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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Memory-dictated dynamics of single-atom Pt on CeO2 for CO oxidation

Abstract Single atoms of platinum group metals on CeO 2 represent a potential approach to lower precious metal requirements for automobile exhaust treatment catalysts. Here we show the dynamic evolution of two types of single-atom Pt (Pt 1 ) on CeO 2 , i.e., adsorbed Pt 1 in Pt/CeO 2 and square planar Pt 1 in Pt AT CeO 2 , fabricated at 500 °C and by atom-trapping method at 800 °C, respectively. Adsorbed Pt 1 in Pt/CeO 2 is mobile with the in situ formation of few-atom Pt clusters during CO oxidation, contributing to high reactivity with near-zero reaction order in CO. In contrast, square planar Pt 1 in Pt AT CeO 2 is strongly anchored to the support during CO oxidation leading to relatively low reactivity with a positive reaction order in CO. Reduction of both Pt/CeO 2 and Pt AT CeO 2 in CO transforms Pt 1 to Pt nanoparticles. However, both catalysts retain the memory of their initial Pt 1 state after reoxidative treatments, which illustrates the importance of the initial single-atom structure in practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Cancer risk at low doses of ionizing radiation: artificial neural networks inference from atomic bomb survivors

Cancer risk at low doses of ionizing radiation remains poorly defined because of ambiguity in the quantitative link to doses below 0.2 Sv in atomic bomb survivors in Hiroshima and Nagasaki arising from limitations in the statistical power and information available on overall radiation dose. To deal with these difficulties, a novel nonparametric statistics based on the ‘integrate-and-fire’ algorithm of artificial neural networks was developed and tested in cancer databases established by the Radiation Effects Research Foundation. The analysis revealed unique features at low doses that could not be accounted for by nominal exposure dose, including (i) the presence of a threshold that varied with organ, gender and age at exposure, and (ii) a small but significant bumping increase in cancer risk at low doses in Nagasaki that probably reflects internal exposure to 239 Pu. The threshold was distinct from the canonical definition of zero effect in that it was manifested as negative excess relative risk, or suppression of background cancer rates. Such a unique tissue response at low doses of radiation exposure has been implicated in the context of the molecular basis of radiation–environment interplay in favor of recently emerging experimental evidence on DNA double-strand break repair pathway choice and its epigenetic memory by histone marking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

4D Printing via an Unconventional Fused Deposition Modeling Route to High-Performance Thermosets

An unprecedented four-dimensional (4D) printing process allowing high-performance and shape memory thermoset to be printed, for the first time, by fused deposition modeling (FDM) with isotropic properties has been achieved. Here, bisphenol A-based epoxy and benzoxazine were formulated to a low-temperature thermoplastic and high-temperature thermoset resin, which is melt-extrudable and can be postcured into covalently cross-linked material. Carbon nanotube (CNT) was added in the resin to work as both mechanical enhancement filler and rheology modifier to prevent shape deformation during postcuring process. The cross-layer reaction fuses individual layers into an integrity, thus eliminating layer delamination induced by FDM, offering isotropic mechanical properties regardless of the printing orientations. The highly cross-linked network provides outstanding mechanical strength and superb thermal stability. The excellent shape memory performance with fast recovery rate and large recovery degree is also obtained in the three-dimensional (3D) printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Terahertz conductivity of the magnetic Weyl semimetal Mn 3 Sn films

Mn 3 Sn is a noncollinear antiferromagnet which displays a large anomalous Hall effect at room temperature. It is believed that the principal contribution to its anomalous Hall conductivity comes from the Berry curvature. Moreover, dc transport and photoemission experiments have confirmed that Mn 3 Sn may be an example of a time-reversal symmetry breaking Weyl semimetal. Due to a small, but finite moment in the room temperature inverse triangular spin structure, which allows control of the Hall current with the external field, this material has garnered much interest for next generation memory devices and terahertz spintronics applications. In this work, we report a terahertz range study of randomly oriented Mn 3 Sn thin films as a function of temperature. At low frequencies, we found that the optical conductivity can be well described by a single Drude oscillator. The plasma frequency is strongly suppressed in a temperature dependent fashion as one enters the 260 K helical phase. This may be associated with partial gapping of the Fermi surfaces, which comes from breaking translational symmetry along the c-axis. Finally, the scattering rate shows a quadratic temperature dependence below 200 K, highlighting the possible important role of interactions in this compound.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗
DOE OSTI2016

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, relies on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Applications of Strain-Coupled Magnetoelectric Composites

This article deals with research, development and future directions of magnetoelectric composites for practical devices applications. In the past 20 years there has been a surge of research in the area of multiferroics (MF) and magnetoelectrics (ME) due to their potential to replace existing technologies based only on ferroelectric or ferromagnetic materials. Some of the magnetoelectric composites show exceptionally high potential in the area of magnetic field sensors, however, work remains before commercialization can be realized. The cross coupling among various ferroic parameters in magnetoelectric composites is several orders higher than single phase magetoelectrics, which make its favorable for low detection (nT or pT) magnetic field sensors. Advances in both layered structures or controlled three-dimensional matrix composites for applications as magnetoelectric nonvolatile memory elements are both required. Robust cross-coupling among various parameters with more than four logic states and its compatibility with complementary-symmetry metal–oxide–semiconductor (CMOS) technology are the main requirements for heterostructure magnetoelectric thin films. The major hurdles in the area of magnetoelectric nonvolatile memory elements are poor interfacial properties and weak magnetoelectric coupling for high density fast read and write processes. Another potential area is strained coupled magneto-electric composites where magnetostriction mediated dimensional change in the magnetic layer effectively modulate the change in the dimension of piezoelectric layers via piezostriction, which leads to a strong ME coupling where their coupling magnitude is sufficient for magnetic field sensors. Energy harvesters based on magnetoelectric composites are also intriguing concepts to capture various types of waste energy, in the form mechanical vibration, pressure, wind energy, hydrothermal and waste temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurements of Single Event Upset in ATLAS IBL

Effects of Single Event Upsets (SEU) and Single Event Transients (SET) are studied in the FE-I4B chip of the innermost layer of the ATLAS pixel system. SEU/SET affect the FE-I4B Global Registers as well as the settings for the individual pixels, causing, among other things, occupancy losses, drops in the low voltage currents, noisy pixels, and silent pixels. Quantitative data analysis and simulations indicate that SET dominate over SEU on the load line of the memory. Operational issues and mitigation techniques are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Scaling up of High-Performance Single Crystalline Ni-rich Cathode Materials (CRADA 509)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and Albemarle Corporation (“Participant”) to develop and scale up an innovative and low-cost synthesis approach for preparing high-performance single crystalline Ni-rich cathode materials, i.e., LiNi0.8Mn0.1Co0.1O2 (NMC811) and LiNi0.9Mn0.05Co0.05O2 (NMC90) for next-generation LIBs. At the end of this project, the team will (1) develop a cost-effective synthesis approach for preparing single crystalline MNC811 (>200 mAh/g) and NMC90 (>210 mAh/g) by using advanced lithium salts, (2) address the performance issues of single crystals prepared from large-scale synthesis, and (3) demonstrate the processing/scaling up capabilities of up to 1 kg/batch of high-performance NMC811 and NMC90 single crystals.

36 MATERIALS SCIENCE↗
NASA NTRS1980

DSS command software update

The modifications, additions, and testing results for a version of the Deep Space Station command software, generated for support of the Voyager Saturn encounter, are discussed. The software update requirements included efforts to: (1) recode portions of the software to permit recovery of approximately 2000 words of memory; (2) correct five Voyager Ground data System liens; (3) provide capability to automatically turn off the command processor assembly local printer during periods of low activity; and (4) correct anomalies existing in the software.

Stinnett, W. G.↗
NASA NTRS1992

Development of iterative techniques for the solution of unsteady compressible viscous flows

A research effort was initiated at Georgia Tech in February 1991 on the development of efficient techniques for the computation of 2-D and 3-D unsteady compressible flow problems. It was found that in 2-D unsteady viscous flow applications, the generalized minimal residual (GMRES) scheme was able to significantly improve the accuracy and stability characteristics of an existing 2-D ADI (Alternating Direction Implicit) time marching scheme. That is, the GMRES/ADI combination allowed 10 to 20 times larger time steps compared to an ADI scheme. Because the GMRES algorithm requires 5 to 10 times the CPU work compared to the ADI scheme, the combined GMRES/ADI scheme yields a net factor of 2 savings in CPU cost. During the past year, we also experimented with GMRES/multigrid/ADI combination. The purpose of this combination was to compute the low frequency components of the change in the flow properties from one time step to the next on a coarse grid. This strategy reduces the memory requirements of the GMRES method roughly by a factor of 4-8 for steady flow problems.

Sankar, Lakshmi N.↗
NASA NTRS1994

Instrument Records And Plays Back Acceleration Signals

Small, battery-powered, hand-held instrument feeds power to accelerometer and records time-varying component of output for 15 seconds in analog form. No power needed to maintain content of memory; memory chip removed after recording and stored indefinitely. Recorded signal plays back at any time up to several years later. Principal advantages: compactness, portability, and low cost.

Bozeman, Richard J.↗
NASA NTRS2004

Effects of heavy ion to the primary culture of mouse brain cells

To investigate effects of low dose heavy particle radiation to CNS system, we adopted mouse neonatal brain cells in culture being exposed to heavy ions by HIMAC at NIRS and NSRL at BNL. The applied dose varied from 0.05 Gy up to 2.0 Gy. The subsequent biological effects were evaluated by an induction of apoptosis and neuron survival focusing on the dependencies of the animal strains, SCID, B6, B6C3F1, C3H, used for brain cell culture, SCID was the most sensitive and C3H the least sensitive to particle radiation as evaluated by 10% apoptotic criterion. The LET dependency was compared with using SCID and B6 cells exposing to different ions (H, C, Ne, Si, Ar, and Fe). Although no detectable LET dependency was observed in the high LET (55-200 keV/micrometers) and low dose (<0.5 Gy) regions. The survivability profiles of the neurons were different in the mouse strains and ions. In this report, a result of memory and learning function to adult mice after whole-body and brain local irradiation at carbon ion and iron ion.

NASA Discipline Radiation Health↗
NASA NTRSDate not supplied

A Neural Network Parametrization of Volumetric Cloud Fraction Profiles Using Satellite Observations and MERRA-2 Reanalysis Meteorological Data

Clouds play a crucial role in regulating the hydrologic cycle and Earth's radiative energy budget, yet they are often poorly represented in global climate models (GCMs). This study applies deep machine learning techniques to develop a physical parameterization of volumetric cloud fraction (VCF), the fraction of a 3-D grid volume occupied by clouds using satellite lidar-radar measurements. The neural network (NN) captures the complicated relationships between observed VCF profiles and collocated meteorological variables from MERRA-2 reanalysis data. Our results show that the NN model, particularly a sequence-to-sequence long short-term memory (LSTM) network with a sixfactor loss function, effectively learns the underlying cloud physical processes. The NN model outperforms MERRA-2 reanalysis in representing low-level clouds in tropical and subtropical regions and low- and middle-level clouds over midlatitude storm-track regions, and also improves VCF histograms. These improvements are reflected in the vertical distributions of zonally, meridionally, and globally averaged VCFs, geographic distributions of low-, middle-, and high-level clouds, and seasonal variations in monthly-mean VCF. Furthermore, the NN predictions effectively capture the El Niño-Southern Oscillation (ENSO) effects and other interannual variations. The NN parameterization is further evaluated through a sensitivity analysis, in which a single predictor is perturbed at a time. This reveals that relative humidity (RH) is the dominant factor influencing variations in globally averaged VCF at low and middle altitudes, followed by temperature. At higher altitudes, temperature becomes the primary driver of VCF through its effect on RH. Changes in wind components had minimal impact on globally averaged VCF.

Shan Zeng↗
DOE OSTI2020

Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning

It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational footprints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.

Drgona, Jan↗
NASA NTRS2008

Miniature High-Force, Long-Stroke SMA Linear Actuators

Improved long-stroke shape-memory-alloy (SMA) linear actuators are being developed to exert significantly higher forces and operate at higher activation temperatures than do prior SMA actuators. In these actuators, long linear strokes are achieved through the principle of displacement multiplication, according to which there are multiple stages, each intermediate stage being connected by straight SMA wire segments to the next stage so that relative motions of stages are additive toward the final stage, which is the output stage. Prior SMA actuators typically include polymer housings or shells, steel or aluminum stages, and polymer pads between successive stages of displacement-multiplication assemblies. Typical output forces of prior SMA actuators range from 10 to 20 N, and typical strokes range from 0.5 to 1.5 cm. An important disadvantage of prior SMA wire actuators is relatively low cycle speed, which is related to actuation temperature as follows: The SMA wires in prior SMA actuators are typically made of a durable nickel/titanium alloy that has a shape-memory activation temperature of 80 C. An SMA wire can be heated quickly from below to above its activation temperature to obtain a stroke in one direction, but must then be allowed to cool to somewhat below its activation temperature (typically, less than or equal to 60 C in the case of an activation temperature of 80 C) to obtain a stroke in the opposite direction (return stroke). At typical ambient temperatures, cooling times are of the order of several seconds. Cooling times thus limit cycle speeds. Wires made of SMA alloys having significantly higher activation temperatures [denoted ultra-high-temperature (UHT) SMA alloys] cool to the required lower return-stroke temperatures more rapidly, making it possible to increase cycle speeds. The present development is motivated by a need, in some applications (especially aeronautical and space-flight applications) for SMA actuators that exert higher forces, operate at greater cycle speeds, and have stronger housings that can withstand greater externally applied forces and impacts. The main novel features of the improved SMA actuators are the following: 1) The ends of the wires are anchored in compact crimps made from short steel tubes. Each wire end is inserted in a tube, the tube is flattened between planar jaws to make the tube grip the wire, the tube is compressed to a slight U-cross-section deformation to strengthen the grip, then the crimp is welded onto one of the actuator stages. The pull strength of a typical crimp is about 125 N -- comparable to the strength of the SMA wire and greater than the typical pull strengths of wire-end anchors in prior SMA actuators. Greater pull strength is one of the keys to achievement of higher actuation force; 2) For greater strength and resistance to impacts, housings are milled from aluminum instead of being made from polymers. Each housing is made from two pieces in a clamshell configuration. The pieces are anodized to reduce sliding friction; 3) Stages are made stronger (to bear greater compression loads without excessive flexing) by making them from steel sheets thicker than those used in prior SMA actuators. The stages contain recessed pockets to accommodate the crimps. Recessing the pockets helps to keep overall dimensions as small as possible; and, 4) UHT SMA wires are used to satisfy the higher-speed/higher-temperature requirement.

Cummin, Mark A.↗
NASA NTRS1976

Digital correlation detector for low-cost Omega navigation

Techniques to lower the cost of using the Omega global navigation network with phase-locked loops (PLL) were developed. The technique that was accepted as being "optimal" is called the memory-aided phase-locked loop (MAPLL) since it allows operation on all eight Omega time slots with one PLL through the implementation of a random access memory. The receiver front-end and the signals that it transmits to the PLL were first described. A brief statistical analysis of these signals was then made to allow a rough comparison between the front-end presented in this work and a commercially available front-end to be made. The hardware and theory of application of the MAPLL were described, ending with an analysis of data taken with the MAPLL. Some conclusions and recommendations were also given.

Chamberlin, K. A.↗
DOE OSTI2015

Investigations on the electronic, structural, magnetic properties related to shape-memory behavior in Ti{sub 2}CoX (X=Al, Ga, In)

Highlights: • The analysis of phase stability trend is studied for Ti{sub 2}CoX(X = Al, Ga, In). • Ti{sub 2}CoGa is more suitable as shape memory alloy. • Total magnetic moments disappear with a increase of c/a ratio for all systems. • Density of states at the Fermi level are also shown. - Abstract: Using the full-potential local orbital minimum-basis method, we have performed a systematic investigations on the electronic, structural, and magnetic properties related to shape memory applications for Ti{sub 2}CoX (X=Al, Ga, In) alloys. Our results confirm that these alloys are half-metallic ferromagnets with total magnetic moment of 2μ{sub B} per formula unit in austenite phase, and undergo a martensitic transformation at low temperatures. The relative stabilities of the martensitic phases differ considerably between Ti{sub 2}CoX (X=Al, Ga, In). Details of the electronic structures suggest that the differences in hybridizations between the magnetic components are responsible for trends of phase. Quantitative estimates for the energetics and the magnetizations indicate that Ti{sub 2}CoGa is a promising candidate for shape memory applications.

36 MATERIALS SCIENCE↗