and hence the macroscopic effective toughness. Overall, a comprehensive framework to evaluate the relationship between mechanical response and micro-lithofacial features can allow us to make more accurate prediction of reservoir performance by developing a multi - scale understanding of poromechanical response to coupled chemical and mechanical interactions for subsurface energy related activities.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures

Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Efficient reconstruction and validation of heterogeneous microstructures for energy applications

The digital reconstruction of microstructures is necessary for simulations in fields ranging from geology to electrochemistry, but the state-of-the-art digital reconstruction techniques often compromise between resolution and field of view. It is challenging to retain detailed microstructure information in large-scale reconstructions. Here, this study investigates different aspects of the Yeong-Torquato algorithm based on correlation functions to make it more efficient. We achieve this goal by reducing the computational complexity of the chord-length distribution function and the two-point correlation function, applying the random sphere-packing method as the initial condition, and restricting potential voxel swaps to interfaces. In addition, a novel superposition parallel scheme is introduced to aid in searching for potential voxel swaps. The algorithm proposed is validated by comparing the pore-size distributions of reconstructed 3D custom battery electrodes from a sample dataset obtained from transmission X-ray microscopy. From a sample image with 200 x 200 pixels, the code can reconstruct a 300 x 300 x 300 structure in under 22 h and reconstruct a 400 x 400 x 400 structure in 43 h with eight cores.

42 ENGINEERING↗
DOE OSTI2014

Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures. Final Report

With the coming end of Moore's law, it has become essential to develop new algorithms and techniques that can provide the performance needed by demanding computational science applications, especially those that are part of the DOE science mission. This work was part of a multi-institution, multi-investigator project that explored several approaches to develop algorithms that would be effective at the extreme scales and with the complex processor architectures that are expected at the end of this decade. The work by this group developed new performance models that have already helped guide the development of highly scalable versions of an algebraic multigrid solver, new programming approaches designed to support numerical algorithms on heterogeneous architectures, and a new, more scalable version of conjugate gradient, an important algorithm in the solution of very large linear systems of equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Development of activity–descriptor relationships for supported metal ion hydrogenation catalysts on silica

With the increasing attention on single-site heterogeneous catalysts on account of their high specific activity, more effective catalyst design strategies are necessary. We demonstrate a first-principles-calculation-guided active-site design strategy for alkene hydrogenation using silica-supported single-atom single-site heterogeneous catalysts (SSHCs, i.e., M/SiO2). An activity-descriptor relationship for propylene hydrogenation was established using representative catalysts (i.e., Ga3+, Zn2+, Mn2+ and Ti4+/SiO2), correlating the computational activity descriptor (i.e., the reaction free energy of the metal hydride formation) with the experimental reaction rates. Microkinetic modeling confirmed the predicted reaction mechanisms and further explained the rationale of the activity-descriptor relationship. This relationship was then used to predict the trend of activities of a variety of isolated ions on silica, and an In3+/SiO2 catalyst was identified as the most promising candidate based on its predicted activity and synthetic feasibility. The monodispersed In3+/SiO2 catalyst was then synthesized, for the first time, and showed higher propylene hydrogenation activity than the other four single-atom SSHCs, as predicted. Detailed spectroscopic characterization (XAS, XPS, DRIFTS and DRUV-Vis) provided insights into coordination environments and oxidation states of the catalysts, as well as evidence for the hydride intermediate. The successful discovery of the In3+/SiO2 catalyst for propylene hydrogenation using the first-principles-calculations-guided design strategy opens up new opportunities for efficient development of single-atom SSHCs.

DFT↗