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At least 973 records · Page 54

Analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures

Vector Particle-In-Cell (VPIC) is one of the fastest plasma simulation codes in the world, with particle numbers ranging from one trillion on the first petascale system, Roadrunner, to ten trillion particles on the more recent Blue Waters supercomputer. As supercomputers continue to grow rapidly in size, so too does the gap between computing capability and memory capability. Current memory systems limit VPIC simulations greatly as the maximum number of particles that can be simulated directly depends on the available memory. In this study, we present a suite of VPIC memory optimizations (i.e., particle weight, half-precision, and fixed-point optimizations) that enable a significant increase in the number of particles in VPIC simulations. Here, we assess the optimizations’ impact on memory and runtime performance for a suite of cutting-edge computer architectures such has the NVIDIA V100 GPU, the IBM Power9, and the Fujitsu A64FX architectures. Our optimizations enable a 31.25% reduction in memory usage and up to 40% increase in the number of particles. This paper extends our work on developing particle storage format optimizations Tan et al.

97 MATHEMATICS AND COMPUTING↗

Ethanol-fueled metal supported solid oxide fuel cells with a high entropy alloy internal reforming catalyst

High-performance metal supported solid oxide fuel cells (MS-SOFC) with an integrated high entropy alloy (HEA) internal reforming catalyst (IRC) are demonstrated for transportation applications using ethanol and methanol as fuels. Addition of the HEA IRC dramatically improves cell performance and stability when using ethanol/water blend fuel. Absence of carbon deposition predicted by thermodynamic calculations is confirmed by Raman spectroscopy analysis of posttest anodes. Optimal catalyst processing (deposition technique, loading, firing temperature) and cell operation conditions (flow rates, temperature, fuel compositions) are explored. Infiltrated HEA reforming catalyst provides a highly porous structure and low catalyst loading (6 mg cm –2 ). The designed structure and catalysts achieve small mass transport resistances in the fuel electrode (26.2 s m –1 ) and oxygen electrode (41.6 s m –1 ). The best ethanol concentration (60:40 v% ethanol: water) provides 0.83 W cm –1 at 700 °C, without carbon deposition. The ethanol-fueled MS-SOFC is operated for 500 h, including five thermal cycles. As a result, cell evolution is similar to that reported previously for hydrogen fuel; nickel aggregation and chromia deposition were the major observed changes, and carbon formation can be avoided even after long-term operation.

30 DIRECT ENERGY CONVERSION↗

A new method for the preparation of a Fe{sub 3}O{sub 4}/graphene hybrid material and its applications in electromagnetic wave absorption

Graphical abstract: A microwave-assisted solvothermal process was used to prepare Fe{sub 3}O{sub 4} nanoparticles/graphene hybrids, which could be applied as an electromagnetic (EM) radiation absorbent. The absorber, composed of 20 wt% Fe{sub 3}O{sub 4}/graphene–epoxy, exhibited a dual-frequency reflection characteristic covering the C and Ku bands with maximum reflection losses of less than −20 dB at thicknesses of 4 and 5 mm. - Highlights: • Fe{sub 3}O{sub 4}/graphene composites were prepared by a microwave-assisted solvothermal route. • Uniform loading of Fe{sub 3}O{sub 4} nanoparticles on graphene was obtained. • The products as-synthesized show great promise as a microwave absorption material. • Synergistic effects of Fe{sub 3}O{sub 4} and graphene caused improved absorption efficiency. • The Fe{sub 3}O{sub 4}/graphene product possessed a dual-frequency reflection characteristic. - Abstract: A rapid, simple, and inexpensive process combining a microwave-assisted technique and a solvothermal method has been developed using graphene sheets and FeCl{sub 3}·6H{sub 2}O as the reactant to prepare graphene/Fe{sub 3}O{sub 4} nanoparticle hybrids, which can be applied as an electromagnetic radiation absorbent. The experimental factors (i.e., composition ratio, microwave power, and irradiation time) on the products’ characteristics were examined. Under optimal conditions, the morphological analysis revealed that the graphene sheet was homogeneously covered with Fe{sub 3}O{sub 4} nanoparticles (∼50 nm). The electromagnetic parameters of the composites made from 20 wt% Fe{sub 3}O{sub 4}/graphene–epoxy were measured by a vector network analyzer. It was found that the 4- and 5 mm-thick composites could attain a reflection loss below −20 dB in the dual-ranges of 4–8 and 12–18 GHz.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Microstructure and mechanical properties of high Mn-containing ferritic-martensitic alloys exposed to cyclical thermal treatment

Substantial residual tensile stress tends to accumulate in currently available high-Cr ferritic martensitic steels that are subjected to cyclical heat treatment, which leads to premature brittle fracture. By tailoring the alloy composition, this thermal cycling can be exploited to induce a high number density of nanoprecipitates and phase transformations countering residual tensile stresses. In this work, three new variants of ferritic-martensitic steels have been designed with computational thermodynamics to meet the goals of mitigating residual tensile stresses by lowering martensite start temperatures and of enhancing mechanical strength and irradiation sink strength by increasing the number density of nanoprecipitates. Furthermore, ctenast materials were subjected to cyclical heat treatment. The thermally cycled samples were evaluated with mechanical testing and microstructural analysis to identify the optimal composition in which figures of merit include low residual stress and a high density of nanoscale MX (M = metal, X = C/N) precipitates, leading to high yield strength with reasonable ductility. The noticeably higher density of nanoprecipitates in the optimal alloy favor its higher yield strength, which is supported by the microstructure-derived yield strength calculation and precipitation kinetics simulation.

36 MATERIALS SCIENCE↗

Enhancing Neutron Beam Production with a Convoluted Moderator

We describe a new concept for a neutron moderating assembly resulting in the more efficient production of slow neutron beams. The Convoluted Moderator, a heterogeneous stack of interleaved moderating material and nearly transparent single-crystal spacers, is a directionally-enhanced neutron beam source, improving beam effectiveness over an angular range comparable to the range accepted by neutron beam lines and guides. We have demonstrated gains of 50% in slow neutron intensity for a given fast neutron production rate while simultaneously reducing the wavelength-dependent emission time dispersion by 25%, both coming from a geometric effect in which the neutron beam lines view a large surface area of moderating material in a relatively small volume. Additionally, we have confirmed a Bragg-enhancement effect arising from coherent scattering within the single-crystal spacers. We have not observed hypothesized refractive effects leading to additional gains at long wavelength. In addition to confirmation of the validity of the Convoluted Moderator concept, our measurements provide a series of benchmark experiments suitable for developing simulation and analysis techniques for practical optimization and eventual implementation at slow neutron source facilities.

Grooved moderator↗

A convex penalty for switching control of partial differential equations

A convex penalty for promoting switching controls for partial differential equations is introduced; such controls consist of an arbitrary number of components of which at most one should be simultaneously active. Using a Moreau–Yosida approximation, a family of approximating problems is obtained that is amenable to solution by a semismooth Newton method. In conclusion, the efficiency of this approach and the structure of the obtained controls are demonstrated by numerical examples.

97 MATHEMATICS AND COMPUTING↗

Smartphone-based Dual-channel Immunochromatographic Test Strip with Polymer Quantum Dot Labels for Simultaneous Detection of Cypermethrin and 3-phenoxybenzoic acid

Currently, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are the primary methods used to detect pesticides and their metabolites for biomonitoring of exposure. Although GC-MS and LC-MS can provide accurate and sensitive measurements, these techniques are not suitable for point-of-care or in-field biomonitoring applications. The objective of this work is to develop a smartphone-based dual-channel immunochromatographic test strip (ICTS) for on-site biomonitoring of exposure to cypermethrin by simultaneous detection of cypermethrin and its metabolite, 3-phenoxybenzoic acid (3-PBA). Polymer carbon dots (PCDs) with ultra-high fluorescent brightness were synthesized and used as signal amplifier in ICTS assay. Cypermethrin (a representative pyrethroid pesticide) and its major metabolite 3-PBA were simultaneously detected to provide more comprehensive analysis of cypermethrin exposure. After competitive immunoreactions between the target sample and the coating antigens preloaded on the test line, the tracer antibody (PCDs conjugated antibody) was quantitatively captured on the test lines. The captured PCDs were inversely proportional to the amount of the target compound in sample. The red fluorescence on the test line then was recorded by a smartphone-based device capable of conducting image analysis and recording. Under optimal conditions, the sensor showed excellent linear responses for detecting cypermethrin and 3-PBA ranging from 1 ng/mL to 100 ng/mL and from 0.1 ng/mL to 100 ng/mL, the limits of detection were calculated to be ~0.35 ng/mL for cypermethrin and ~0.04 ng/mL for 3-PBA, respectively. The results demonstrate that the ICTS device is promising for accurate point-of-care biomonitoring of pesticide exposure.

Zhao, Yuting↗

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. Here, in this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

Feedstock price and availability are key challenges for biorefinery development and biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the variability of yields of hydrolyzed sugar remained unclear. This study quantifies the uncertainties in the sugar yields from the blends of corn stover, switchgrass, and grass clippings by considering both variable and model uncertainties. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A further investigation on xxx demonstrates that the reduction in overall uncertainty is achieved by reduced compositional uncertainties of blended feedstock. Based on these results, the optimization of blending ratios was performed with respect to three objectives: (1) probability of meeting the sugar yield target; (2) expected sugar yields; and (3) sugar yield per unit feedstock expense, while satisfying constraints of feedstock availability and cost. In conclusion, the optimization method developed in this study, is readily applied to other combinations of feedstocks, biofuels production processes, and constraints.

09 BIOMASS FUELS↗

First-Principles Prediction of Thermodynamically Stable Two-Dimensional Electrides

Two-dimensional (2D) electrides, emerging as a new type of layered material whose electrons are confined in interlayer spaces instead of at atomic proximities, are receiving interest for their high performance in various (opto)electronics and catalytic applications. Experimentally, however, 2D electrides have been only found in a couple of layered nitrides and carbides. We report new thermodynamically stable alkaline-earth based 2D electrides by using a first-principles global structure optimization method, phonon spectrum analysis, and molecular dynamics simulation. The method was applied to binary compounds consisting of alkaline-earth elements as cations and group VA, VIA, or VIIA nonmetal elements as anions. We also revealed that the stability of a layered 2D electride structure is closely related to the cation/anion size ratio; stable 2D electrides possess a sufficiently large cation/anion size ratio to minimize electrostatic energy among cations, anions, and anionic electrons. This work demonstrates a new avenue to the discovery of thermodynamically stable 2D electrides beyond experimental material databases and provides new insight into the principles of electride design.

36 MATERIALS SCIENCE↗

Extricating New Physics Scenarios at DUNE with Higher Energy Beams

Here, the proposed Deep Underground Neutrino Experiment (DUNE) utilizes a wide-band on-axis tunable muon-(anti)neutrino beam with a baseline of 1300 km to search for CP violation with high precision. Given the long baseline, DUNE is also sensitive to effects due to matter induced non-standard neutrino interactions (NSI) which can interfere with the standard three-flavor oscillation paradigm. Hence it is desirable to design strategies to disentangle effects due to NSI from standard oscillations. In this article, we exploit the tunability of the DUNE neutrino beam over a wide-range of energies to devise an experimental strategy for separating oscillation effects due to NSI from the standard three- flavor oscillation scenario. Using χ 2 analysis, we obtain an optimal combination of beam tunes and distribution of run times in neutrino and anti-neutrino modes that would enable DUNE to isolate new physics scenarios from the standard. We can distinguish scenarios at 3σ (5σ) level for almost all (~50%) values of δ. To the best of our knowledge, our strategy is entirely new and has not been reported elsewhere.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Thermodynamic guiding principles of high-capacity phase transformation materials for splitting H 2 O and CO 2 by thermochemical looping

Here, thermochemical looping splitting of water and carbon dioxide (CO 2 ) with greenhouse-gas-free (GHG-free) energy has the potential to help address the Gt-scale GHG emissions challenge. Reaction thermodynamics largely contributes to the main bottlenecks of cost reduction for thermochemical looping water/CO 2 splitting cycle. Here, we analyze thermodynamic driving forces in such cycles with two-phase ternary ferrites as model systems. We find that cation configurational entropy chiefly determines the change of partial molar entropy with oxygen stoichiometry. In addition, our phase diagram analysis accurately predicts the optimal Fe ratio for maximal water/CO 2 splitting capacity in thermal reduction and in chemical reduction based cycles, underlining the significance of phase boundary positions. With chemical reduction, >10% CO 2 conversion and high oxygen exchange capacity can both be achieved. Furthermore, our reduced Gibbs free energy model illustrates critical thermodynamic factors that influence the water/CO 2 splitting capacity. Our research reveals the thermodynamic driving forces underlying the unconventional high-capacity Fe-poor ferrites, further explained via phase diagrams of Fe–Co–O, Fe–Ni–O and Fe–Mg–O. Future materials improvements can be guided by our reduced Gibbs free energy model.

08 HYDROGEN↗

High-stability cryogenic scanning tunneling microscope based on a closed-cycle cryostat

We report on the design and operation of a cryogenic ultra-high vacuum (UHV) scanning tunneling microscope (STM) coupled to a closed-cycle cryostat (CCC). The STM is thermally linked to the CCC through helium exchange gas confined inside a volume enclosed by highly flexible rubber bellows. The STM is thus mechanically decoupled from the CCC, which results in a significant reduction of the mechanical noise transferred from the CCC to the STM. Noise analysis of the tunneling current shows current fluctuations up to 4% of the total current, which translates into tip-sample distance variations of up to 1.5 picometers. This noise level is sufficiently low for atomic-resolution imaging of a wide variety of surfaces. To demonstrate this, atomic-resolution images of Au(111) and NaCl(100)/Au(111) surfaces, as well as of carbon nanotubes deposited on Au(111), were obtained. Thermal drift analysis showed that under optimized conditions, the lateral stability of the STM scanner can be as low as 0.18 Å/h. Scanning Tunneling Spectroscopy measurements based on the lock-in technique were also carried out, and showed no detectable presence of noise from the closed-cycle cryostat. Using this cooling approach, temperatures as low as 16 K at the STM scanner have been achieved, with the complete cool-down of the system typically taking up to 12 h. These results demonstrate that the constructed CCC-coupled STM is a highly stable instrument capable of highly detailed spectroscopic investigations of materials and surfaces at the atomic scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Giant magnetoresistance modulated by magnetic field in graphene p-n junction

We investigate the tunneling transport across a graphene p-n junction under the influence of a perpendicular magnetic field (B field). We observe a sideway deflection of the transmission profile, which can be quantitatively explained by invoking the classical Lorentz force. By considering the trajectory of the Dirac fermions along their cyclotron orbits, we analytically derive the incident angles for transmission across the graphene junction under a B field, as well as the critical magnetic field for full suppression of tunneling across the junction. These analytical predictions are consistent with the numerical results obtained via the non-equilibrium Green's function method. A stronger B-field conductance modulation is obtained for a p-n as opposed to an n-n or p-p type graphene junction. The magnetic field also induces a forbidden region of almost zero transmission for electron energy close to the Dirac point, which can be utilized to achieve a giant magnetoresistance effect. Based on our analysis, we devise an optimal magneto-electrical transport modulation, which can potentially realize a giant magnetoresistance effect in graphene p-n junction systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy transfer between a passing vortex ring and a flexible plate in an ideal quiescent fluid

Recent advancements in highly deformable smart materials have lead to increasing interest in small-scale energy harvesting research for powering low consumption electronic devices. One such recent experimental study by Goushcha et al. explored energy harvesting from a passing vortex ring by a cantilevered smart material plate oriented parallel to and offset from the path of the ring in an otherwise quiescent fluid. The present study focuses on modeling this experimental study using potential flow to facilitate optimization of the energy extraction from the passing ring to raise the energy harvesting potential of the device. The problem is modeled in two-dimensions with the vortex ring represented as a pair of counter-rotating free vortices. Vortex pair parameters are determined to match the convection speed of the ring in the experiments, as well as the imposed pressure loading on the plate. The plate is approximated as a Kirchhoff-Love plate and represented as a finite length vortex sheet in the fluid domain. The analytical model matches experimental measurements, including the tip displacement, the integrated force along the entire plate length as a function of vortex ring position, and the pressure along the plate. The potential flow solution is employed in a parametric study of the governing dimensionless parameters in an effort to guide the selection of plate properties for optimal energy harvesting performance. Results of the study indicate an optimal set of plate properties for a given vortex ring configuration, in which the time-scale of vortex advection matches that of the plate vibration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A simulation-optimization model for Stone column-supported embankment stability considering rainfall effect

Landslide due to rainfall has been and continues to be one of the most important concerns of geotechnical engineering. The paper presents the variation of factor of safety of stone column-supported embankment constructed over soft soil due to change in water level for an incessant period of rainfall. A combined simulation-optimization based methodology has been proposed to predict the critical surface of failure of the embankment and to optimize the corresponding factor of safety under rainfall conditions using an evolutionary genetic algorithm NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). It has been observed that the position of water table can be reliably estimated with varying periods of infiltration using developed numerical method. The parametric study is presented to study the optimum factor of safety of the embankment and its corresponding critical failure surface under the steady-state infiltration condition. Results show that in case of floating stone columns, period of infiltration has no effect on factor of safety. Even critical failure surfaces for a particular floating column length remain same irrespective of rainfall duration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantitative spectromicroscopy from inelastically scattered photoelectrons in the hard X-ray range

We demonstrate quantitative, highly bulk-sensitive x-ray photoelectron emission microscopy by analysis of inelastically scattered photoelectrons in the hard X-ray range, enabling elemental depth distribution analysis in deeply buried layers. We show results on patterned structures used in electrical testing of high electron mobility power transistor devices with an epitaxial Al{sub 0.25}Ga{sub 0.75}N channel and a Ti/Al metal contact. From the image series taken over an energy range of up to 120 eV in the Ti 1s loss feature region and over a typical 100 μm field of view, one can accurately retrieve, using background analysis together with an optimized scattering cross-section, the Ti depth distribution from 14 nm up to 25 nm below the surface. The method paves the way to multi-elemental, bulk-sensitive 3D imaging and investigation of phenomena at deeply buried interfaces and microscopic scales by photoemission.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗