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At least 343 records · Page 19

Analytical expressions of the surface shape of ‘diaboloid’ mirrors

Modern deterministic polishing processes allow fabrication of x-ray optics with almost any arbitrary aspherical surface shape. Among these optics, the so called "diaboloid"mirror is of special interest. The diaboloid mirror that converts a cylindrical wave to a spherical wave would improve focusing in x-ray beamlines implementing a diffraction element between a parabolic cylinder and a toroidal mirror. The replacement of the toroidal mirror in existing beamlines by the diaboloid mirror would mitigate aberrations. The shape of the diaboloid mirror is usually calculated numerically based on a truncated polynomial solution of the optical path problem. Here, we present an exact analytical solution for the shape of a diaboloid mirror as a function of the conjugate parameters of the mirror placed in a beamline. The derived analytical expressions for the diaboloid mirror in both the canonical and mirror-based coordinate systems are implemented in ray-tracing simulations to verify the beamline performances.

Yashchuk, Valeriy V.↗

Efficient co-solution of time step size and independent state in simulations of fluid-driven fracture propagation with embedded meshes

Here we present an efficient time-continuation scheme for fluid-driven fracture propagation problems in the extended finite element method framework. The approach applies a monolithic solution strategy to a fully coupled and implicit approximation of hydro-mechanical systems in conjunction with simultaneous linear elastic propagation of multiple fractures. At the end of each time step, the process ensures that the weakest fracture tip is in an equilibrium propagation regime. Furthermore, the solution process provides an initialization procedure for the newly created fracture spaces and an a priori estimate of the stress intensity factor growth rate, improving simulation robustness, and efficiency. The solution process is validated using the Kristianovich-Geertsma-de Klerk analytical solution under the toughness- and viscosity-dominated regimes. It is also extended to and demonstrated on problems with multiple fractures undergoing simultaneous propagation with stress shadow interactions. Numerical examples demonstrate that the solution process can reduce the required computational cost by one order of magnitude compared to other existing methods.

42 ENGINEERING↗

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗

Design and operational considerations of catalytic membrane reactors for ammonia synthesis

Production of ammonia using hydrogen derived from renewable electricity instead of hydrocarbon reforming would dramatically reduce the carbon footprint of this commodity chemical. Novel technologies such as catalytic membrane reactors may potentially be more compatible with distributed ammonia production than the conventional Haber-Bosch process. Here, a reactor model is developed based on integrating a standard industrial iron catalyst into a catalytic membrane reactor (CMR) equipped with an inorganic membrane that is selective to NH 3 over N 2 /H 2 . CMR performance is studied as functions of wide ranges of membrane properties and operating conditions. Conversion and ammonia recovery are dictated principally by the ammonia permeance, and the benefits by using membranes become significant above 100 GPU = 3.4 × 10 –8 mol m –2 s –1 Pa –1 . To be effective, the CMR requires a minimum selectivity for ammonia of 10 over both nitrogen and hydrogen, and purity scales with the effective selectivity. Increasing the pressure of operation significantly improves all metrics, and at P = 30 bar with a quality membrane ammonia is almost completely recovered, enabling direct recycle of un-reacted hydrogen and nitrogen without need for recompression. Temperature drives conversion and scales monotonically without thermodynamic limitations in a CMR. Alternatively, the temperature may be reduced as low as 300°C while achieving conversion levels surpassing equilibrium limits at T = 400°C in a conventional reactor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Radical Treatment of Haloacetonitriles in Aqueous Systems: A Kinetic Study

Haloacetonitriles (HANs) are important drinking water disinfection byproducts formed through the chlorination and chloramination of amino acids. Although HAN concentrations in treated water are usually lower than trihalomethanes, they are still of major concern due to their higher cyto- and genotoxicity. HANs undergo chemical transformations by hydrolysis on the hour to week time scales; however, for possible direct water reuse situations, their active removal using advanced oxidation/reduction processes (AO/RPs) may be required. We report here our systematic kinetic study of the four major AO/RP radiolysis species, oxidizing hydroxyl (·OH) and sulfate (SO 4 −· ) radicals and reducing hydrated electron (e aq − ) and hydrogen atoms (H · ) with five HANs (mono-, di-, and trichloroacetonitriles and mono- and dibromoacetonitriles) in water measured using electron pulse radiolysis techniques. At ambient temperatures and pH 1−7, significant reactivity was found for e aq − ( k = (1−5) × 10 10 M −1 s −1 ) and H · atoms ( k = (1 − 40 × 10 7 M −1 s −1 ), but only minimal oxidation by ·OH ( k = (0.6−10) × 10 7 M −1 s −1 ) and SO 4 −· ( k = (0.2−4) × 10 6 M −1 s −1 ) occurred. These data suggest that the large-scale AO/RP treatment of these contaminants will be effective for deaerated reducing systems, where the reductive electron-induced degradation of HANs will occur.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Artificial Intelligence and Computer Vision for Cost-Effective Benthic Habitat Characterizations

Machine learning applied to computer vision and pattern recognition is a type of artificial intelligence that has advanced rapidly in the last 10 to 15 years, spurred forward by breakthroughs in deep convolutional neural networks. These state-of-the-art methods are poised to become widely used in environmental monitoring applications as a result of the increasing abundance of data available from different imaging platforms (e.g., fixed-point cameras, drone surveys, high-resolution satellite data) that can be analyzed to observe, model, and understand environmental conditions. Computer vision and pattern recognition (CVPR) tools advance our ability to use imagery and camera-based tools in cost-effective ways for environmental monitoring. Although these techniques offer great potential, some challenges remain, such as the need for large sets of labeled images for model training and validation and optimized hardware and software to ensure that the models can be trained effectively and in a reasonable amount of time. Here, we have overcome many of these rate-limiting challenges by using a diverse image library built across multiple projects coupled with staff expertise and onsite computing resources. We are working toward a fully automated SPI processing system and also are moving to develop CVPR analytical tools for other imaging platforms and data sets.

02 PETROLEUM↗

Radiolytic degradation of formic acid and formate in aqueous solution: modeling the final stages of organic mineralization under advanced oxidation process conditions

The successful use of advanced oxidation processes to treat aqueous solutions containing undesirable organic species requires the degradation of these species to lower molecular weight, lower hazard compounds. Safe application of this technology requires a thorough understanding of the mechanisms of degradation. These oxidative transformations are mainly initiated by the reactions of reactive oxygen species, particularly hydroxyl radicals. These react with organic molecules to generate carbon-centered radicals. In the presence of dissolved oxygen, the carbon-centered radicals are next converted to peroxyl radicals, which then decay to lower molecular weight species by multiple mechanistic pathways. Formic acid and its conjugate base formate are the last stable chemical species produced immediately before the complete mineralization of any organic molecule undergoing oxidative degradation in aqueous solution. Once understood, the radical-induced chemistry of formic acid/formate under these conditions has wide applicability in all advanced oxidation technologies. To develop this quantitative knowledge, here we have performed a series of 60 Co gamma irradiation studies on aqueous formic acid/formate over different pH and solution conditions. The measured species concentration changes, as a function of applied dose, are compared with the predictions of a kinetic computer model constructed from literature reactions and reported rate coefficients. The excellent agreement found between the results and modeling gives confidence in the mechanism presented here and provide the first complete computer model for the radiolytic degradation of formic acid in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗

Laser synthesis and processing of atomically thin 2D materials

Recent advances in laser synthesis and processing of 2D materials are described that address key issues of scalable synthesis, precise heterogeneity control, and transformative manufacturing. Here, laser spectroscopy is used to remotely characterize and optimize the structure and functionality of 2D materials, enabling their in-situ diagnostic-based synthesis and processing.

2D materials↗

Modelling Development in Radical (Co)Polymerization of Multivinyl Monomers

Radical polymerization (RP) of multivinyl monomers (MVMs) provides a facile solution for manipulating polymer topology and has received increasing attention due to their industrial and academic significance. Continuous efforts have been made to understand their mechanism, which is the key to regulating materials structure. Modelling techniques have become a powerful tool that can provide detailed information on polymerization kinetics which is inaccessible by experiments. Many publications have reported the combination of experiments and modelling for free radical polymerization (FRP) and reversible-deactivation radical polymerizations (RDRP) of MVMs. Herein, a minireview is presented for the most important modelling techniques and their applications in FRP/RDRP of MVMs. This review hopes to illustrate that the combination of modelling and wet experiments can be a great asset to polymer researchers and inspire new thinking for the future MVMs experiment optimization and product design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for dimuon resonance in the 35 to 75 GeV mass range using 140 fb−1 of 13 TeV pp collisions with the ATLAS detector

A model-independent search for low-mass resonances decaying into pairs of oppositely charged muons is presented. The analysis uses proton-proton collision data corresponding to an integrated luminosity of 140 fb−1, recorded by the ATLAS detector at the Large Hadron Collider between 2015 and 2018. The search targets hypothetical dimuon resonances in the invariant mass range from 35 GeV to 75 GeV. The modelling of this mass region is particularly challenging for conventional analytic background parameterisations. To address this, a Gaussian process regression technique is used to model the background. The dimuon mass spectrum is analysed for potential signals, and no statistically significant excess is observed. Upper limits at the 95% confidence level are set on the fiducial production cross-section of new resonances decaying promptly into muons, ranging from 20 fb to 110 fb, depending on the resonance mass. These results are further interpreted in the context of dark-photon and dark-matter-mediator models, leading to new constraints on their parameter spaces.

Aad, G↗

Mafic explosive volcanism at Llaima Volcano: 3D x-ray microtomography reconstruction of pyroclasts to constrain shallow conduit processes

Abstract Mafic volcanic activity is dominated by effusive to mildly explosive eruptions. Plinian and ignimbrite-forming mafic eruptions, while rare, are also possible; however, the conditions that promote such explosivity are still being explored. Eruption style is determined by the ability of gas to escape as magma ascends, which tends to be easier in low-viscosity, mafic magmas. If magma permeability is sufficiently high to reduce bubble overpressure during ascent, volatiles may escape from the magma, inhibiting violent explosive activity. In contrast, if the permeability is sufficiently low to retain the gas phase within the magma during ascent, bubble overpressure may drive magma fragmentation. Rapid ascent may induce disequilibrium crystallization, increasing viscosity and affecting the bubble network with consequences for permeability, and hence, explosivity. To explore the conditions that promote strongly explosive mafic volcanism, we combine microlite textural analyses with synchrotron x-ray computed microtomography of 10 pyroclasts from the 12.6 ka mafic Curacautín Ignimbrite (Llaima Volcano, Chile). We quantify microlite crystal size distributions (CSD), microlite number densities, porosity, bubble interconnectivity, bubble number density, and geometrical properties of the porous media to investigate the role of magma degassing processes at mafic explosive eruptions. We use an analytical technique to estimate permeability and tortuosity by combing the Kozeny-Carman relationship, tortuosity factor, and pyroclast vesicle textures. The groundmass of our samples is composed of up to 44% plagioclase microlites, > 85% of which are < 10 µm in length. In addition, we identify two populations of vesicles in our samples: (1) a convoluted interconnected vesicle network produced by extensive coalescence of smaller vesicles (> 99% of pore volume), and (2) a population of very small and completely isolated vesicles (< 1% of porosity). Computed permeability ranges from 3.0 × 10 −13 to 6.3 × 10 −12 m 2 , which are lower than the similarly explosive mafic eruptions of Tarawera (1886; New Zealand) and Etna (112 BC; Italy). The combination of our CSDs, microlite number densities, and 3D vesicle textures evidence rapid ascent that induced high disequilibrium conditions, promoting rapid syn-eruptive crystallization of microlites within the shallow conduit. We interpret that microlite crystallization increased viscosity while simultaneously forcing bubbles to deform as they grew together, resulting in the permeable by highly tortuous network of vesicles. Using the bubble number densities for the isolated vesicles (0.1-3 −3 × 10 4 bubbles per mm 3 ), we obtain a minimum average decompression rate of 1.4 MPa/s. Despite the textural evidence that the Curacautín magma reached the percolation threshold, we propose that rapid ascent suppressed outgassing and increased bubble overpressures, leading to explosive fragmentation. Further, using the porosity and permeability of our samples, we estimated that a bubble overpressure > 5 MPa could have been sufficient to fragment the Curacautín magma. Other mafic explosive eruptions report similar disequilibrium conditions induced by rapid ascent rate, implying that syn-eruptive disequilibrium conditions may control the explosivity of mafic eruptions more generally.

Valdivia, Pedro↗

Real-space observation of ergodicity transitions in artificial spin ice

Abstract Ever since its introduction by Ludwig Boltzmann, the ergodic hypothesis became a cornerstone analytical concept of equilibrium thermodynamics and complex dynamic processes. Examples of its relevance range from modeling decision-making processes in brain science to economic predictions. In condensed matter physics, ergodicity remains a concept largely investigated via theoretical and computational models. Here, we demonstrate the direct real-space observation of ergodicity transitions in a vertex-frustrated artificial spin ice. Using synchrotron-based photoemission electron microscopy we record thermally-driven moment fluctuations as a function of temperature, allowing us to directly observe transitions between ergodicity-breaking dynamics to system freezing, standing in contrast to simple trends observed for the temperature-dependent vertex populations, all while the entropy features arise as a function of temperature. These results highlight how a geometrically frustrated system, with thermodynamics strictly adhering to local ice-rule constraints, runs back-and-forth through periods of ergodicity-breaking dynamics. Ergodicity breaking and the emergence of memory is important for emergent computation, particularly in physical reservoir computing. Our work serves as further evidence of how fundamental laws of thermodynamics can be experimentally explored via real-space imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evolution of nanopores in hexagonal boron nitride

Abstract The engineering of atomically-precise nanopores in two-dimensional materials presents exciting opportunities for both fundamental science studies as well as applications in energy, DNA sequencing, and quantum information technologies. The exceptional chemical and thermal stability of hexagonal boron nitride (h-BN) suggest that exposed h-BN nanopores will retain their atomic structure even when subjected to extended periods of time in gas or liquid environments. Here we employ transmission electron microscopy to examine the time evolution of h-BN nanopores in vacuum and in air and find, even at room temperature, dramatic geometry changes due to atom motion and edge contamination adsorption, for timescales ranging from one hour to one week. The discovery of nanopore evolution contrasts with general expectations and has profound implications for nanopore applications of two-dimensional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗