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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 253 records · Page 14

Implementation of Self-Align Local Poly Interconnection on 0.25 Micron Flash Memory

For ETOX Flash technology. the self-aligned source module plays a critical role in minimizing cell size. For advanced Flash technology using the shallow-trench isolation (STI) scheme, however, it is difficult to form a stable source line. The Flash process in this experiment features an ETOX structure and with SIN spacer. Poly-Si (implanted poly) is used as the local interconnection material connecting the source line and was successfully implemented in the ETOX flash array in this paper.

C H Lee↗

Intranasal Nanoparticle Vaccination Elicits a Persistent, Polyfunctional CD4 T Cell Response in the Murine Lung Specific for a Highly Conserved Influenza Virus Antigen That Is Sufficient To Mediate Protection from Influenza Virus Challenge

We report lung-localized CD4 T cells play a critical role in the control of influenza virus infection and can provide broadly protective immunity. However, current influenza vaccination strategies primarily target influenza hemagglutinin (HA) and are administered peripherally to induce neutralizing antibodies. We have used an intranasal vaccination strategy targeting the highly conserved influenza nucleoprotein (NP) to elicit broadly protective lung-localized CD4 T cell responses. The vaccine platform consists of a self-assembling nanolipoprotein particle (NLP) linked to NP with an adjuvant. We have evaluated the functionality, in vivo localization, and persistence of the T cells elicited. Our study revealed that intranasal vaccination elicits a polyfunctional subset of lung-localized CD4 T cells that persist long term. A subset of these lung CD4 T cells localize to the airway, where they can act as early responders following encounter with cognate antigen. Polyfunctional CD4 T cells isolated from airway and lung tissue produce significantly more effector cytokines IFN-γ and TNF-α, as well as cytotoxic functionality. When adoptively transferred to naive recipients, CD4 T cells from NLP:NP-immunized lung were sufficient to mediate 100% survival from lethal challenge with H1N1 influenza virus.

59 BASIC BIOLOGICAL SCIENCES↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Modeling of single-event upset in bipolar integrated circuits

The results of work done on the quantitative characterization of single-event upset (SEU) in bipolar random-access memories (RAMs) have been obtained through computer simulation of SEU in RAM cells that contain circuit models for bipolar transistors. The models include current generators that emulate the charge collected from ion tracks. The computer simulation results are compared with test data obtained from a RAM in a bipolar microprocessor chip. This methodology is applicable to other bipolar integrated circuit constructions in addition to RAM cells.

Zoutendyk, J. A.↗

2003 NASA Faculty Fellowship Program at Glenn Research Center

The Office of Education at NASA Headquarters provides overall policy and direction for the NASA Faculty Fellowship Program (NFFP). The American Society for Engineering Education (ASEE) and the Universities Space Research Association (USRA) have joined in partnership to recruit participants, accept applications from a broad range of participants, and provide overall evaluation of the NFFP. The NASA Centers, through their University Affairs Officers, develop and operate the experiential part of the program. In concert with co-directing universities and the Centers, Fellows are selected and provided the actual research experiences. This report summarizes the 2003 session conducted at the Glenn Research Center (GRC).Research topics covered a variety of areas including, but not limited to, biological sensors, modeling of biological fluid systems, electronic circuits, ceramics and coatings, unsteady probablistic analysis and aerodynamics, gas turbines, environmental monitoring systems for water quality, air quality, gaseous and particulate emissions, bearings for flywheel energy storage, shape memory alloys,photonic interrogation and nanoprocesses,carbon nanotubes, polymer synthesis for fuel cells, aviation communications, algorithm development and RESPlan Database.

Prahl, Joseph M.↗

Stent with expandable foam

A system comprising first, second, and third shape memory polymers (SMPs); wherein (a) the first SMP is a biodegradable open cell foam that includes a first channel; (b) the second SMP includes a second channel and is included in the first channel; (c) the foam is in a first state and is configured to expand to a second state, radially outward from the second foam, in response to thermal stimulus; (d) the third SMP is between the first and second SMPs and includes a stent having a first strut that includes the third SMP and a second strut that includes the third SMP; and (e) each of the first, second, and third SMPs is coupled to a wire.

Wilson, Thomas S.↗

GSRP/David Marshall: Fully Automated Cartesian Grid CFD Application for MDO in High Speed Flows

With the renewed interest in Cartesian gridding methodologies for the ease and speed of gridding complex geometries in addition to the simplicity of the control volumes used in the computations, it has become important to investigate ways of extending the existing Cartesian grid solver functionalities. This includes developing methods of modeling the viscous effects in order to utilize Cartesian grids solvers for accurate drag predictions and addressing the issues related to the distributed memory parallelization of Cartesian solvers. This research presents advances in two areas of interest in Cartesian grid solvers, viscous effects modeling and MPI parallelization. The development of viscous effects modeling using solely Cartesian grids has been hampered by the widely varying control volume sizes associated with the mesh refinement and the cut cells associated with the solid surface. This problem is being addressed by using physically based modeling techniques to update the state vectors of the cut cells and removing them from the finite volume integration scheme. This work is performed on a new Cartesian grid solver, NASCART-GT, with modifications to its cut cell functionality. The development of MPI parallelization addresses issues associated with utilizing Cartesian solvers on distributed memory parallel environments. This work is performed on an existing Cartesian grid solver, CART3D, with modifications to its parallelization methodology.

Source record↗

A funnel approach to enable analyses of epitope-specific human CD4 T cells specific for influenza and SARS-CoV-2

Protection against pathogens relies heavily on the adaptive immune response, whose key regulators are CD4 T cells. CD4 T cells, notable for their complex repertoire and functional potential, can most easily be dissected by identifying, quantifying, characterizing, and isolating epitope-specific cells. In the study reported here, we present a systematic and unbiased strategy that has enabled the identification of highly immunogenic peptide epitopes derived from influenza virus and SARS-CoV-2, presented by human HLA-DR proteins. Coupling the use of HLA-DR transgenic mice with infection and vaccination and highly sensitive epitope-specific cytokine ELISpot assays, we have narrowed the potential epitopes from 450 to 600 peptides to 5–15 peptides for each allele by an iterative process of elimination and selection, which we have termed a funnel approach. These epitopes have been validated in HLA-DR-typed human CD4 T cells directly ex vivo and enabled the derivation and implementation of HLA-DR peptide tetramers. Tetramer staining of human PBMCs enriched for CD4 T memory populations from healthy adult subjects, highlighted this approach as a sensitive and specific method for identifying novel epitopes, and subsequent CD4 T-cell responses to human viral infections.

CD4 T cell↗

Integrally regulated solar array demonstration using an Intel 8080 microprocessor

A concept for regulating the voltage of a solar array by using a microprocessor to effect discrete voltage changes was demonstrated. Eight shorting switches were employed to regulate a simulated array at set-point voltages between 10,000 and 15,000 volts. The demonstration showed that the microprocessor easily regulated the solar array output voltage independently of whether or not the switched cell groups were binary sized in voltage. In addition, the microprocessor provided logic memory capability to perform additional tasks such as locating and insolating a faulty switch.

Petrik, E. J.↗

SEU hardening of CMOS memory circuit

This paper reports a design technique to harden CMOS memory circuits against Single Event Upset (SEU) in the space environment. A RAM cell and Flip Flop design are presented to demonstrate the method. The Flip Flop was used in the control circuitry for a Reed Solomon encoder designed for the Space Station.

Whitaker, S.↗

Radiation Issues and Applications of Floating Gate Memories

The radiation effects that affect various systems that comprise floating gate memories are presented. The wear-out degradation results of unirradiated flash memories are compared to irradiated flash memories. The procedure analyzes the failure to write and erase caused by wear-out and degradation of internal charge pump circuits. A method is described for characterizing the radiation effects of the floating gate itself. The rate dependence, stopping power dependence, SEU susceptibility and applications of floating gate in radiation environment are presented. The ramifications for dosimetry and cell failure are discussed as well as for the long term use aspects of non-volatile memories.

Scheick, L. Z.↗

Threadsafe Dynamic Neighbor Lists for Monte Carlo Ray Tracing

Monte Carlo (MC) transport codes offer high-fidelity modeling of particle transport physics, but their high computational cost makes them impractical for many applications. For some applications such as multiphysics and depletion that use finely discretized geometries, a large portion of this computational cost is attributable to ray tracing. Neighbor lists are a well-known method for accelerating ray-tracing calculations in a MC code, but despite their prevalence, little work has been published on the details of their implementation. The fine details can have a significant impact on performance, particularly when using shared-memory parallelism. This paper addresses these details of implementation with a discussion of different neighbor list schemes and their impact on software runtime. Performance tests were run by using OpenMC on a pin-cell problem discretized with up to 200 axial regions. The results demonstrate that switching from surface-based to cell-based neighbor lists leads to a 10 faster calculation rate for the most fine discretization. Finally, using a threadsafe shared-memory data structure results in a 20% faster calculation rate versus simple threadprivate neighbor lists. Results here show that a data structure that is contiguous in memory improves performance by only 1% to 2% over noncontiguous linked lists.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

EAP Patterns

EAP Patterns: Memory access and iteration patterns from the EAP code base with the physics removed. This is intended to be a serial app representing memory access patterns. We will populate the data structures from EAP output files to provide representative patterns of face and cell loops within the EAP code base The arguments to the program are the EAP output file and the number of MPI processors to emulate. Currently there is no MPI in the application and the number of processors represents a means of emulating the halo (clone) cells around the domain of the given processor. An optional argument `processor_ID` can be provided to specify the processor to emulate. In the future we plan to include the ability to run multiple MPI ranks to more accurately represent the on-node demands on memory bandwidth.

Swaminarayan, Sriram↗

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗

The human aortic endothelium undergoes dose-dependent DNA methylation in response to transient hyperglycemia

Glycemic control is a strong predictor of long-term cardiovascular risk in patients with diabetes mellitus, and poor glycemic control influences long-term risk of cardiovascular disease even decades after optimal medical management. This phenomenon, termed glycemic memory, has been proposed to occur due to stable programs of cardiac and endothelial cell gene expression. This transcriptional remodeling has been shown to occur in the vascular endothelium through a yet undefined mechanism of cellular reprogramming.

60 APPLIED LIFE SCIENCES↗

R-Adaptivity to Enable Compression of Elementary Computations in Extreme-Scale Finite Element Simulators

Modern computing systems are capable of exascale calculations, which are revolutionizing the development and application of high-fidelity numerical models in computational science and engineering. While these systems continue to grow in processing power, the available system memory has not increased commensurately, and electrical power consumption continues to grow. A predominant approach to limit the memory usage in large-scale applications is to exploit the abundant processing power and continually recompute many low-level simulation quantities, rather than storing them. However, this approach can adversely impact the throughput of the simulation and diminish the benefits of modern computing architectures. We present three novel contributions to reduce the memory burden while maintaining, and sometimes improving, performance in simulations based on finite element discretizations. The first contribution develops dictionary-based data compression schemes that detect and exploit the structure of the discretization, due to redundancies across the finite element mesh. While these schemes are shown to reduce memory requirements by more than 99% on meshes with large numbers of identical mesh cells, there are applications where this structure does not exist. The second contribution leverages a recently developed augmented Lagrangian optimization algorithm to enable r-adaptivity for meshes with the goal of enhancing the redundancies in the mesh. The third contribution extends these methods to patch-based linear solvers and preconditioners by compressing local matrices. Numerical results demonstrate the effectiveness of the proposed methods to detect, enhance and exploit mesh structure on a suite of examples inspired by large-scale applications.

97 MATHEMATICS AND COMPUTING↗

Acousto-optic techniques for real SAR imaging

Recent advancements in the development of the Real Time Acousto-optic SAR Processor are presented. In particular, the technique for introducing the azimuth reference function into the processor via an acousto-optic Bragg cell is discussed. This approach permits the reference function to be stored in electronic memory, thus giving the processor the flexibility needed to adapt rapidly to changes in the radar/target geometry. The architecture is described and results are presented which show the applicability of the technique to both spot-light and strip-map SAR.

Haney, M.↗

Ion-Conducting Organic/Inorganic Polymers

Ion-conducting polymers that are hybrids of organic and inorganic moieties and that are suitable for forming into solid-electrolyte membranes have been invented in an effort to improve upon the polymeric materials that have been used previously for such membranes. Examples of the prior materials include perfluorosulfonic acid-based formulations, polybenzimidazoles, sulfonated polyetherketone, sulfonated naphthalenic polyimides, and polyethylene oxide (PEO)-based formulations. Relative to the prior materials, the polymers of the present invention offer greater dimensional stability, greater ease of formation into mechanically resilient films, and acceptably high ionic conductivities over wider temperature ranges. Devices in which films made of these ion-conducting organic/inorganic polymers could be used include fuel cells, lithium batteries, chemical sensors, electrochemical capacitors, electrochromic windows and display devices, and analog memory devices. The synthesis of a polymer of this type (see Figure 1) starts with a reaction between an epoxide-functionalized alkoxysilane and a diamine. The product of this reaction is polymerized by hydrolysis and condensation of the alkoxysilane group, producing a molecular network that contains both organic and inorganic (silica) links. The silica in the network contributes to the ionic conductivity and to the desired thermal and mechanical properties. Examples of other diamines that have been used in the reaction sequence of Figure 1 are shown in Figure 2. One can use any of these diamines or any combination of them in proportions chosen to impart desired properties to the finished product. Alternatively or in addition, one could similarly vary the functionality of the alkoxysilane to obtain desired properties. The variety of available alkoxysilanes and diamines thus affords flexibility to optimize the organic/inorganic polymer for a given application.

Kinder, James D.↗