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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Deformation and Failure Mechanisms of Shape Memory Alloys

The goal of this research was to understand the fundamental mechanics that drive the deformation and failure of shape memory alloys (SMAs). SMAs are difficult materials to characterize because of the complex phase transformations that give rise to their unique properties, including shape memory and superelasticity. These phase transformations occur across multiple length scales (one example being the martensite-austenite twinning that underlies macroscopic strain localization) and result in a large hysteresis. In order to optimize the use of this hysteretic behavior in energy storage and damping applications, we must first have a quantitative understanding of this transformation behavior. Prior results on shape memory alloys have been largely qualitative (i.e., mapping phase transformations through cracked oxide coatings or surface morphology). The PI developed and utilized new approaches to provide a quantitative, full-field characterization of phase transformation, conducting a comprehensive suite of experiments across multiple length scales and tying these results to theoretical and computational analysis. The research funded by this award utilized new combinations of scanning electron microscopy, diffraction, digital image correlation, and custom testing equipment and procedures to study phase transformation processes at a wide range of length scales, with a focus at small length scales with spatial resolution on the order of 1 nanometer. These experiments probe the basic connections between length scales during phase transformation. In addition to the insights gained on the fundamental mechanisms driving transformations in shape memory alloys, the unique experimental methodologies developed under this award are applicable to a wide range of solid-to-solid phase transformations and other strain localization mechanisms.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Plasma membrane ordering agent pluronic F-68 (PF-68) reduces neurotransmitter uptake and release and produces learning and memory deficits in rats

A substantial body of evidence indicates that aged-related changes in the fluidity and lipid composition of the plasma membrane contribute to cellular dysfunction in humans and other mammalian species. In the CNS, reductions in neuronal plasma membrane order (PMO) (i.e., increased plasma membrane fluidity) have been attributed to age as well as the presence of the beta-amyloid peptide-25-35, known to play an important role in the neuropathology of Alzheimer's disease (AD). These PMO increases may influence neurotransmitter synthesis, receptor binding, and second messenger systems as well as signal transduction pathways. The effects of neuronal PMO on learning and memory processes have not been adequately investigated, however. Based on the hypothesis that an increase in PMO may alter a number of aspects of synaptic transmission, we investigated several neurochemical and behavioral effects of the membrane ordering agent, PF-68. In cell culture, PF-68 (nmoles/mg SDS extractable protein) reduced [3H]norepinephrine (NE) uptake into differentiated PC-12 cells as well as reduced nicotine stimulated [3H]NE release. The compound (800-2400 microg/kg, i.p., resulting in nmoles/mg SDS extractable protein in the brain) decreased step-through latencies and increased the frequencies of crossing into the unsafe side of the chamber in inhibitory avoidance training. In the Morris water maze, PF-68 increased the latencies and swim distances required to locate a hidden platform and reduced the time spent and distance swam in the previous target quadrant during transfer (probe) trials. PF-68 did not impair performance of a well-learned working memory task, the rat delayed stimulus discrimination task (DSDT), however. Studies with 14C-labeled PF-68 indicated that significant (pmoles/mg wet tissue) levels of the compound entered the brain from peripheral (i.p.) injection. No PF-68 related changes were observed in swim speeds or in visual acuity tests in water maze experiments, rotorod performance, or in tests of general locomotor activity. Furthermore, latencies to select a lever in the DSDT were not affected. These results suggest that PF-68 induced deficits in learning and memory without confounding peripheral motor, sensory, or motivational effects at the tested doses. Furthermore, none of the doses induced a conditioned taste aversion to a novel 0.1% saccharin solution indicating a lack of nausea or gastrointestinal malaise induced by the compound. The data indicate that increases in neuronal plasma membrane order may have significant effects on neurotransmitter function as well as learning and memory processes. Furthermore, compounds such as PF-68 may also offer novel tools for studying the role of neuronal PMO in mnemonic processes and changes in PMO resulting from age-related disorders such as AD.

Poloxamer/pharmacology↗
NASA NTRS2012

Non Volatile Flash Memory Radiation Tests

Commercial flash memory industry has experienced a fast growth in the recent years, because of their wide spread usage in cell phones, mp3 players and digital cameras. On the other hand, there has been increased interest in the use of high density commercial nonvolatile flash memories in space because of ever increasing data requirements and strict power requirements. Because of flash memories complex structure; they cannot be treated as just simple memories in regards to testing and analysis. It becomes quite challenging to determine how they will respond in radiation environments.

single event upset results↗
NASA NTRS2022

Non-Volatile, Low Power, and High Density SiC Memory For Future Venus Missions

Long lived memory would transform Venus landers & missions. Venus durable memory demonstrated in earlier HOTTech with impractically high power and low bit capacity. This project seeks to develop and demonstrate the world’s first Venus-durable low power memory device (Non-Volatile Random Access Memory (NVRAM) to enhance extended Venus surface missions.

silicon carbide↗
NASA NTRS2023

Dynamically Rendering Rough Terrain with Minimal Memory Overhead

Rendering highly detailed terrain is a process with the potential to consume a great deal of a computer’s random access memory (RAM). In a browser-based application, this resource is limited even further, leading to the necessity to use alternative methods of rendering the large amount of data needed for high detail. This report describes one such method that places the onus of rendering on the speed of the graphics processing unit (GPU) rather than on the computer’s memory. By removing attribute buffers, which contribute greatly to memory costs, from the rendering pipeline and generating the requisite attributes on the fly using a heightmap texture instead, it is estimated that memory usage can be cut down to one-sixth that of the previous method.

Visualization↗
DOE OSTI2017

Parallel Asynchronous Distributed-Memory Maximal Independent Set Algorithm with Work Ordering

The maximal independent set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of graph data suggests the use of distributed memory hardware as a cost-effective approach to providing necessary compute and memory resources. Existing distributed memory parallel MIS algorithms rely on synchronous communication and use techniques such as subgraph computations. In this paper, we present an asynchronous distributed-memory parallel graph algorithm that relies on a virtual directed acyclic graph (DAG) that is created during the algorithm execution. We introduce two additional algorithms that save computations by ordering generated work. The first algorithm applies ordering globally to reduce computations, and the second algorithm applies ordering locally at the level of threads to minimize the synchronization overhead. We use two different implementations of Luby’s algorithm variants as baseline to compare the performance of the presented algorithms: (1) vertex-centric Luby A and Luby B implementations, and (2) the CombBLAS linear-algebra Luby A implementation. Results show that proposed algorithms outperform both implementations of Luby algorithms, especially in distributed execution. Furthermore, we show that for low-diameter graphs the algorithm that applies global ordering scales better than other algorithms and for high diameter graphs the original asynchronous algorithm and thread-level ordering algorithm show better performance.

maximal independent set (MIS), distributed memory ↗
DOE OSTI2020

UNITY: Unified Memory and Storage Space

UNITY is a 36-month project focused on providing design and evaluate a new distributed storage paradigm that unifies the traditionally distinct application views of memory- and file-based data storage into a single scalable and resilient environment. The project is a collaboration among Oak Ridge National Laboratory (ORNL, Lead institution), Los Alamos National Labs (LANL), and Georgia Tech (GT). The main contributions of the GT team have been around development of low level systems software for best leveraging the capabilities of new types of persistent memory technologies, and for development of methods for intelligent data management across memory/storage substrates with heterogeneous components. GT contributed the Phoenix library for optimized checkpoint/restart for HPC I/O for systems with non-volatile memory (NVM), the NVStream library for NVM-specialized streaming I/O for HPC workflows, the CoMerge, Mnemo and Kleio solutions for intelligent data management on NVM-based systems. These contributions result in significant improvements in both application performance and system efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Memorial Pools Energy Efficiency Retrofits

The National September 11 Memorial & Museum completed a retrofit of the submergible LED lighting fixtures in its North and South Memorial Pools, located at the World Trade Center site in New York City. The two one-acre pools are illuminated nightly by custom LED fixtures set into their base, and the original lights — in place since 2011 — had begun reaching the end of their useful life, leaving sections of the pools dim or dark. Rather than fully replacing the fixtures, the project team worked with the original manufacturer, Acuity Brands, to retrofit and reuse existing components across all eight pool walls (34 fixtures per wall), reducing cost and waste. Fixtures were shipped in custom crates to Minnesota for retrofitting, then reinstalled onsite by Memorial & Museum staff and contractor ABM. The team addressed two key technical challenges during the project: early leakage in retrofitted fixtures, resolved by introducing vacuum-sealing and nitrogen-fill testing before shipment; and chord damage during transit, resolved with custom-designed shipping crates. All eight pool walls were successfully retrofitted and reinstalled by August 27, 2025, ahead of the 25th anniversary of the September 11, 2001 attacks. Sitewide electrical consumption in September 2025 reflected an approximate 7% reduction, contributing to the institution's broader net-zero and LEED Gold sustainability goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Total-Ionizing-Dose Effects on Long-term Data Retention Characteristics of Commercial 3-D NAND Memories

This article evaluates the data retention characteristics of irradiated multi-level cell (MLC) 3-D NAND flash memories. We irradiate the memory chips by a Co-60 gamma-ray source for up to 50 krad(Si) and then write a random data pattern on the irradiated chip to find its retention characteristics. The experimental results show that the data retention property of the irradiated chips is significantly degraded compared to the un-irradiated ones. We evaluate two independent strategies to improve the data retention characteristics of the irradiated chips. Furthermore, the first method involves high-temperature annealing of the irradiated chip while the second method suggests pre-programming the memory modules before deploying them in radiation-prone environments.

3-D NAND flash↗
DOE OSTI2022

Optical Memory, Switching, and Neuromorphic Functionality in Metal Halide Perovskite Materials and Devices

Metal halide perovskite-based materials have emerged over the past few decades as remarkable solution-processable opto-electronic materials with many intriguing properties and potential applications. Notably, these emerging materials have recently been considered for their promise in low-energy memory and information processing applications. In particular, their large optical cross-sections, high photoconductance contrast, large carrier diffusion lengths, and mixed electronic/ionic transport mechanisms are attractive for enabling memory elements and neuromorphic devices that are written and/or read in the optical domain. Here, we review recent progress towards memory and neuromorphic functionality in metal halide perovskite materials and devices where photons are used as a critical degree of freedom for switching, memory, and neuromorphic functionality.

14 SOLAR ENERGY↗
DOE OSTI2022

Nonvolatile Electrochemical Random‐Access Memory under Short Circuit

Abstract Electrochemical random‐access memory (ECRAM) is a recently developed and highly promising analog resistive memory element for in‐memory computing. One longstanding challenge of ECRAM is attaining retention time beyond a few hours. This short retention has precluded ECRAM from being considered for inference classification in deep neural networks, which is likely the largest opportunity for in‐memory computing. In this work, an ECRAM cell with orders of magnitude longer retention than previously achieved is developed, and which is anticipated to exceed ten years at 85 °C. This study hypothesizes that the origin of this exceptional retention is phase separation, which enables the formation of multiple effectively equilibrium resistance states. This work highlights the promises and opportunities to use phase separation to yield ECRAM cells with exceptionally long, and potentially permanent, retention times.

Kim, Diana S.↗
DOE OSTI2024

From shockwaves to the gravitational memory effect

We study the relationship between shockwave geometries and the gravitational memory effect in four-dimensional asymptotically flat spacetime. In particular, we show the ’t Hooft commutation relations of shockwave operators are equivalent to the commutation relation between soft and Goldstone modes parametrizing a sector of the gravitational phase space. We demonstrate this equivalence via a diffeomorphism that takes a shockwave metric to a metric whose transverse traceless component is the gravitational memory. The shockwave momentum in ’t Hooft’s analysis is related to the soft graviton mode, which is responsible for the memory effect, while the shift in the shockwave position is related to the Goldstone mode. This equivalence opens new directions to utilize the gravitational memory effect to explore the observational implications of shockwave geometries in flat space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Disrupting nNOS-PSD-95 coupling in the hippocampal dentate gyrus promotes extinction memory retrieval

Granule cells in the dentate gyrus regenerate constantly in adult hippocampus and then integrate into neural circuits in the hippocampus thereby providing the neural basis for learning and memory. Promoting the neurogenesis in the hippocampus facilitates learning and memory such as spatial learning, object identification, and extinction learning. The interaction between neuronal nitric oxide synthase (nNOS) and postsynaptic density protein-95 (PSD-95) is reported to negatively regulate neurogenesis in brain, so we hypothesized that disrupting this interaction might facilitate the neurogenesis in the dentate gyrus (DG) and thus enhance the extinction memory retrieval of fear learning. We found that uncoupling the nNOS-PSD-95 complex in remote contextual fear condition promoted both neuronal proliferation and survival in the DG, contributing to an enhanced retrieval of the extinction memory. Moreover, the nNOS-PSD-95 uncoupling-induced neurogenesis may be mediated by the extracellular signal-regulated kinase (ERK) as the phosphorylation level of ERK1/2 was increased after uncoupling. These findings suggest that the nNOS-PSD-95 complex may serve as a novel target for the treatment of post-traumatic stress disorder (PTSD). - Highlights: • nNOS-PSD-95 disruption promoted neurogenesis in the DG. • Delayed disruption of nNOS-PSD-95 still enhanced remote contextual fear extinction. • The enhancement of fear extinction relied on neuronal proliferation. • nNOS-PSD-95 disruption increased ERK1/2 phosphorylation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Sirtuin 7 is involved in the consolidation of fear memory in mice

Highlights: • SIRT7 is involved in many biological processes. • The functional role of SIRT7 in the brain is unknown. • We demonstrate that SIRT7 is expressed in the amygdala and hippocampus. • Fear memory consolidation was impaired in Sirt7 knockout mice. • SIRT7 is involved in the consolidation of fear memory. Sirtuin 7 (SIRT7) is an NAD{sup +}-dependent deacetylase/deacylase, and is involved in a variety of biological processes relevant to the transcription of rRNA, the DNA damage response, tumorigenesis, and metabolism. SIRT7 mRNA is expressed ubiquitously, including in the brain, but there is no detailed information about the anatomical distribution and functional role of SIRT7 in the brain. Here, we demonstrated that SIRT7 is widely expressed in the mouse brain, including in the cortex, striatum, thalamus, hippocampus, and amygdala. Behavioral examinations revealed that Sirt7 knockout (KO) and control mice showed similar levels of freezing behavior immediately after a fear response, but a significant decrease of freezing behavior at 24 h after fear conditioning was observed in Sirt7 KO mice. Histological analysis revealed that there is no apparent structural abnormality of the amygdala and hippocampus, which are regions involved in fear memory consolidation, in Sirt7 KO mice. Our results indicate that SIRT7 is involved in the consolidation of fear memory.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Attenuation of zinc-enhanced inflammatory M1 phenotype of microglia by peridinin protects against short-term spatial-memory impairment following cerebral ischemia in mice

Highlights: • Peridinin suppressed zinc-enhanced inflammatory M1 phenotype of microglia. • Zinc-increased microglial ROS level was abolished by peridinin. • Peridinin protected mice from ischemia-induced deficits in short-term spatial memory. Activated microglia exhibit two opposite activation states, the inflammatory M1 and the anti-inflammatory M2 activation states. In the mammalian brain, ischemia elicits a massive release of zinc from hippocampal neurons, and the extracellular zinc primes M1 microglia—by inducing reactive oxygen species (ROS) generation—to enhance their production of proinflammatory cytokines, which ultimately results in short-term spatial memory impairment. Here, we examined how peridinin, a carotenoid in dinoflagellates, affects the zinc-enhanced inflammatory M1 phenotype of microglia. Treatment of microglia with 30–300 ng/mL peridinin caused a dose-dependent attenuation of zinc-enhanced interleukin (IL)-1β, IL-6, and tumor necrosis factor-α (TNFα) secretion when M1 activation was induced by lipopolysaccharide exposure. Moreover, peridinin inhibited the increase in ROS levels in zinc-treated microglia without directly interacting with zinc. Notably, when mice were administrated peridinin (20–200 ng/animal) intracerebroventricularly 5 min before cerebral ischemia-reperfusion, the peridinin treatment not only suppressed the increase in expression of IL-1β, IL-6, TNFα, and the microglial M1 surface marker CD16/32, but also protected the mice against ischemia-induced short-term spatial-memory impairment. Our findings suggest that peridinin prevents extracellular zinc-enhanced proinflammatory cytokine secretion from M1 microglia by inhibiting the increase in microglial ROS levels, and that this anti-inflammatory effect of peridinin might result in protection against deficits in short-term spatial memory.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Speeding up and reducing memory usage for scientific machine learning via mixed precision

Scientific machine learning (SciML) has emerged as a versatile approach to address complex computational science and engineering problems. Within this field, physics-informed neural networks (PINNs) and deep operator networks (DeepONets) stand out as the leading techniques for solving partial differential equations by incorporating both physical equations and experimental data. However, training PINNs and DeepONets require significant computational resources, including long computational times and large amounts of memory. In search of computational efficiency, training neural networks using half precision (float16) rather than the conventional single (float32) or double (float64) precision has gained substantial interest, given the inherent benefits of reduced computational time and memory consumed. However, we find that float16 cannot be applied to SciML methods, because of gradient divergence at the start of training, weight updates going to zero, and the inability to converge to a local minima. To overcome these limitations, we explore mixed precision, which is an approach that combines the float16 and float32 numerical formats to reduce memory usage and increase computational speed. Our experiments showcase that mixed precision training not only substantially decreases training times and memory demands but also maintains model accuracy. Here, we also reinforce our empirical observations with a theoretical analysis. The research has broad implications for SciML in various computational applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Kokkos: Enabling manycore performance portability through polymorphic memory access patterns

The manycore revolution can be characterized by increasing thread counts, decreasing memory per thread, and diversity of continually evolving manycore architectures. High performance computing (HPC) applications and libraries must exploit increasingly finer levels of parallelism within their codes to sustain scalability on these devices. We found that a major obstacle to performance portability is the diverse and conflicting set of constraints on memory access patterns across devices. Contemporary portable programming models address manycore parallelism (e.g., OpenMP, OpenACC, OpenCL) but fail to address memory access patterns. The Kokkos C++ library enables applications and domain libraries to achieve performance portability on diverse manycore architectures by unifying abstractions for both fine-grain data parallelism and memory access patterns. In this paper we describe Kokkos’ abstractions, summarize its application programmer interface (API), present performance results for unit-test kernels and mini-applications, and outline an incremental strategy for migrating legacy C++ codes to Kokkos. Furthermore, the Kokkos library is under active research and development to incorporate capabilities from new generations of manycore architectures, and to address a growing list of applications and domain libraries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗