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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Application of machine learning for the estimation of electron energy distribution from optical emission spectra

Abstract This paper discusses the use of probabilistic deep neural networks for the prediction of the electron energy probability function in low-temperature non-thermal plasmas. The neural networks are trained using optical emission spectroscopy and Langmuir probe measurements, with the goal of providing a reliable estimate of the electron energy probability function solely from optical emission data. The performance of both non-Bayesian and Bayesian networks is evaluated. It is found that Bayesian models are preferable as they assign a higher level of uncertainty to their prediction especially when the dataset used to train them is small. This work describes one of the many potential applications of machine learning in plasma science and technology.

Physics↗
DOE OSTI2022

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↗
DOE OSTI2025

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↗
DOE OSTI2023

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↗
DOE OSTI2020

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↗
DOE OSTI2021

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↗
DOE OSTI2023

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↗
DOE OSTI2022

Slip velocity boundary conditions for the lattice Boltzmann modeling of microchannel flows

Abstract Slip flows in ducts are important in numerous engineering applications, most notably in microchannel flows. Compared to the standard no‐slip Dirichlet condition, the case of slip formulates as a Robin‐type condition for the fluid tangential velocity. Such an increase in mathematical complexity is accompanied by a more challenging numerical transcription. The present work concerns with this topic, addressing the modeling of the slip velocity boundary condition in the lattice Boltzmann method (LBM) applied to steady slow viscous flows inside ducts of nontrivial shapes. As novelty, we extend the newly revised local second‐order boundary (LSOB) Dirichlet fluid flow method [ Philos. Trans. R. Soc. A 378, 20190404 (2020)] to implement the slip velocity condition within the two‐relaxation‐time (TRT) framework. The LSOB follows an in‐node philosophy where its operation principle seeks to explicitly reconstruct the unknown boundary populations in the form of a third‐order accurate Chapman–Enskog expansion, where the wall slip condition is built‐in as a normal Taylor‐type condition. The key point of this approach is that the required first‐ and second‐order momentum derivatives, rather than computed through nonlocal finite difference approximations, are locally determined through a simple local linear algebra procedure, whose formulation is particularly aided by the TRT symmetry argument. To express the obtained derivatives, two approaches are considered, called and , which operate with node and wall variables, respectively. These two formulations are developed to prescribe the physical slip condition over plane and curved walls, including the corners. Their consistency and accuracy characteristics are examined against alternative linkwise strategies to impose the wall slip velocity, such as the kinetic‐based diffusive bounce‐back scheme, the central linear interpolation slip scheme, and the multireflection slip scheme. The several slip schemes are tested over different 3D microchannel configurations, with walls not conforming with the LBM uniform mesh. Numerical tests confirm the advanced accuracy characteristics of the proposed LSOB slip boundary scheme, revealing the added challenge of the wall slip modeling, and that parabolic accuracy is a necessary requirement to reach second‐order accuracy within this problem class.

Silva, Goncalo↗
DOE OSTI2024

Surface Functionalization of Carbon Black for PEM Fuel Cell Electrodes

Abstract Carbon‐based materials are extensively used in fuel cell applications due to their crucial role in maintaining high performance. Particularly, carbon black (CB) stands out as a preferred electrode material for fuel cells, owing to its high electrical conductivity and large surface area. This review focuses on the functionalization of CB and its use as a support for Pt‐based catalysts in proton exchange membrane fuel cells. Functionalization strategies include oxidation, covalent functionalization, as well as polymer grafting or impregnation. Various approaches to functionalize the CB surface are discussed that effectively tailor the surface properties of electrodes, leading to improved fuel cell performance. The improvements are seen in enhanced dispersibility of catalyst particles, better ionomer distribution, increased catalyst stability, and reduced carbon corrosion. This review provides an overview of various modifications applied to CB to enhance their structural and electrochemical properties, thereby boosting fuel cell performance.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Electrowetting‐Mediated Transport to Produce Electrochemical Transistor Action in Nanopore Electrode Arrays

Abstract Understanding water behavior in confined volumes is important in applications ranging from water purification to healthcare devices. Especially relevant are wetting and dewetting phenomena which can be switched by external stimuli, such as light and electric fields. Here, these behaviors are exploited for electrochemical processing by voltage‐directed ion transport in nanochannels contained within nanopore arrays in which each nanopore presents three electrodes. The top and middle electrodes (TE and ME) are in direct contact with the nanopore volume, but the bottom electrode (BE) is buried beneath a 70 nm silicon nitride (SiN x ) insulating layer. Electrochemical transistor operation is realized when small, defect‐mediated channels are opened in the SiN x . These defect channels exhibit voltage‐driven wetting that mediates the mass transport of redox species to/from the BE. When BE is held at a potential maintaining the defect channels in the wetted state, setting the potential of ME at either positive or negative overpotential results in strong electrochemical rectification with rectification factors up to 440. By directing the voltage‐induced electrowetting of defect channels, these three‐electrode nanopore structures can achieve precise gating and ion/molecule separation, and, as such, may be useful for applications such as water purification and drug delivery.

Kwon, Seung‐Ryong↗
DOE OSTI2023

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

Abstract Thermal sprayed metal coatings are used in many industrial applications, and characterizing the structure and performance of these materials is vital to understanding their behavior in the field. X-ray computed tomography (CT) enables volumetric, nondestructive imaging of these materials, but precise segmentation of this grayscale image data into discrete material phases is necessary to calculate quantities of interest related to material structure. In this work, we present a methodology to automate the CT segmentation process as well as quantify uncertainty in segmentations via deep learning. Neural networks (NNs) have been shown to excel at segmentation tasks; however, memory constraints, class imbalance, and lack of sufficient training data often prohibit their deployment in high resolution volumetric domains. Our 3D convolutional NN implementation mitigates these challenges and accurately segments full resolution CT scans of thermal sprayed materials with maps of uncertainty that conservatively bound the predicted geometry. These bounds are propagated through calculations of material properties such as porosity that may provide an understanding of anticipated behavior in the field.

Martinez, Carianne↗
DOE OSTI2025

Effect of Crystallinity on Polymer Chain Compression in Polyethylene Dynamically Loaded with In-Situ X-Ray Diffraction

Abstract Polyethylene (PE) is a polymer widely used in commercial applications, where the properties of PE can be altered based on the molecular conformation. In this study, shock compression experiments with in-situ x-ray diffraction were conducted on two conformations of PE– low density polyethylene (LDPE) and ultra-high molecular weight polyethylene (UHMWPE). Encouragingly, X-ray diffraction patterns were easily observed in LDPE, which is only 25% crystalline. In agreement with a previous study on HDPE, LDPE exhibited a phase transition at 7.7 GPa. Lower pressure experiments on UHMWPE and LDPE exhibited polymer chain compression, but no occurrence of a phase transition.

36 MATERIALS SCIENCE↗