Search NASA⌕ Search

SEARCH · Search NASA

Results for “Memory device”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Zoned namespaces for computing device main memory

Disclosed in some examples are methods, systems, memory devices, memory controllers, and machine-readable mediums which provide for reserving physical memory device resources to specific execution units. Execution units may include processes, threads, virtual machines, functions, procedures, or the like. Physical memory device resources may include channels, modules, ranks, banks, bank groups, and the like. For example, a physical memory device resource that is reservable may be a smallest unit that allows for parallel access with another of the same size unit.

Sheridan, Patrick Michael↗

Controlling reversible phase transitions in rare-earth nickelates for novel memory devices

Resistive switching in correlated complex oxides is lucrative for emerging applications in neuromorphic computing, and densely scaled non-volatile memory. Electrical conductance of such complex oxides can be controllable switched across multiple orders of magnitude by either (a) electroforming a conduction channel (e.g., in tungsten oxide), or (b) inducing Mott-Hubbard transition (e.g., in rare-earth nickelates)– both via controlled migration of defects (such as oxygen vacancies) under applied bias. Nevertheless, the promise of such defect-driven electronic transitions are far from realized due to a lack of fundamental understanding of the atomic-scale processes that underlie migration and spatiotemporal evolution of oxygen vacancies over nano-to-mesoscopic length/timescales under applied electric field. In this project, we employ a synergistic integration of density functional theory (DFT) calculations, ab initio/classical molecular dynamics (AIMD/CMD) simulations, machine learning (ML), precision synthesis, and multi-modal X-ray imaging experiments to address this knowledge gap. Such an integrated approach offers to elucidate the correlations between subtle structural distortion and oxidation states; treat localized charge carriers; describe defect/ion transport in the presence of electric field; and, in turn, greatly advance the current understanding of microstructural evolution in complex oxides under applied bias. The fundamental knowledge gained from this work will enable precise control over hierarchical defect structures and unravel new routes to manipulate resistance states in complex oxides. This, in turn, will accelerate design of novel devices with desired set of neural functionalities, and high-speed densely-scaled resistive random access memory technologies.

36 MATERIALS SCIENCE↗

Mneme

A simple tool allowing recording the execution of a GPU (CUDA) kernel and replaying that kernel as an independent executable. The tool operates in 3 phases. During compile time the user needs to apply a provided LLVM pass to instrument the code. The pass detects all device global variables and device functions and stores this information with the respective LLVM-IR in the global device memory. The compilation generates a record-able executable. The second phase involves running the application executable with a desired input and using LD_PRELOAD to enable recording. When recording before invoking a device kernel the pre-loaded library stores device memory in persistent storage and associates the memory with the device kernel and an LLVM IR file. At the end of the recorded execution the pre-load library generates a database in the form of a JSON file containing information regarding the LLVM-IR files and the snapshots of device memory. During the third and last phase the user can replay the execution of an kernel as a separate independent executable. Besides executing it the user can modify the LLVM IR file and auto-tune parameters such as kernel launch-bounds or kernel runtime execution parameters (e.g. Kernel Block and Grid Dimensions). Is

Parasyris, Konstantinos↗

Autonomous Multistate Nanoencoding Using Combinatorial Ferroelectric Closure Domains in BiFeO 3

Recent advances in ferroic materials have identified topological defects as promising candidates for enabling additional functionalities in future electronic systems. The generation of stable and customizable polar topologies is needed to achieve multistates that enable beyond-binary device architectures. Here, in this study, we show how to autonomously pattern on-demand highly tunable striped closure domains in pristine rhombohedral-phase BiFeO 3 thin films through precise scanning of a biased atomic force microscopy tip along carefully designed paths. By employing this strategy, we generate and manipulate closed-loop structures with high spatial resolution in an automated manner, allowing the creation of highly tunable and intricate topological domain structures that exhibit distinct polarization configurations without the need for electrode deposition or complex heterostructure growth. As a proof-of-concept for ferroelectric beyond-binary memory devices, we use such topological domains as multistates, engineering an alphabet and automating the symbolic writing/reading process using autonomous microscopy. The resulting information density is compared with that of current commercially available memory devices, demonstrating the potential of ferroelectric topological domains for multistate information storage applications.

BiFeO3↗

A new era of ferroelectric thin films for nonvolatile memories

Ferroelectric films have potential applications in nonvolatile memory devices. In addition to the well-established perovskite-structure oxide ferroelectrics, hafnia- and wurtzite-based ferroelectrics have recently attracted considerable attention because of the improved scalability of the ferroelectric response (down to nanometer thicknesses), their compatibility with silicon fabrication processes, and the availability of deposition methods that realize three-dimensional structures. Furthermore, due to their high compatibility with silicon processes, these are also expected to be used in emerging energy-efficient applications, such as neuromorphic computing and reservoir computing. In this article, we review the fundamentals of hafnia- and wurtzite-based ferroelectrics and their advantages and issues for developing in nonvolatile memory devices. Then, possible emerging applications are discussed.

36 MATERIALS SCIENCE↗

Field-free switching of perpendicular magnetization in a ferrimagnetic insulator with spin reorientation transition

Writing magnetic bits through spin-orbit torque (SOT) switching is promising for fast and efficient magnetic random-access memory devices. While SOT switching of out-of-plane (OOP) magnetized states requires lateral symmetry breaking, in-plane (IP) magnetized states suffer from low storage density. Here, we demonstrate a field-free switching scheme using a 5-nanometer europium iron garnet film grown with a (110) orientation that shows a spin reorientation transition from OOP to IP above room temperature. This scheme combines the benefits of high-density storage in the OOP states at room temperature and the efficient field-free SOT switching in the IP states at elevated temperatures. While conventional switching of OOP bits faces the dilemma that high OOP anisotropy is required to improve bit stability and low OOP anisotropy is required to lower switching current density, this scheme disentangles this interdependence, allowing for low switching currents to be possible without sacrificing the bit stability, offering opportunities for future memory devices.

Science & Technology - Other Topics↗

Magnetic Switching in Monolayer 2D Diluted Magnetic Semiconductors via Spin‐to‐Spin Conversion

Abstract The integration of 2D van der Waals (vdW) magnets with topological insulators or heavy metals holds great potential for realizing next‐generation spintronic memory devices. However, achieving high‐efficiency spin–orbit torque (SOT) switching of monolayer vdW magnets at room temperature poses a significant challenge, particularly without an external magnetic field. Here, it is shown field‐free, deterministic, and nonvolatile SOT switching of perpendicular magnetization in the monolayer, diluted magnetic semiconductor (DMS), Fe‐doped MoS 2 (Fe:MoS 2 ) at up to 380 K with a current density of ≈7 × 10 4 A cm −2 . The in situ doping of Fe into monolayer MoS 2 via chemical vapor deposition and the geometry‐induced strain in the crystal break the rotational switching symmetry in Fe:MoS 2 , promoting field‐free SOT switching by generating out‐of‐plane spins via spin‐to‐spin conversion. An apparent anomalous Hall effect (AHE) loop shift at a zero in‐plane magnetic field verifies the existence of z spins in Fe:MoS 2 , inducing an antidamping‐like torque that facilitates field‐free SOT switching. This field‐free SOT application using a 2D ferromagnetic monolayer provides a new pathway for developing highly power‐efficient spintronic memory devices.

Chen, Siwei [Department of Mechanical Engineering ↗

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

Characterization of fluorite-structured ferroelectrics using transmission electron microscopy: Techniques, challenges, and recent advances

Fluorite-structured ferroelectrics, such as hafnium oxide and its alloyed variants, are key candidates for next-generation memory devices. Yet, fundamental questions about switching mechanisms, domain dynamics, and phase evolution remain open. Transmission electron microscopy (TEM) provides unique capabilities to address these challenges by simultaneously resolving the positions of anions and cations, chemical variations, and structural transformations. Recent advances—including in situ heating, electron beam-induced switching, electron energy loss spectroscopy, and differential phase contrast imaging—have revealed critical insights into phase transitions, potential switching pathways, and oxygen vacancy behavior. However, experimental barriers such as TEM sample-preparation-induced artifacts, high coercive fields, and imaging constraints persist, especially for polycrystalline films. By offering a focused overview of current TEM developments in fluorite ferroelectrics, this work outlines how TEM contributes to understanding key phenomena and proposes a roadmap for future studies.

36 MATERIALS SCIENCE↗

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)↗

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↗

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↗

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↗

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↗

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↗

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 ↗

Error-Free and Current-Driven Synthetic Antiferromagnetic Domain Wall Memory Enabled by Channel Meandering

We propose a new type of energy-efficient multi-bit magnetic memory based on current-driven, field-free, controlled domain wall motion. A meandering domain wall channel with precisely interspersed pinning regions provides the multi-bit capability of a magnetic tunnel junction memory. The magnetic free layer of the memory device has perpendicular magnetic anisotropy (PMA) and interfacial Dzyaloshinskii-Moriya interaction (DMI) so that spin-orbit torques (SOTs) induce efficient domain wall motion. Using micromagnetic simulations, we find two different cell designs: two-way switching and four-way switching. The memory cell design choices and the physics of pinning mechanisms are discussed in detail. Furthermore, we show that switching reliability and speed may be significantly improved by replacing the ferromagnetic free layer with a synthetic antiferromagnetic (SAF) layer. Switching behavior and material choices will be discussed for the two memory implementations.

magnetic domain wall↗

Increased Static Charge–Induced Threshold Voltage Shifts and Memristor Activity in Pentacene OFETs Comprising Polystyrene–Based Gate Dielectrics Containing Electroactive Small Molecule Crystallites

Top-contact bottom-gate pentacene OFETs are fabricated with single layer dielectrics comprised of either polystyrene (PS), poly(4-methylstyrene) (P4MS), or poly(4-tert-butylstyrene) (P4TBS). The polystyrenes are blended with varying concentrations of two different small molecules, dibenzotetrathiafulvalene (DBTTF) and 2,8-difluoro-5,11-bis(triethylsilylethynyl)anthradithiophene (diF-TES-ADT), to form small, separated crystallites contained throughout the polymer dielectric layer. The OFET characteristics of these devices are investigated and their threshold voltage shifts are measured after –70 V static charging for 5 min. Two-terminal measurements are conducted using multiple different gate biases in the range of –50 to +50 V to investigate memristor behavior in the devices. OFETs containing DBTTF exhibited ΔVth increases as large as 330% relative to control OFETs containing no DBTTF, while OFETs containing at least 7.5 wt.% DBTTF exhibited memristor activity, with currents ranging from 20 nA to 44 µA depending on the applied bias. Furthermore, this work demonstrates that including small, separated crystallites in polymer dielectrics enhances their charge storage ability and can be promising for creating nonbinary memory devices for data processing. Additionally, the observed memristor activity indicates the OFETs in this work can be used in development of neuromorphic systems that aim to mimic the synaptic behavior of the human nervous system.

25 ENERGY STORAGE↗