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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Study on advanced information processing system

Issues related to the reliability of a redundant system with large main memory are addressed. In particular, the Fault-Tolerant Processor (FTP) for Advanced Launch System (ALS) is used as a basis for our presentation. When the system is free of latent faults, the probability of system crash due to nearly-coincident channel faults is shown to be insignificant even when the outputs of computing channels are infrequently voted on. In particular, using channel error maskers (CEMs) is shown to improve reliability more effectively than increasing the number of channels for applications with long mission times. Even without using a voter, most memory errors can be immediately corrected by CEMs implemented with conventional coding techniques. In addition to their ability to enhance system reliability, CEMs--with a low hardware overhead--can be used to reduce not only the need of memory realignment, but also the time required to realign channel memories in case, albeit rare, such a need arises. Using CEMs, we have developed two schemes, called Scheme 1 and Scheme 2, to solve the memory realignment problem. In both schemes, most errors are corrected by CEMs, and the remaining errors are masked by a voter.

Shin, Kang G.↗
DOE OSTI2024

Towards dynamical low-rank approximation for neutrino kinetic equations. Part I: Analysis of an idealized relaxation model

Dynamical low-rank approximation (DLRA) is an emerging tool for reducing computational costs and provides memory savings when solving high-dimensional problems. Here, in this work, we propose and analyze a semi-implicit dynamical low-rank discontinuous Galerkin (DLR-DG) method for the space homogeneous kinetic equation with a relaxation operator, modeling the emission and absorption of particles by a background medium. Both DLRA and the discontinuous Galerkin (DG) scheme can be formulated as Galerkin equations. To ensure their consistency, a weighted DLRA is introduced so that the resulting DLR-DG solution is a solution to the fully discrete DG scheme in a subspace of the standard DG solution space. Similar to the standard DG method, we show that the proposed DLR-DG method is well-posed. We also identify conditions such that the DLR-DG solution converges to the equilibrium. Numerical results are presented to demonstrate the theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

EqualWrites: Reducing Intra-set Write Variations for Enhancing Lifetime of Non-volatile Caches

Driven by the trends of increasing core-count and bandwidth-wall problem, the size of last level caches (LLCs) has greatly increased and hence, the researchers have explored non-volatile memories (NVMs) which provide high density and consume low-leakage power. Since NVMs have low write-endurance and the existing cache management policies are write variation-unaware, effective wear-leveling techniques are required for achieving reasonable cache lifetimes using NVMs. We present EqualWrites, a technique for mitigating intra-set write variation. In this paper, our technique works by recording the number of writes on a block and changing the cache-block location of a hot data-item to redirect the future writes to a cold block to achieve wear-leveling. Simulation experiments have been performed using an x86-64 simulator and benchmarks from SPEC06 and HPC (high-performance computing) field. The results show that for single, dual and quad-core system configurations, EqualWrites improves cache lifetime by 6.31X, 8.74X and 10.54X, respectively. In addition, its implementation overhead is very small and it provides larger improvement in lifetime than three other intra-set wear-leveling techniques and a cache replacement policy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Applications of cold hibernated elastic memory (CHEM) structures

Experiments and analyses have confirmed the feasibility of an innovative, new class of very simple, reliable, low mass, low packaging volume, and low-cost self-deployable structures for space and commercial applications.

shape memory polymers open cellular structures exp↗
DOE OSTI2021

In situ Parallel Training of Analog Neural Network Using Electrochemical Random-Access Memory

In-memory computing based on non-volatile resistive memory can significantly improve the energy efficiency of artificial neural networks. However, accurate in situ training has been challenging due to the nonlinear and stochastic switching of the resistive memory elements. One promising analog memory is the electrochemical random-access memory (ECRAM), also known as the redox transistor. Its low write currents and linear switching properties across hundreds of analog states enable accurate and massively parallel updates of a full crossbar array, which yield rapid and energy-efficient training. While simulations predict that ECRAM based neural networks achieve high training accuracy at significantly higher energy efficiency than digital implementations, these predictions have not been experimentally achieved. In this work, we train a 3 × 3 array of ECRAM devices that learns to discriminate several elementary logic gates (AND, OR, NAND). We record the evolution of the network’s synaptic weights during parallel in situ (on-line) training, with outer product updates. Due to linear and reproducible device switching characteristics, our crossbar simulations not only accurately simulate the epochs to convergence, but also quantitatively capture the evolution of weights in individual devices. The implementation of the first in situ parallel training together with strong agreement with simulation results provides a significant advance toward developing ECRAM into larger crossbar arrays for artificial neural network accelerators, which could enable orders of magnitude improvements in energy efficiency of deep neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Manipulation of magnetostructural transition and realization of prominent multifunctional magnetoresponsive properties in NiCoMnIn alloys

Promising multifunctional magnetoresponsive effects such as magnetoresistance, magnetostrain, and the magnetocaloric effect have recently been extensively studied in Ni-Mn-based metamagnetic shape memory alloys, but large reversible magnetoresponsive effects are usually obtained under high magnetic fields, which is an obstacle for practical applications. In this work, through manipulating magnetostructural transition, we achieved large reversible magnetoresponsive effects under a relatively low magnetic field of 3 T in a Ni-Co-Mn-In alloy. By systematically tuning the Mn/In ratio and Co substitution, an optimum composition Ni 49 Co 3 Mn 34 In 14 with a low thermal hysteresis (8 K), a narrow transformation interval (7 K) and a high sensitivity of transformation temperature to field change (6KT -1 ), was obtained. Good geometric compatibility between austenite and martensite was revealed by in situ synchrotron high-energy x-ray diffraction experiment, which accounts for the low hysteresis and narrow transformation interval. A reversible transformation between pure austenite and pure martensite is induced by a relatively low field of 3 T, which was directly evidenced by in situ neutron diffraction experiments. As a result, a large reversible magnetocaloric effect with entropy change of 16.5Jkg -1 K -1 , a large reversible magnetostrain of 0.26%, and a large reversible magnetoresistance of 60%, under a relatively low field of 3 T, were simultaneously achieved. These reversible magnetoresponsive effects are comparable to the maximum reversible values obtained under high fields in other Ni-Mn-based alloys, but the magnetic field we applied is much lower. This research may guide the design of metamagnetic shape memory alloys with low-field-induced magnetoresponsive properties for magnetic refrigeration, magnetic sensing, and magnetic recording applications.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Optically Addressable, Ferroelectric Memory With NDRO

For readout, memory cells addressed via on-chip semiconductor lasers. Proposed thin-film ferroelectric memory device features nonvolatile storage, optically addressable, nondestructive readout (NDRO) with fast access, and low vulnerability to damage by ionizing radiation. Polarization switched during recording and erasure, but not during readout. As result, readout would not destroy contents of memory, and operating life in specific "read-intensive" applications increased up to estimated 10 to the 16th power cycles.

Thakoor, Sarita↗
NASA NTRS2018

A Study of Shape Memory Polymer Based Slat-Cove Filler

Aircraft noise reduction is an application of current intense interest for which smart materials show significant potential. Specifically, the aeroacoustic noise produced by the unsteady aerodynamic flow about the leading-edge high-lift device, such as leading-edge slat, of typical transport-aircraft wings is of particular interest. Concepts with the most promise to mitigate this noise source, most notably the slat-cove filler concept, have focused on highly reconfigurable structures that change shape between different phases of the flight envelope. These shape changes often involve large deformation, which has stimulated the consideration of shape memory materials. In recent years, shape memory materials (SMMs) have drawn greater interest for applications such as smart fabrics, intelligent medical devices, self-deployable space structures, morphing structures and packaging. Compared to other shape memory materials, like shape memory alloys (SMAs) or shape memory ceramics (SMCs), shape memory polymers (SMPs) have desirable advantages such as high elastic deformation to enable large shape change, broad tailorability of mechanical properties, potential biocompatibility and biodegradability, ductility, light weight and ease of processing. However, SMPs still have some critical disadvantages such as insufficient mechanical and thermal characteristics for structural applications, low recovery stress, and long response time. The new LaRC shape memory thermosetting polymer composite (LaRC-SMPC) discussed herein was synthesized with nontoxic monomers and conductive/magnetic fillers to yield enhanced thermal/mechanical characteristics and faster response times. LaRC-SMPCs with a variety of fiber reinforcements [Kevlar®, carbon fiber (standard and thin-ply), and carbon-nanotube (CNT) sheet] were fabricated to tailor the physical properties and test for suitability as a slat-cove filler (SCF). The performance of SCF prototypes fabricated with the developed LaRC-SMPCs was evaluated using a bench-top test apparatus. The SCFs made of Kevlar® fiber fabric or carbon fiber fabric infused shape memory polymer composite (SMPC) exhibited kinking during simulated deployment and stowage, which can be problematic during operation. The SCF made of CNT sheet/SMP composite did not exhibit kinking, but the deployment was sluggish compared to carbon fiber fabric/SMP composite. This report documents the evolution of designing SMPCs as slat-cove fillers for aircraft noise reduction. In the course of the investigation, several 2 approaches were investigated to address shortcomings in material characteristics based on performance requirements of operational slat-cove fillers.

Kang, Jin Ho↗
DOE OSTI2018

Cancer epidemiology update, following the 2011 IARC evaluation of radiofrequency electromagnetic fields (Monograph 102)

Highlights: • Increased risk of brain, vestibular nerve and salivary gland tumors are associated with mobile phone use. • Nine studies (2011–2017) report increased risk of brain cancer from mobile phone use. • Four case-control studies (3 in 2013, 1 in 2014) report increased risk of vestibular nerve tumors. • Concern for other cancers: breast (male & female), testis, leukemia, and thyroid. • Based on the evidence reviewed it is our opinion that IARC's current categorization of RFR as a possible human carcinogen (Group 2B) should be upgraded to Carcinogenic to Humans (Group 1). Epidemiology studies (case-control, cohort, time trend and case studies) published since the International Agency for Research on Cancer (IARC) 2011 categorization of radiofrequency radiation (RFR) from mobile phones and other wireless devices as a possible human carcinogen (Group 2B) are reviewed and summarized. Glioma is an important human cancer found to be associated with RFR in 9 case-control studies conducted in Sweden and France, as well as in some other countries. Increasing glioma incidence trends have been reported in the UK and other countries. Non-malignant endpoints linked include acoustic neuroma (vestibular Schwannoma) and meningioma. Because they allow more detailed consideration of exposure, case-control studies can be superior to cohort studies or other methods in evaluating potential risks for brain cancer. When considered with recent animal experimental evidence, the recent epidemiological studies strengthen and support the conclusion that RFR should be categorized as carcinogenic to humans (IARC Group 1). Opportunistic epidemiological studies are proposed that can be carried out through cross-sectional analyses of high, medium, and low mobile phone users with respect to hearing, vision, memory, reaction time, and other indicators that can easily be assessed through standardized computer-based tests. As exposure data are not uniformly available, billing records should be used whenever available to corroborate reported exposures.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2016

Combining Pre- and Post-Nucleation Trajectories for the Synthesis of High FAU-Content Faujasite Nanocrystals from Organic-Free Sols

The effects of synthesis conditions on the FAU/EMT content and the size of nanocrystals, formed from inorganic aluminosilicate sols, were investigated. High resolution transmission electron microscopy imaging and comparison of experimental X-ray diffraction patterns with simulations demonstrated that all materials made starting from synthesis mixtures in the composition range (1.8-33) SiO2: 1 Al2O3: (2.7-33) Na2O: (41-1000) H2O contain FAU/EMT intergrowths. Compositions with low water content increase the FAU fraction up to 0.8 but the crystal size exceeds 100 nm. Extension of the higher FAU purity to nanocrystals was achieved only by first mixing the sol at high water content compositions that favor nanocrystal formation and then - after a certain time - lowering by freeze-drying the water to levels favoring the formation of FAU. Cryogenic transmission electron microscopy and small angle X-ray scattering from representative optically clear and colloidally stable precursor sols (aged and crystallized at ambient temperature) reveal the formation of amorphous aggregates before the detection of crystals, in agreement with earlier findings and an existing model for the aggregative growth of the zeolite MFI. The presence of these amorphous aggregates coincides with the aforementioned state of sol that preserves the original trajectory towards nano-crystals after the pronounced reduction of water content by freeze-drying. If water reduction by freeze-drying is applied earlier (before the detection of amorphous aggregates), the sol follows the low water content trajectory towards larger crystals. Despite this memory effect, the sol at this stage is still agnostic towards FAU or EMT formation, the relative content of which is dominantly determined by the final water content. These findings demonstrate that it is possible to combine the effects of pre-and post-nucleation sol composition to steer crystal size and crystal structure, respectively. They confirm precursor nanoparticle evolution, while they emphasize the importance of solution phase composition at both pre- and post-nucleation stages of aggregative crystal growth.

Khaleel, Maryam↗
DOE OSTI2025

Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance

The combination of machine learning (ML) models with chemistry-related tasks requires the description of molecular structures in a machine-readable way. The nature of these so-called molecular descriptors has a direct and major impact on the performance of ML models and remains an open problem in the field. Structural descriptors like SMILES strings or molecular graphs lack size-independence and can be memory intensive. Machine-learned descriptors can be of low dimensionality and constant size but lack physical significance and human interpretability. Sigma profiles, which are unnormalized histograms of the surface charge distributions of solvated molecules, combine physical significance with low dimensionality and size-independence, making them a suitable candidate for a universal molecular descriptor. However, their widespread adoption in ML applications requires open access to sigma profile generation, which is currently not available. This work details the development of OpenSPGen – an open-source tool for generating sigma profiles. Also presented are studies on the effect of different settings on the efficacy of the generated sigma profiles at predicting thermophysical material properties when used as inputs to a Gaussian process as a simple surrogate ML model. We find that a higher level of theory does not translate to more accurate results. We also provide further recommendations for sigma profile calculation and use in ML models.

Salih, Fathya Y. M. [University of Notre Dame, IN ↗
DOE OSTI2014

Percolation conductivity in hafnium sub-oxides

In this study, we demonstrated experimentally that formation of chains and islands of oxygen vacancies in hafnium sub-oxides (HfO{sub x}, x < 2) leads to percolation charge transport in such dielectrics. Basing on the model of Éfros-Shklovskii percolation theory, good quantitative agreement between the experimental and theoretical data of current-voltage characteristics was achieved. Based on the percolation theory suggested model shows that hafnium sub-oxides consist of mixtures of metallic Hf nanoscale clusters of 1–2 nm distributed onto non-stoichiometric HfO{sub x}. It was shown that reported approach might describe low resistance state current-voltage characteristics of resistive memory elements based on HfO{sub x}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Optically sensitive devices based on Pt nano particles fabricated by atomic layer deposition and embedded in a dielectric stack

We report a series of metal insulator semiconductor devices with embedded Pt nano particles (NPs) fabricated using a low temperature atomic layer deposition process. Optically sensitive nonvolatile memory cells as well as optical sensors: (i) varactors, whose capacitance-voltage characteristics, nonlinearity, and peak capacitance are strongly dependent on illumination intensity; (ii) highly linear photo detectors whose responsivity is enhanced due to the Pt NPs. Both single devices and back to back pairs of diodes were used. The different configurations enable a variety of functionalities with many potential applications in biomedical sensing, environmental surveying, simple imagers for consumer electronics and military uses. The simplicity and planar configuration of the proposed devices makes them suitable for standard CMOS fabrication technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ferroelectric behavior of sputter deposited Al 0.72 Sc 0.28 N approaching 5 nm thickness

Ferroelectric Al 1-x Sc x N has raised much interest in recent years due to its unique ferroelectric properties and complementary metal oxide semiconductor back-end-of-line compatible processing temperatures. Potential applications in embedded nonvolatile memory, however, require ferroelectric materials to switch at relatively low voltages. One approach to achieving a lower switching voltage is to significantly reduce the Al 1-x Sc x N thickness. In this work, ferroelectric behavior in 5-27 nm films of sputter deposited Al 0.72 Sc 0.28 N has been studied. We find that the 10 kHz normalized coercive field increases from 4.4 to 7.3 MV/cm when reducing the film thickness from 27.1 to 5.4 nm, while over the same thickness range, the characteristic breakdown field of a 12.5 μm radius capacitor increases from 8.3 to 12.1 MV/cm. In conclusion, the 5.4 nm film demonstrates ferroelectric switching at 5.5 V when excited with a 500 ns pulse and a switching speed of 60 ns.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Deep melting reveals liquid structural memory and anomalous ferromagnetism in bismuth

As an archetypal semimetal with complex and anisotropic Fermi surface and unusual electric properties (e.g., high electrical resistance, large magnetoresistance, and giant Hall effect), bismuth (Bi) has played a critical role in metal physics. In general, Bi displays diamagnetism with a high volumetric susceptibility (~10 -4 ). Here in this paper, we report unusual ferromagnetism in bulk Bi samples recovered from a molten state at pressures of 1.4–2.5 GPa and temperatures above ~1,250 K. The ferromagnetism is associated with a surprising structural memory effect in the molten state. On heating, low-temperature Bi liquid (L) transforms to a more randomly disordered high-temperature liquid (L') around 1,250 K. By cooling from above 1,250 K, certain structural characteristics of liquid L' are preserved in L. Bi clusters with characteristics of the liquid L' motifs are further preserved through solidification into the Bi-II phase across the pressure-independent melting curve, which may be responsible for the observed ferromagnetism.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep learning of accurate force field of ferroelectric HfO 2

The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗