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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Magnetic force microscopy revealing long-range room temperature stable molecule bridge-induced magnetic ordering on magnetic tunnel junction (MTJ) pillars

Magnetic tunnel junctions (MTJs) can integrate novel single molecular device elements to overcome long-standing fabrication challenges, thus unlocking their novel potential. This study employs magnetic force microscopy (MFM) to demonstrate that organometallic molecules, when placed between two ferromagnetic electrodes along cross-junction shaped MTJ edges, dramatically altered the magnetic properties of the electrodes, affecting areas several hundred microns in size around the molecular junction vicinity at room temperature. These findings are supported by magnetic resonance and magnetometer studies on ∼7000 MTJ pillars. MFM on the pillar sample showed an almost complete disappearance of the magnetic contrast. The spatial magnetic image suggests that molecular channels significantly impacted the spin density of states in the ferromagnetic electrodes. This advancement in MTJ-based molecular devices paves the way for a new generation of commercially viable logic and memory devices controlled by molecular quantum states at near-room temperatures.

Tyagi, Pawan (ORCID:0000000275411344)↗
NASA NTRS2010

Nonvolatile Memory Technology for Space Applications

This slide presentation reviews several forms of nonvolatile memory for use in space applications. The intent is to: (1) Determine inherent radiation tolerance and sensitivities, (2) Identify challenges for future radiation hardening efforts, (3) Investigate new failure modes and effects, and technology modeling programs. Testing includes total dose, single event (proton, laser, heavy ion), and proton damage (where appropriate). Test vehicles are expected to be a variety of non-volatile memory devices as available including Flash (NAND and NOR), Charge Trap, Nanocrystal Flash, Magnetic Memory (MRAM), Phase Change--Chalcogenide, (CRAM), Ferroelectric (FRAM), CNT, and Resistive RAM.

Oldham, Timothy R.↗
DOE OSTI2026

Magnon confinement in epitaxial antiferromagnetic oxide heterostructures.

Magnons, the quanta of spin waves, have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices. Controlling magnons in conventional antiferromagnets and harnessing them in practical applications, however, remains a challenge. Here, we demonstrate highly efficient magnon transport in a LaFeO3/ BiFeO3/ LaFeO3 all-antiferromagnetic system, which can be controlled electrically, making it highly desirable for energy-efficient computation. Leveraging spin-orbit-driven spin-charge transduction, we demonstrate that this material architecture permits magnon confinement in ultrathin antiferromagnets, enhancing the output voltage generated by magnon transport by several orders of magnitude, which provides a pathway to enable magnetoelectric memory and logic functionalities. Additionally, the non-volatility of output voltage enables ultralowpower logic-in-memory processing, where magnonic devices can be efficiently reconfigured via electrically controlled magnon spin currents within magnetoelectric channels.

Husain, Sajid↗
NASA NTRS1995

Storing Data In Circulating Electrons

Proposed memory device contains electrons traveling in circular orbit in vacuum. Orientations of electron spins (up or down) represents binary ones or zeros, respectively. Assuming length of each memory element 100 times classical fictitious electron radius, device theoretically capable of storing 446 gigabytes of data per meter of circumference of orbit.

Eastman, Ted R.↗
DOE OSTI2025

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nonvolatile electrochemical memory at 600°C enabled by composition phase separation

Silicon-based microelectronics are limited to ~150°C and therefore not suitable for the extremely high temperatures in aerospace, energy, and space applications. While wide-band-gap semiconductors can provide high-temperature logic, nonvolatile memory devices at high temperatures have been challenging. In this work, we develop a nonvolatile electrochemical memory cell that stores and retains analog and digital information at temperatures as high as 600°C. Through correlative scanning transmission electron microscopy, we show that this high-temperature information retention is a result of composition phase separation between the oxidized and reduced forms of amorphous tantalum oxide. This result demonstrates a memory concept that is resilient at extreme temperatures and reveals phase separation as the principal mechanism that enables nonvolatile information storage in these electrochemical memory cells.

42 ENGINEERING↗
DOE OSTI2020

Performance Potential of Mixed Data Management Modes for Heterogeneous Memory Systems

Many high-performance systems now include different types of memory devices within the same compute platform to meet strict performance and cost constraints. Such heterogeneous memory systems often include an upper-level tier with better performance, but limited capacity, and lower-level tiers with higher capacity, but less bandwidth and longer latencies for reads and writes. To utilize the different memory layers efficiently, current systems rely on hardware-directed, memory -side caching or they provide facilities in the operating system (OS) that allow applications to make their own data-tier assignments. Since these data management options each come with their own set of trade-offs, many systems also include mixed data management configurations that allow applications to employ hardware- and software-directed management simultaneously, but for different portions of their address space. Despite the opportunity to address limitations of stand-alone data management options, such mixed management modes are under-utilized in practice, and have not been evaluated in prior studies of complex memory hardware. In this work, we develop custom program profiling, configurations, and policies to study the potential of mixed data management modes to outperform hardware- or software-based management schemes alone. Our experiments, conducted on an Intel ® Knights Landing platform with high-bandwidth memory, demonstrate that the mixed data management mode achieves the same or better performance than the best stand-alone option for five memory intensive benchmark applications (run separately and in isolation), resulting in an average speedup compared to the best stand-alone policy of over 10 %, on average.

Effler, Chad↗
NASA NTRS2007

Radiation Test Challenges for Scaled Commerical Memories

As sub-100nm CMOS technologies gather interest, the radiation effects performance of these technologies provide a significant challenge. In this talk, we shall discuss the radiation testing challenges as related to commercial memory devices. The focus will be on complex test and failure modes emerging in state-of-the-art Flash non-volatile memories (NVMs) and synchronous dynamic random access memories (SDRAMs), which are volatile. Due to their very high bit density, these device types are highly desirable for use in the natural space environment. In this presentation, we shall discuss these devices with emphasis on considerations for test and qualification methods required.

LaBel, Kenneth A.↗
DOE OSTI2026

Spatiotemporal Thermal Coupling in VO 2 Device Arrays

Correlated oxides such as VO 2 exhibit an electrically driven insulator–metal transition (IMT) that underlies their promise for neuromorphic and memory devices. Yet the IMT is not a uniform bulk process but a spatiotemporal phenomenon in which local heating nucleates filaments, contracts or dissolves them with the electric field, and couples to the environment. In this work, we directly image the VO 2 IMT dynamics by mid-wave infrared, thermography synchronized with electrical transport, resolving device temperature with micrometer spatial and microsecond temporal resolution. At the single-device level, we capture the full cycle of filament nucleation, contraction, and relaxation during current/voltage-driven resistive switching. At the array level, we show that heat propagates across etched gaps with an effective length scale of ∼131 µm, enabling cooperative behaviors among electrically isolated devices. Short-range distanced devices exhibit mutual filament attraction and sequential dissolution, while long-range distanced devices differentiate into distinct roles: drivers that initiate switching, cooperative responders that undergo assisted self-oscillations, and passive reporters that record the thermal field. Furthermore, these results reframe thermal crosstalk, long regarded as parasitic, as an intrinsic coupling channel and design principle for organizing collective switching behaviors, with direct implications for emergent circuit functionality in neuromorphic and unconventional computing architectures.

coupling↗
NASA NTRS2009

Flash memory reliability NEPP 2008 task final report

This is the preliminary report which is based on the flash memory reliability studies conducted during the first year (2008) of the multi-year NEPP task. The report outlines the technology and reliability challenges for advanced flash memory technologies, summarizes the test results and analyses of reliability characterizations performed on the selected flash memory devices during 2008, and provides the preliminary thoughts on the risk mitigation approaches on using advanced flash memory technologies for space applications.

Chen, Yuan↗
DOE OSTI2022

Hod Carrier

SAND2023-06720O Hod Carrier is a simple proof-of-concept library for moving data from host to NVIDIA BlueField device memory using remote direct memory access. The Hod Carrier software also facilitates research activities related to the potential uses of NVIDIA BlueField data processing unit devices. Using well-established technologies (e.g., RDMA over Infiniband), it will move data from the host to the data processing unit’s memory. This software is a middleware utility for moving data without regard to its semantic meaning. Its operation is fundamentally unaffected by storage allocation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2024

Algorithmic optimization of quantum optical storage in solids

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Published by the American Physical Society 2024

Lei, Yisheng↗
NASA NTRS1992

NAS technical summaries: Numerical aerodynamic simulation program, March 1991 - February 1992

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefiting other supercomputer centers in Government and industry. This report contains selected scientific results from the 1991-92 NAS Operational Year, March 4, 1991 to March 3, 1992, which is the fifth year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP. The Cray-2, the first generation supercomputer, has four processors, 256 megawords of central memory, and a total sustained speed of 250 million floating point operations per second. The Cray Y-MP, the second generation supercomputer, has eight processors and a total sustained speed of one billion floating point operations per second. Additional memory was installed this year, doubling capacity from 128 to 256 megawords of solid-state storage-device memory. Because of its higher performance, the Cray Y-MP delivered approximately 77 percent of the total number of supercomputer hours used during this year.

Source record↗
NASA NTRS2002

The contribution of diffusion to device upset cross sections

A novel technique incorporating carrier recombination, for determining the charge collection efficiency funcition is presented and applied to a realistic, 3-D, memory device to obtain the upset cross section as a function of LET and orientation of incidence.

charge collection diffusion SEU↗
DOE OSTI2022

Probabilistic Nanomagnetic Memories for Uncertain and Robust Machine Learning

This project evaluated the use of emerging spintronic memory devices for robust and efficient variational inference schemes. Variational inference (VI) schemes, which constrain the distribution for each weight to be a Gaussian distribution with a mean and standard deviation, are a tractable method for calculating posterior distributions of weights in a Bayesian neural network such that this neural network can also be trained using the powerful backpropagation algorithm. Our project focuses on domain-wall magnetic tunnel junctions (DW-MTJs), a powerful multi-functional spintronic synapse design that can achieve low power switching while also opening the pathway towards repeatable, analog operation using fabricated notches. Our initial efforts to employ DW-MTJs as an all-in-one stochastic synapse with both a mean and standard deviation didn’t end up meeting the quality metrics for hardware-friendly VI. In the future, new device stacks and methods for expressive anisotropy modification may make this idea still possible. However, as a fall back that immediately satisfies our requirements, we invented and detailed how the combination of a DW-MTJ synapse encoding the mean and a probabilistic Bayes-MTJ device, programmed via a ferroelectric or ionically modifiable layer, can robustly and expressively implement VI. This design includes a physics-informed small circuit model, that was scaled up to perform and demonstrate rigorous uncertainty quantification applications, up to and including small convolutional networks on a grayscale image classification task, and larger (Residual) networks implementing multi-channel image classification. Lastly, as these results and ideas all depend upon the idea of an inference application where weights (spintronic memory states) remain non-volatile, the retention of these synapses for the notched case was further interrogated. These investigations revealed and emphasized the importance of both notch geometry and anisotropy modification in order to further enhance the endurance of written spintronic states. In the near future, these results will be mapped to effective predictions for room temperature and elevated operation DW-MTJ memory retention, and experimentally verified when devices become available.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Nanoprobe Based Information Processing: Nanoprobe‐Electronics

Abstract With computational architectures becoming data‐centric and with the rise of in‐memory computing, the role of memory will be ever more crucial. In turn, storing massive amount of data demands for ultra‐low power and non‐volatile types necessitating new memory technologies. Here, a controllable nanoelectromechanical (NEM) spin memory is proposed for compact nonvolatile memory arrays. It combines the advantages of both nanomechanical and spin‐transfer torque (STT) magnetic memory devices to overcome fundamental scalability roadblocks of non‐hybrid alternatives. The hybrid system paves the way to a new memory technology in the regime of sub‐10‐nm lateral size with a sub‐1‐MA cm −2 switching energy.

Yi, Bao↗
DOE OSTI2024

Low Power, Radiation Resilient Synchronous Edge Processing for Remote Monitoring

Next-generation space remote sensing systems may be equipped with imaging arrays that sense data at a rate that outstrips the processing capability of any computing hardware that can operate within a satellite’s power budget. This project developed novel convolutional and recurrent neural networks to detect and estimate point-like events amid clutter, and investigated their efficient and accurate implementation on analog in-memory computing systems that are 10-1000× more energy-efficient than digital processors. This project leveraged two memory devices at different levels of technological maturity: a large-scale analog computing prototype using commercial SONOS charge-trap memory, and electrochemical memory (ECRAM) with intrinsic radiation hardness. We experimentally demonstrated end-to-end analog processing of our neural networks on SONOS and characterized the radiation response of both SONOS and ECRAM. We advanced the state-of-the-art in ECRAM precision and reliability, and developed co-design methods to enable accurate long-term operation of SONOS analog accelerators in space radiation environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗