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The ignition of sputter deposited nanolaminate foils comprising alternating Co and Al layers results in rapid, self-propagating formation reactions. The propagating waves present after ignition of 150 nm-thick foils are characterized in movie mode dynamic transmission electron microscopy where these are found to have reaction speeds and wave morphology that vary with bilayer thickness. High speed videography reveals different bilayer thickness-wave character relationships in 750 nm-thick and 7500 nm-thick Co/Al foils. The reaction speed dependencies on bilayer thickness are calculated for each total thickness by treating the effect of radiation loss as a perturbation from an analytical model described by the difference in the heat of reaction measured in calorimetry and the adiabatic heat of product formation. From this model, an effective activation energy, diffusion constant, and flame temperatures are obtained, which allows for an interpretation of the reaction phase variations with laminate design and their effects on the propagating wave morphology.

Nanoparticles of non-noble metals are useful for many applications but can be prone to sintering or surface oxidation. Here, the authors use a rapid heating-cooling approach to synthesize uniformly distributed nanoparticles in a reduced graphene oxide matrix, and test them as switchable energetic materials.

A new form of aneurysmal dilatation of large vessels is becoming known in patients with human immunodeficiency virus (HIV) infection. We present a case report of a patient with this anomaly and discuss the radiological dilemmas involved in the diagnosis of the disease. This case highlights the need for computed tomography (CT) angiography as the imaging medium of choice.

The term “in situ processing” has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

We describe a novel technique for the simultaneous visualization of multiple scalar fields, e.g. representing the members of an ensemble, based on their contour trees. Using tree alignments, a graph-theoretic concept similar to edit distance mappings, we identify commonalities across multiple contour trees and leverage these to obtain a layout that can represent all trees simultaneously in an easy-to-interpret, minimally-cluttered manner. We describe a heuristic algorithm to compute tree alignments for a given similarity metric, and give an algorithm to compute a joint layout of the resulting aligned contour trees. We apply our approach to the visualization of scalar field ensembles, discuss basic visualization and interaction possibilities, and demonstrate results on several analytic and real-world examples.

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We demonstrate the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.

Nanoparticles hosted in conductive matrices are ubiquitous in electrochemical energy storage, catalysis and energetic devices. However, agglomeration and surface oxidation remain as two major challenges towards their ultimate utility, especially for highly reactive materials. Here we report uniformly distributed nanoparticles with diameters around 10 nm can be self-assembled within a reduced graphene oxide matrix in 10 ms. Microsized particles in reduced graphene oxide are Joule heated to high temperature (∼1,700 K) and rapidly quenched to preserve the resultant nano-architecture. A possible formation mechanism is that microsized particles melt under high temperature, are separated by defects in reduced graphene oxide and self-assemble into nanoparticles on cooling. The ultra-fast manufacturing approach can be applied to a wide range of materials, including aluminium, silicon, tin and so on. One unique application of this technique is the stabilization of aluminium nanoparticles in reduced graphene oxide film, which we demonstrate to have excellent performance as a switchable energetic material.

The computational work to perform particle advection‐based flow visualization techniques varies based on many factors, including number of particles, duration, and mesh type. In many cases, the total work is significant, and total execution time ("performance") is a critical issue. This state‐of‐the‐art report considers existing optimizations for particle advection, using two high‐level categories: algorithmic optimizations and hardware efficiency. The sub‐categories for algorithmic optimizations include solvers, cell locators, I/O efficiency, and precomputation, while the sub‐categories for hardware efficiency all involve parallelism: shared‐memory, distributed‐memory, and hybrid. Finally, this STAR concludes by identifying current gaps in our understanding of particle advection performance and its optimizations. [ABSTRACT FROM AUTHOR]

Reduced diffusion length scales and increased specific surface areas of nanosized metal fuels have recently demonstrated increased reaction rates for these systems, increasing their relevance in a wide variety of applications. The most commonly employed metal fuel, aluminum, tends to oxidize rapidly near its melting point (660 °C) in addition to undergoing a phase change of the nascent oxide shell. To further expand on the understanding of nanosized metal fuel oxidation, tantalum nanoparticles were studied due to their high melting point (3017 °C) in comparison to aluminum. Both traditional slow heating rate and in-situ high heating rate techniques were used to probe the oxidation of tantalum nanoparticles in oxygen containing environments in addition to nanothermite mixtures. When oxidized by gas phase oxygen, the oxide shell of the tantalum nanoparticles rapidly crystallized creating cracks that may attribute to enhanced oxygen diffusion into the particle. In the case of tantalum based nanothermites, oxide shell crystallization was shown to induce reactive sintering with the metal oxide resulting in a narrow range of ignition temperatures independent of the metal oxide used. The oxidation mechanism was modeled using the Deal-Grove model to extract rate parameters, and theoretical burn times for tantalum based nanocomposites were calculated. [ABSTRACT FROM AUTHOR]

BackgroundHeightened stress and insufficient sleep are common in the transition to college, often co-occur, and have both been linked to negative health outcomes. A challenge concerns disentangling whether perceived stress precedes or succeeds changes in sleep. These day-to-day associations may vary across individuals, but short study periods and group-level analyses in prior research may have obscured person-specific phenotypes. ObjectiveThis study aims to obtain stable estimates of lead-lag associations between perceived stress and objective sleep duration in the individual, unbiased by the group, by developing an individual-level linear model that can leverage intensive longitudinal data while remaining parsimonious. MethodsIn total, 55 college students (n=6, 11% second-year students and n=49, 89% first-year students) volunteered to provide daily self-reports of perceived stress via a smartphone app and wore an actigraphy wristband for the estimation of daily sleep duration continuously throughout the academic year (median usable daily observations per participant: 178, IQR 65.5). The individual-level linear model, developed in a Bayesian framework, included the predictor and outcome of interest and a covariate for the day of the week to account for weekly patterns. We validated the model on the cohort of second-year students (n=6, used as a pilot sample) by applying it to variables expected to correlate positively within individuals: objective sleep duration and self-reported sleep quality. The model was then applied to the fully independent target sample of first-year students (n=49) for the examination of bidirectional associations between daily stress levels and sleep duration. ResultsProof-of-concept analyses captured expected associations between objective sleep duration and subjective sleep quality in every pilot participant. Target analyses revealed negative associations between sleep duration and perceived stress in most of the participants (45/49, 92%), but their temporal association varied. Of the 49 participants, 19 (39%) showed a significant association (probability of direction>0.975): 8 (16%) showed elevated stress in the day associated with shorter sleep later that night, 5 (10%) showed shorter sleep associated with elevated stress the next day, and 6 (12%) showed both directions of association. Of note, when analyzed using a group-based multilevel model, individual estimates were systematically attenuated, and some even reversed sign. ConclusionsThe dynamic interplay of stress and sleep in daily life is likely person specific. Paired with intensive longitudinal data, our individual-level linear model provides a precision framework for the estimation of stable real-world behavioral and psychological dynamics and may support the personalized prioritization of intervention targets for health and well-being.