Decomposition of diverse solid inorganic matrices with molten ammonium bifluoride salt for constituent elemental analysis
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O'Hara, Matthew J. (ORCID:0000000339825897)↗
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Results for “DECOMPOSITION”
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Efficient tree decomposition of high-rank tensors [Efficient decomposition of high-rank tensors]
Tensors are a natural way to express correlations among many physical variables, but storing tensors in a computer naively requires memory which scales exponentially in the rank of the tensor. This is not optimal, as the required memory is actually set not by the rank but by the mutual information amongst the variables in question. Representations such as the tensor tree perform near-optimally when the tree decomposition is chosen to reflect the correlation structure in question, but making such a choice is non-trivial and good heuristics remain highly context-specific. In this work I present two new algorithms for choosing efficient tree decompositions, independent of the physical context of the tensor. The first is a brute-force algorithm which in most cases produces optimal decompositions but is generally impractical for high-rank tensors, as the number of possible choices grows exponentially in rank. Here, the second is a greedy algorithm, and while it is not optimal it performs extremely well in numerical experiments while having runtime which makes it practical even for tensors of very high rank.
97 MATHEMATICS AND COMPUTING↗
Decompositions in Complete Lattices III. Unique Irredundant Decompositions and Convex Geometries
We give a characterization of complete strongly dually atomic lattices having unique irredundant decompositions which are also canonical. It is shown that all known characterizations of lattices with unique irredundant decompositions are a consequence of this result. In addition, upper continuous closure lattices of convex geometries with (unique) irredundant decompositions are characterized.
97 MATHEMATICS AND COMPUTING↗
Geochemical drivers of organic matter decomposition in Arctic tundra soils
Climate change is warming tundra ecosystems in the Arctic, resulting in the decomposition of previously-frozen soil organic matter (SOM) and release of carbon (C) to the atmosphere; however, the processes that control SOM decomposition and C emissions remain highly uncertain. In this study, we evaluate geochemical factors that influence anaerobic production of carbon dioxide (CO 2 ) and methane (CH 4 ) in the active layers of four ice-wedge polygons. Surface and soil pore waters were collected during the annual thaw season over a two-year period in an area containing waterlogged, low-centered polygons and well-drained, high-centered polygons. We report spatial and seasonal patterns of dissolved gases in relation to the geochemical properties of Fe and organic C as determined using spectroscopic and chromatographic techniques. Iron was present as Fe(II) in soil solution near the permafrost boundary but enriched as Fe(III) in the middle of the active layer, similar to dissolved aromatic-C and organic acids. Dissolved CH 4 increased relative to dissolved CO 2 with depth and varied with soil moisture in the middle of the active layer in patterns that were positively correlated with the proportion of dissolved Fe(III) in transitional and low-centered polygon soils but negatively correlated in the drier flat- and high-centered polygons. These results suggest that microbial-mediated Fe oxidation and reduction influence respiration/fermentation of SOM and production of substrates (e.g., low-molecular-weight organic acids) for methanogenesis. As a result, we infer that geochemical differences induced by water saturation dictate microbial products of SOM decomposition, and Fe geochemistry is an important factor regulating methanogenesis in anoxic tundra soils.
58 GEOSCIENCES↗
Studies of the decomposition of the ethylene hydrophenylation catalyst TpRu(CO)(NCMe)Ph
Not provided.
Chemistry↗
Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis
We consider the frequency domain form of proper orthogonal decomposition (POD), called spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space–time POD problem for statistically stationary flows and leads to modes that each oscillate at a single frequency. This form of POD goes back to the original work of Lumley ( Stochastic Tools in Turbulence , Academic Press, 1970), but has been overshadowed by a space-only form of POD since the 1990s. We clarify the relationship between these two forms of POD and show that SPOD modes represent structures that evolve coherently in space and time, while space-only POD modes in general do not. We also establish a relationship between SPOD and dynamic mode decomposition (DMD); we show that SPOD modes are in fact optimally averaged DMD modes obtained from an ensemble DMD problem for stationary flows. Accordingly, SPOD modes represent structures that are dynamic in the same sense as DMD modes but also optimally account for the statistical variability of turbulent flows. Finally, we establish a connection between SPOD and resolvent analysis. The key observation is that the resolvent-mode expansion coefficients must be regarded as statistical quantities to ensure convergent approximations of the flow statistics. When the expansion coefficients are uncorrelated, we show that SPOD and resolvent modes are identical. Our theoretical results and the overall utility of SPOD are demonstrated using two example problems: the complex Ginzburg–Landau equation and a turbulent jet.
Mechanics↗
Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing
Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.
Zhang, Jiang↗
Data decomposition of Monte Carlo particle transport simulations via tally servers
An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients
We present a novel approach for solving steady-state stochastic partial differential equations in high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support our construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Our results show that accurate global solutions can be obtained with significantly reduced computational costs.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Data-driven acceleration of thermal radiation transfer calculations with the dynamic mode decomposition and a sequential singular value decomposition
In this work, we present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem, a factor of several thousand on a cooling problem where the effective scattering ratio approaches unity, and a factor of 20 improvement in a realistic, multimaterial radiating shock problem.
97 MATHEMATICS AND COMPUTING↗
Three phase crystallography and solute distribution analysis during residual austenite decomposition in tempered nanocrystalline bainitic steels
Interphase carbide precipitation due to austenite decomposition was investigated by high resolution transmission electron microscopy and atom probe tomography in tempered nanostructured bainitic steels. Results showed that cementite (θ) forms by a paraequilibrium transformation mechanism at the bainitic ferrite–austenite interface with a simultaneous three phase crystallographic orientation relationship. - Highlights: • Interphase carbide precipitation due to austenite decomposition • Tempered nanostructured bainitic steels • High resolution transmission electron microscopy and atom probe tomography • Paraequilibrium θ with three phase crystallographic orientation relationship.
36 MATERIALS SCIENCE↗
An Adaptive Reduced Basis Collocation Method Based on PCM ANOVA Decomposition for Anisotropic Stochastic PDEs
The combination of reduced basis and collocation methods enables efficient and accurate evaluation of the solutions to parameterized PDEs. Here, we study the stochastic collocation methods that can be combined with reduced basis methods to solve high-dimensional parameterized stochastic PDEs. We also propose an adaptive algorithm using a probabilistic collocation method (PCM) and ANOVA decomposition. This procedure involves two stages. First, the method employs an ANOVA decomposition to identify the effective dimensions, i.e., subspaces of the parameter space in which the contributions to the solution are larger, and sort the reduced basis solution in a descending order of error.Then, the adaptive search refines the parametric space by increasing the order of polynomials until the algorithm is terminated by a saturation constraint. We demonstrate the effectiveness of the proposed algorithm for solving a stationary stochastic convection-diffusion equation, a benchmark problem chosen because solutions contain steep boundary layers and anisotropic features. Lastly, we show that two stages of adaptivity are critical in a benchmark problem with anisotropic stochasticity.
97 MATHEMATICS AND COMPUTING↗
TATB Thermal Decomposition: An Improved Kinetic Model for Explosive Safety Analysis
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Materials science, Chemistry - Chemical explosives↗
Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition
Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.
Hanson, Joshua↗
Probing properties of the interfacial perimeter sites in TiO x /Au/SiO 2 with 2-propanol decomposition
The decomposition of 2-propanol was studied over SiO2, SiO2 with an overlayer of TiO2 (Ti/SiO2), Au/SiO2, and Au/SiO2 with an overlayer of TiO2 (Ti/[Au/SiO2]) at 170–190 °C. There was no reaction on SiO2. Propene was the only product on Ti/SiO2, and its rate of formation increased proportionally with the Ti content. Acetone was the major product (selectivity 65–99%) on all Au-containing catalysts. Its rate of formation also increased with Ti loading. In addition, small amounts of propene were also formed on Ti/[Au/SiO2] the rate of which increased with Ti loading. Characterization of the catalysts with N2 adsorption, STEM, DR-UV-vis spectroscopy, XPS, XANES and EXAFS suggested that the Ti formed an amorphous TiO2 overlayer on the catalyst. At high Ti loadings (4–5 wt.%), there were patches of thick porous TiO2 layer, and some microdomains of crystalline TiO2 could be detected. Au was present as 1–3 nm nanoparticles on all catalysts, before and after used in reaction. Only Lewis acid sites were detected based on results from pyridine adsorption, and their quantities increased with Ti loading. Based on the comparison of reaction rates, the dependence of the kinetics on 2-propanol partial pressure, the apparent activation energies, and the effect of co-feeding O2 among different catalysts, it was concluded that propene was formed on the TiO2 overlayer, acetone was formed primarily at the Au-TiO2 interfacial perimeter sites, and α-C-H bond breaking preceding acetone formation was more facile on Au at the interfacial site than other surface Au atoms. Implication of these results to the selective acetone formation in the oxidation of propane in the presence of a O2/H2 mixture was discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Thermodynamic studies of studtite thermal decomposition pathways via amorphous intermediates UO 3 , U 2 O 7 , and UO 4
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nuclear (including radiation effects), materials a↗
Catalytic decomposition of methane into hydrogen and high-value carbons: combined experimental and DFT computational study
Thermocatalytic decomposition (TCD) of methane can produce hydrogen and valuable nanocarbon co-products with low to near-zero CO2 emission. In this study, a series of Pd promoted Ni catalysts, prepared with various Ni/Pd ratios on a CNT support, were evaluated for methane TCD performance. Characterization and calculations using density functional theory (DFT) were carried out to elucidate the activity–structure relationship and growth mechanism of carbon nanomaterials. It was found that the methane conversion and stability of the catalysts were highly dependent on the Ni/Pd ratio and reaction temperature. DFT calculations revealed that the diffusion of carbon in the metal sublayer required for CNT growth was more favorable in the Ni–Pd alloy lattice suggesting that the buildup of carbon in the metal alloy sublayer facilitated the formation of CNTs and CNFs. A cyclic reaction–regeneration process for self-sustained TCD was experimentally demonstrated. In each cycle, a portion of the separated CNT product was used to re-synthesize the Ni–Pd/CNT catalyst for use in the next reaction cycle. After five cycles of operation, the CH4 conversion, morphology and crystallinity of the carbon product remained unchanged.
Wang, I-Wen↗