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At least 793 records · Page 44

Evenly spaced columns in the Bishop Tuff (California, USA) as relicts of hydrothermal cooling

A few square kilometers of the Bishop Tuff in eastern California (USA) have evenly spaced columns that are more resistant to erosion than the surrounding tuff owing to the precipitation of mordenite, a low-temperature (100-130 °C) zeolite. We hypothesize that the columns are a result of instabilities at the liquid water and steam interface as cold water seeped into the still-cooling Bishop Tuff. We use two methods to quantitatively assess this hypothesis. First, scaling shows which hydrodynamic instabilities exist in the system. Second, to account for the effects of multiphase flow, latent heat, and the finite amplitude and temporal evolution of these instabilities we use two-dimensional numerical models of liquid water infiltrating hot tuff. These tests highlight several features of boiling hydrothermal systems. (1) The geometry of at least some convection appears to be broadly captured by linear stability theory that neglects reactive transport, heterogeneity of the host rock, and the finite amplitude of instabilities. (2) Slopes > 10% set the wavelength of convection, meaning that these columns formed somewhere with relatively gentle topography. (3) For permeabilities of > 10 -13 m 2 , the wavelength of the instability changes through time, slowing infiltration, while for permeabilities < 10 -15 m 2 , cooling is dominated by conduction. The spacing and stability of columns increase with higher vertical permeability and decrease with higher horizontal permeability. These columns are a rare window into hydrothermal processes that may be widespread.

58 GEOSCIENCES↗

Preferential flow systems amended with biogeochemical components: imaging of a two-dimensional study

The vadose zone is a highly interactive heterogeneous system through which water enters the subsurface system by infiltration. This paper details the effects of simulated plant exudate and soil component solutions upon unstable flow patterns in a porous medium (ASTM silica sand; US Silica, Ottawa, IL, USA) through the use of two-dimensional tank light transmission method (LTM). The contact angle (θ) and surface tension (γ) of two simulated plant exudate solutions (i.e., oxalate and citrate) and two soil component solutions (i.e., tannic acid and Suwannee River natural organic matter, SRNOM) were analyzed to determine the liquid–gas and liquid–solid interface characteristics of each. To determine if the unstable flow formations were dependent on the type and concentration of the simulated plant exudates and soil components, the analysis of the effects of the simulated plant exudate and soil component solutions were compared to a control solution (Hoagland nutrient solution with 0.01 M NaCl). Fingering flow patterns, vertical and horizontal water saturation profiles, water saturation at the fingertips, finger dimensions and velocity, and number of fingers were obtained using the light transmission method. Significant differences in the interface properties indicated a decrease between the control and the plant exudate and soil component solutions tested; specifically, the control (θ = 64.5° and γ = 75.75mNm -1 ) samples exhibited a higher contact angle and surface tension than the low concentration of citrate (θ = 52.6° and γ = 70.8mNm -1 ). Wetting front instability and fingering flow phenomena were reported in all infiltration experiments. The results showed that the plant exudates and soil components influenced the soil infiltration as differences in finger geometries, velocities, and water saturation profiles were detected when compared to the control. Among the tested solutions and concentrations of soil components, the largest finger width (10.19cm) was generated by the lowest tannic acid solution concentration (0.1mgL -1 ), and the lowest finger width (6.00cm) was induced by the highest SRNOM concentration (10mgL -1 ). Similarly, for the plant exudate solutions, the largest finger width (8.36cm) was generated by the lowest oxalate solution concentration (0.1mgL -1 ), and the lowest finger width (6.63cm) was induced by the lowest citrate concentration (0.1mgL -1 ). The control solution produced fingers with average width of 8.30cm. Additionally, the wettability of the medium for the citrate, oxalate, and SRNOM solutions increased with an increase in concentration. Our research demonstrates that the plant exudates and soil components which are biochemical compounds produced and released in soil are capable of influencing the process of infiltration in soils. The results of this research also indicate that soil wettability, expressed as cosθ 1/2 , should be included in the scaling of the finger dimension, i.e., finger width, when using the Miller and Miller (1956) scaling theory for the scaling of flow in porous media.

58 GEOSCIENCES↗

Design of Heterogeneous Chalcogenide Nanostructures with Pressure-Tunable Gaps and without Electronic Trap States

Heterogeneous nanostructures, such as quantum dots (QDs) embedded in solid matrices or core–shell nanoparticles, are promising platforms for a wide variety of applications, including phosphors with increased quantum yield, photocatalysis, and solar energy conversion. However, characterizing and controlling their interfacial morphology and defects, which greatly influence their electronic properties, have proven difficult in numerous cases. Here we carried out atomistic calculations on chalcogenide nanostructured materials, i.e., PbSe QDs in CdSe matrices and CdSe embedded in PbSe, and we established how interfacial and core structures affect their electronic properties. In particular, we showed that defects present at interfaces of PbSe nanoparticles and CdSe matrices give rise to detrimental intragap states, degrading the performance of photovoltaic devices. Instead, the electronic gaps of the inverted system (CdSe dots in PbSe) are clean, indicating that this material has superior electronic properties for solar applications. In addition, our calculations predicted that the core structure of CdSe and in turn its band gap may be tuned by applying pressure to the PbSe matrix, providing a means to engineering the properties of new functional materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Modeling Hot Spot Experiments on Shocked Octahydro-1,3,5,7-Tetranitro-1,3,5,7-Tetrazocine

The cover picture shows a shock-induced reaction in a porous bed of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX). Our study shows compaction, reaction, and gas jetting during the initial stages of shock in the powder bed. Shock reflection at the glass window interface increases hot spot temperatures in HMX product gas in excess of 7000 K at higher impact speeds which is readily observable using pyrometry techniques. We extract a temperature histogram from simulations at discrete times, using it to calculate an effective emission spectrum and effective temperature, T eff , for comparison to data. Calculating T eff based on Planck's Law with a gray body assumption demonstrates good agreement with hot spot temperature data. The agreement with experimental results validates our mesoscale simulations as useful tools for elucidating the role of hot spot mechanisms in the shock initiation of heterogeneous explosives. Finally, more details can be found in the Full Paper by Harry Springer, Will Bassett, Sorin Bastea, Svjetlana Stekovic, and Craig Tarver on page 330 ff.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of Graph Pattern Matching Workloads in Graph Analysis Systems

Graph analysis has emerged as a powerful method for data scientists to represent, integrate, query, and explore heterogeneous data sources. As a result, graph data management and mining became a popular area of research, and led to the development of plethora of systems in recent years. Unfortunately, the number of emerging graph analysis systems and the wide range of applications, coupled with a lack of apples-to-apples comparisons, make it difficult to understand the trade-offs between different systems and the graph operations for which they are designed. A fair comparison of these systems is a challenging task for the following reasons: multiple data models, non-standardized serialization formats, various query interfaces to users, and diverse environments they operate in. To address these key challenges, in this paper we present a new benchmark suite by extending the Lehigh University Benchmark (LUBM) to cover the most common capabilities of various graph analysis systems. We provide the design process of the benchmark, which generalizes the workflow for data scientists to conduct the desired graph analysis on different graph analysis systems. Equipped with this extended benchmark suite, we present performance comparison for nine subgraph pattern retrieval operations over six graph analysis systems, namely NetworkX, Neo4j, Jena, Titan, GraphX, and uRiKA. Through the proposed benchmark suite, this study reveals both quantitative and qualitative findings in (1) implications in loading data into each system; (2) challenges in describing graph patterns for each query interface; and (3) different sensitivity of each system to query selectivity. We envision that this study will pave the road for: (i) data scientists to select the suitable graph analysis systems, and (ii) data management system designers to advance graph analysis systems.

Hong, Seokyong↗

Water Structure and Properties at Hydrophilic and Hydrophobic Surfaces

The properties of water on both molecular and macroscopic surfaces critically influence a wide range of physical behaviors, with applications spanning from membrane science to catalysis to protein engineering. Yet, our current understanding of water interfacing molecular and material surfaces is incomplete, in part because measurement of water structure and molecular-scale properties challenges even the most advanced experimental characterization techniques and computational approaches. This review highlights progress in the ongoing development of tools working to answer fundamental questions on the principles that govern the interactions between water and surfaces. One outstanding and critical question is what universal molecular signatures capture the hydrophobicity of different surfaces in an operationally meaningful way, since traditional macroscopic hydrophobicity measures like contact angles fail to capture even basic properties of molecular or extended surfaces with any heterogeneity at the nanometer length scale. Resolving this grand challenge will require close interactions between state-of-the-art experiments, simulations, and theory, spanning research groups and using agreed-upon model systems, to synthesize an integrated knowledge of solvation water structure, dynamics, and thermodynamics.

catalysis (heterogeneous)↗

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A comparative study of solute trapping in Fe-(33–45 at%) Cu alloys manufactured by laser directed energy deposition

The high cooling rates in laser directed energy deposition (DED-LB) of alloys lead to substantial amounts of solute trapping as solute atoms cannot diffuse away from the solid/liquid interface before it advances. In some concentrated alloys, this results in supersaturated solid phases that form nanoscale hierarchical microstructures when the solute atoms precipitate out during reheating from subsequent laser passes. We choose the Iron-Copper (Fe-Cu) binary alloy as model system as it is chemically homogeneous in the liquid phase and has negligible solid solubility at room temperature. Two alloys with nominal compositions in atomic (at.) %, Fe67Cu33 and Fe55Cu45, were manufactured using DED-LB. Scanning transmission electron microscopy (STEM), energy dispersive spectroscopy (EDS) and wavelength dispersive spectroscopy (WDS) were used to characterize the nanostructures and heterogeneous chemical compositions. A non-equilibrium solute partitioning model was used to compute the supersaturated chemistries of the constituent phases and validated with experimentally measured compositions. The measured phase compositions of the two alloys were very similar, at roughly 12 at.% Cu and 4 at.% Fe in the α(bcc)-Fe and ε(fcc)-Cu phases respectively, despite having different processing parameters and mechanical behavior. This indicates that the total thermal history, that depends on both the processing parameters and laser scan pattern, plays a stronger role on the final microstructure evolution than just the initial quantity of trapped solute. In addition, we find that current non-equilibrium solute partitioning models applied on the continuum scale fall short of predicting accurate quantitative phase compositions in concentrated alloys, although the qualitative trends are captured correctly.

36 MATERIALS SCIENCE↗

Structural and Dynamical Roles of Bound Polymer Chains in Rubber Reinforcement

The addition of nanofillers to rubber matrices is a powerful route to improve the mechanical properties. Here, we focus on a molecular understanding of basic mechanisms that are important for the reinforcement in rubbers. The key role in this process is ascribed to bound rubber (BR) that engages with the matrix as well as with adjacent nanofillers. To date, this understanding has been impeded by the lack of experimental tools to directly probe the BR chains buried in a polymer matrix composed of the same polymer. To tackle this challenge, we combine neutron scattering/spectroscopy techniques with isotope-labeling and molecular dynamics simulations. The system is a simplified carbon-black-filled polybutadiene. The combined experimental and computational results provide new insights into the local structural and dynamical heterogeneities of BR chains and their interactions with the matrix polymer, highlighting (i) the structural partition of the bound chains into three components (i.e., trains, loops, and tails) and their fractions; (ii) their dynamical hierarchies, i.e., the trains that remain immobile on the filler surface, the loops that are fairly large and hence allow the interdigitation of matrix chains, and the tails with their unique characteristics to reach far out into the matrix and entangle with matrix chains. These multiple roles of the constituent components of the BR chains promote the formation of a well-developed adhesive polymer–filler interface, enhancing the elastic property of a filled rubber. Finally, the comprehensive understanding derived and validated by the model rubber will be translatable to many other polymer nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stress-Alteration Enhancement of the Reactivity of Aluminum Nanoparticles in the Catalytic Decomposition of exo -Tetrahydrodicyclopentadiene (JP-10)

High energy density aluminum nanoparticles (AlNP) upon thermal annealing followed by super-quenching results in elevated stress levels in the metallic core and reduced surface energy at the core-shell interface. Isomer-selective vacuum ultraviolet based photoionization mass spectrometry coupled to a high temperature chemical microreactor reveals that these stress-altered (SA) AlNPs exhibit distinctive temperature-dependent reactivities towards catalytic decomposition of the hydrocarbon jet fuel exo-tetrahydrodicyclopentadiene (JP-10, C 10 H 16 ) compared to untreated (UN) AlNPs. SA-AlNPs show a delayed initiation of the decomposition for JP-10 by 200 K relative to the UN-AlNPs, however, the full decomposition is achieved at 100 K lower temperature. Furthermore, there is less oxygenated products that are generated from the alumina surface-induced heterogeneous oxidation process, and a larger fraction of closed and open-shell hydrocarbons. Furthermore, chemical insight bridging the reactivity order of SA-AlNPs at low and high temperatures, simultaneously, is obtained via a detailed examination of the product branching ratios obtained in this study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AlGaAs/Si dual-junction tandem solar cells by epitaxial lift-off and print-transfer-assisted direct bonding

A novel method is developed to realize a III-V/Si dual-junction photovoltaic cell by combining epitaxial lift-off (ELO) and print-transfer-assisted bonding methods. The adoption of ELO enables III-V wafers to be recycled and reused, which can further lower the cost of III-V/Si photovoltaic panels. For demonstration, high crystal quality, micrometer-thick, GaAs/AlGaAs/GaAs films are lifted off, transferred, and directly bonded onto Si wafer without the use of any adhesive or bonding agents. The bonding interface is optically transparent and conductive both thermally and electrically. Prototype AlGaAs/Si dual-junction tandem solar cells have been fabricated and exhibit decent performance.

14 SOLAR ENERGY↗

Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FE meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.

36 MATERIALS SCIENCE↗

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗

A Strawman for an HPC PowerStack

The landscape of High-Performance Computing (HPC) is changing as we enter the exascale era and power and energy management are key design points for any next generation of supercomputers. Efficiently utilizing procured power and optimizing performance of scientific applications under power and energy constraints is challenging due to several reasons including dynamic phase behavior, processor manufacturing variability and increasing heterogeneity of node-level components. Extending the scope from the node- and application-level up to the system-level introduces further challenges on top of power-unaware job scheduling, which is known to be NP-hard on its own. While there exists several individual efforts across the community to research automatic techniques for managing power and energy better, the majority of these techniques have been specialized to meet the needs of a specific HPC center or specific optimization goals and provide little support to connect them to each other. Some projects, most notably the PowerAPI efforts [1], discuss interfaces that form a good starting point for full stack integration, but these interfaces still need to be hooked up to the wide range of software components offered by academic partners, developers or vendors. Furthermore, a recent survey conducted by the EE HPC WG concluded that the majority of such techniques have lacked the application-awareness required to achieve the best system performance and throughput. Other observations were that each technique tended to target management of power and energy for a different subset of the site or system hardware and that the different techniques tended to perform management at different (and often conflicting) granularities. Unfortunately, the existing techniques have not been designed to coexist simultaneously on one site and cooperate on management in an integrated manner [2]. The lack of application-awareness, lack of coordinated management across different granularities, and the lack of widely accepted interfaces and consequent limited connectivity between modules, can result in substantially underutilized Watts and FLOPS. To address these gaps, the HPC community needs a holistic stack for power and energy management and none currently exists. In our view, a holistic stack is one that is extensible enough to support the present and anticipated future needs of various different HPC centers, one that achieves best system performance and throughput through application-awareness, one that is designed to coordinate management at different granularities, and one that enables the seamless integration of software components from different developers and vendors. In this seminar, our goal is bring together experts from academia, research laboratories, and industry in order to take stock of existing approaches, design points and power management concepts and requirements at the various participant’s institutions, and to design concepts for a holistic power and energy management stack, which we refer to as the HPC PowerStack. Further, we hope to take steps toward defining the interfaces necessary for providing a complete prototype shared among many groups. The intention is to align development and research efforts across the community so that we may share development resources, avoid duplicating effort, agree on common interfaces and reap the rewards together as a community. The intended final outcome of this collaboration will be a holistic, flexible and extensible concept of a software stack ecosystem that allows us to combine product-grade open-source software components to enable runtime optimization of system power, energy, and performance.

97 MATHEMATICS AND COMPUTING↗

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗

Super-Resolved Single-Molecule Tracking Studies of Rhodamine B Accumulation on Fresh and Aged Polyethylene Terephthalate

It is well-known that toxic organic micropollutants (OMs) accumulate on the surfaces of microplastics. However, much remains to be learned about the exact molecular level mechanisms of OM accumulation and how these evolve as the plastics age. In this work, super-resolved single-molecule tracking (SMT) is used for the first time to investigate the accumulation of Rhodamine B (RhB) dye on fresh and artificially aged polyethylene terephthalate (PET) surfaces. PET thin films serve as models for microplastics, while RhB serves as a proxy for the OMs they accumulate. Artificial aging of the films is accomplished by exposing them in a UV-ozone chamber. Water contact angle, spectroscopic ellipsometry, and carbonyl index measurements reveal a gradual decrease in film hydrophobicity, thickness, and carbonyl content with age. Atomic force microscopy (AFM) data reveal an increase in surface roughness and confirm that the films remain largely intact and continuous across the aging times explored. In SMT experiments, wide-field fluorescence videos acquired from the water/PET interface under 7.5 pM RhB reveal both mobile and immobile dye molecules. Measurements of the frame-to-frame displacements of the dye show that diffusion occurs by a desorption-mediated mechanism and that the diffusion rate varies with PET film age. The surface density of mobile dye molecules decreases with increasing PET age, while the population of immobile molecules becomes relatively larger, suggesting an age-dependent transformation of the mechanism(s) by which the dye is accumulated. SMT data reveal that both mobile and immobile molecules repeatedly adsorb over the same surface sites, consistent with the emergence of nanoscale PET surface heterogeneity also revealed by AFM. Estimates of the adsorption coefficients are obtained using a nearest-neighbor analysis, giving values from 9.9 × 10 5 to 2.1 × 10 6 M –1 for immobile molecules and from 1.8 × 10 5 to 2.5 × 10 5 M –1 for mobile molecules on fresh and 5 min aged PET, respectively. Here, anomalous age-dependent variations in the velocity of molecular motion on the PET surface and in the population of immobile molecules are shown to correlate with changes in the strength of RhB adsorption.

Adsorption↗