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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75

Imaging elliptically polarized infrared near-fields on nanoparticles by strong-field dissociation of functional surface groups

Abstract We investigate the strong-field ion emission from the surface of isolated silica nanoparticles aerosolized from an alcoholic solution, and demonstrate the applicability of the recently reported near-field imaging at 720 nm [Rupp et al., Nat. Comm., 10(1):4655, 2019] to longer wavelength (2 $$\mu $$ μ m) and polarizations with arbitrary ellipticity. Based on the experimental observations, we discuss the validity of a previously introduced semi-classical model, which is based on near-field driven charge generation by a Monte-Carlo approach and classical propagation. We furthermore clarify the role of the solvent in the surface composition of the nanoparticles in the interaction region. We find that upon injection of the nanoparticles into the vacuum, the alcoholic solvent evaporates on millisecond time scales, and that the generated ions originate predominantly from covalent bonds with the silica surface rather than from physisorbed solvent molecules. These findings have important implications for the development of future theoretical models of the strong-field ion emission from silica nanoparticles, and the application of near-field imaging and reaction dynamics of functional groups on isolated nanoparticles. Graphical abstract

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Exascale workflow applications and middleware: An ExaWorks retrospective

Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. However, these software combinations and integrations are difficult to achieve due to the challenges of coordinating and deploying heterogeneous software components on diverse and massive platforms. Here, we present the ExaWorks project, which addresses many of these challenges. We developed a workflow Software Development Toolkit (SDK), a curated collection of workflow technologies that can be composed and interoperated through a common interface, engineered following current best practices, and specifically designed to work on HPC platforms. ExaWorks also developed PSI/J, a job management abstraction API, to simplify the construction of portable software components and applications that can be used over various HPC schedulers. The PSI/J API is a minimal interface for submitting and monitoring jobs and their execution state across multiple and commonly used HPC schedulers. We also describe several leading and innovative workflow examples of ExaWorks tools used on DOE leadership platforms. Furthermore, we discuss how our project is working with the workflow community, large computing facilities, and HPC platform vendors to address the requirements of workflows sustainably at the exascale.

97 MATHEMATICS AND COMPUTING↗

Cation Adaptive Structures Based on Manganese Cyanide Prussian Blue Analogues: Application of Powder Diffraction Data to Solve Complex, Unprecedented Stoichiometries and New Structure Types

Abstract A Mn(II) salt and A + CN − under anaerobic conditions react to form 2‐D and 3‐D extended structured compounds of A m Mn II n (CN) m+2n stoichiometry. Here, the creation and characterization of this large family of compounds, for example AMn II 3 (CN) 7 , A 2 Mn II 3 (CN) 8 , A 2 Mn II 5 (CN) 12 , A 3 Mn II 5 (CN) 13 , and A 2 Mn II [Mn II (CN) 6 ], where A represents alkali and tetraalkylammonium cations, is reviewed. Cs 2 Mn II [Mn II (CN) 6 ] has the typical Prussian blue face centered cubic unit cell. However, the other alkali salts are monoclinic or rhombohedral. This is in accord with smaller alkali cation radii creating void space that is minimized by increasing the van der Waals stabilization energy by reducing ∠Mn−N≡C, which, strengthens the magnetic coupling and increases the magnetic ordering temperatures. This is attributed to the non‐rigidity of the framework structure due the significant ionic character associated with the high‐spin Mn II sites. For larger tetraalkylammonium cations, the high‐spin Mn sites lack sufficient electrostatic A + ⋅⋅⋅NC stabilization and form unexpected 4‐ and 5‐coordinated Mn sites within a flexible, extended framework around the cation; hence, the size, shape, and charge of the cation dictate the unprecedented stoichio‐metry and unpredictable cation adaptive structures. Antiferromagnetic coupling between adjacent Mn II sites leads to ferrimagnetic ordering, but in some cases antiferromagnetic coupling of ferrimagnetic layers are compensated and synthetic antiferromagnets are observed. The magnetic ordering temperatures for ferrimagnetic A 2 Mn II [Mn II (CN) 6 ] with both octahedral high‐ and low‐spin Mn II sites increase with decreasing ∠Mn−N≡C. The crystal structures for all of the extended structured materials were obtained by powder diffraction.

Chemistry↗

An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

Abstract The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data.

Computer Science↗

(abstract) A High Throughput 3-D Inner Product Processor

A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated.

imaging parallel processing algorithms linear vect↗

Design and Performance of Kokkos Staging Space toward Scalable Resilient Application Couplings

With the growing number of applications designed for heterogeneous HPC devices, application programmers and users are finding it challenging to compose scalable workflows as ensembles of these applications, that are portable, performant and resilient. The Kokkos C++ library has been designed to simplify this cumbersome procedure by providing an intra-application uniform programming model and portable performance. However, assembling multiple Kokkos-enabled applications into a complex workflow is still a challenge. Although Kokkos enables a uniform programming model, the inter-application data exchange still remains a challenge from both performance and software development cost perspectives. In order to address this issue, we propose Kokkos data staging memory space, an extension of Kokkos' data abstraction (memory space) for heterogeneous computing systems. This new abstraction allows to express data on a virtual shared-space for multiple Kokkos applications, thus extending Kokkos to support inter-application data exchange to build an efficient application workflow. Additionally, we study the effectiveness of asynchronous data layout conversions for applications requiring different memory access patterns for the shared data. Our preliminary evaluation with a synthetic benchmark indicate the effectiveness of this conversion adapted to three different scenarios representing access frequency and use patterns of the shared data.

97 MATHEMATICS AND COMPUTING↗

Electrical Interrogation of Thickness‐Dependent Multiferroic Phase Transitions in the 2D Antiferromagnetic Semiconductor NiI 2

Abstract 2D magnetic materials hold promise for quantum and spintronic applications. 2D antiferromagnetic materials are of particular interest due to their relative insensitivity to external magnetic fields and higher switching speeds compared to 2D ferromagnets. However, their lack of macroscopic magnetization impedes detection and control of antiferromagnetic order, thus motivating magneto‐electrical measurements for these purposes. Additionally, many 2D magnetic materials are ambient‐reactive and electrically insulating or highly resistive below their magnetic ordering temperatures, which imposes severe constraints on electronic device fabrication and characterization. Herein, these issues are overcome via a fabrication protocol that achieves electrically conductive devices from the ambient‐reactive 2D antiferromagnetic semiconductor NiI 2 . The resulting gate‐tunable transistors show band‐like electronic transport below the antiferromagnetic and multiferroic transition temperatures of NiI 2 , revealing a Hall mobility of 15 cm 2 V −1 s −1 at 1.7 K. These devices also allow direct electrical probing of the thickness‐dependent multiferroic phase transition temperature of NiI 2 from 59 K (bulk) to 28 K (monolayer).

2D magnets↗