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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ultra-Fast Non-Volatile Resistive Switching Devices with Over 512 Distinct and Stable Levels for Memory and Neuromorphic Computing

Low-current multilevel programmability with inherent non-volatility and high stability of resistance states is required for both multi-bit memory storage and deep learning accelerators but is difficult to achieve. Here, in a resistive switching system, this work realizes >512 (>9 bits) distinct non-volatile conductance levels with stable retention for each state with current levels down to the nanoampere range, highly promising for potential integration with small processing nodes with ultra-low power consumption requirements. This is achieved by demonstrating a new thin film design concept that encompasses three key features: an ultra-thin epitaxial oxygen ionic switching layer that provides a tunable energy barrier at the bottom electrode, an overcoat amorphous layer that acts as an ion migration barrier for stable state retention, and a partial conductive filament as a localized electronic transport channel to the epitaxial switching layer. A large dynamic resistance range of up to seven orders of magnitude is achieved with reset-free transitions among intermediate states, and programmability is demonstrated with ultra-fast (20 ns) pulses. Artificial neural network (ANN) simulations, based on the experimental performance and its non-idealities, demonstrate close-to-ideal inference accuracies for various Modified National Institute of Standards and Technology (MNIST) data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Study of carbon nanotube embedded honey as a resistive switching material

In this paper, natural organic honey embedded with carbon nanotubes (CNTs) was studied as a resistive switching material for biodegradable nonvolatile memory in emerging neuromorphic systems. CNTs were dispersed in a honey-water solution with the concentration of 0.2 wt% CNT and 30 wt% honey. The final honey-CNT-water mixture was spin-coated and dried into a thin film sandwiched in between Cu bottom electrode and Al top electrode to form a honey-CNT based resistive switching memory (RSM). Surface morphology, electrical characteristics and current conduction mechanism were investigated. The results show that although CNTs formed agglomerations in the dried honey-CNT film, both switching speed and the stability in SET and RESET process of honey-CNT RSM were improved. The mechanism of current conduction in CNT is governed by Ohm’s law in low-resistance state and the low-voltage range in high-resistance state, but transits to the space charge limited conduction at high voltages approaching the SET voltage.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anisotropic MagnetoMemristance

Abstract In the last decade, nanoscale resistive devices with memory have been the subject of intense study because of their possible use in brain-inspired computing. However, operational endurance is one of the limiting factors in the adoption of such technology. For this reason, we discuss the emergence of current-induced memristance in magnetic materials, known for their durability. We show analytically and numerically that a single ferromagnetic layer can possess GHz memristance, due to a combination of two factors: a current-induced transfer of angular momentum (Zhang-Li torque) and the anisotropic magnetoresistance (AMR). We term the resulting effect the anisotropic magneto-memristance (AMM). We connect the AMM to the topology of the magnetization state, within a simple model of a one-dimensional annulus-shaped magnetic layer, confirming the analytical results with micromagnetic simulations for permalloy. Our results open a new path towards the realization of single-layer magnetic memristive devices operating at GHz frequencies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Suppressing Structural Relaxation in Nanoscale Antimony to Enable Ultralow‐Drift Phase‐Change Memory Applications

Abstract Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10 −4 –10 −3 . This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO 2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electronegative metal dopants improve switching variability in Al 2 ⁢O 3 resistive switching devices

Resistive random-access memories are promising for nonvolatile memory and brain-inspired computing applications. High variability and low yield of these devices are key drawbacks hindering reliable training of physical neural networks. In this paper, we show that doping an oxide electrolyte, Al 2 ⁢O 3 , with electronegative metals makes resistive switching significantly more reproducible, surpassing the reproducibility requirements for obtaining reliable hardware neuromorphic circuits. Based on density functional theory calculations, the underlying mechanism is hypothesized to be the ease of creating oxygen vacancies in the vicinity of electronegative dopants due to the capture of the associated electrons by dopant midgap states and the weakening of Al-O bonds. These oxygen vacancies and vacancy clusters also bind significantly to the dopant, thereby serving as preferential sites and building blocks in the formation of conducting paths. Throughout this work, we validate this theory experimentally by implanting different dopants over a range of electronegativities in devices made of multiple alternating layers of Al 2 ⁢O 3 and WN and find superior repeatability and yield with highly electronegative metals, Au, Pt, and Pd. These devices also exhibit a gradual SET transition, enabling multibit switching that is desirable for analog computing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reduced Stochastic Resistive Switching in Organic-Inorganic Hybrid Memristors by Vapor-Phase Infiltration

We report resistive random-access memory (RRAM) is promising for next-generation data storage and non-von Neumann computing hardware. However, tuning device switching characteristics and particularly, controlling their stochastic variation remain as critical challenges. Here, new organic-inorganic hybrid RRAM media are reported whose bipolar switching characteristics and stochasticity can be controlled by vapor-phase infiltration (VPI), an ex situ hybridization technique derived from atomic layer deposition. Hybrid RRAMs based on AlO x -infiltrated SU-8 feature facile tunability of device switching voltages, off-state current, and on-off ratio by adjusting the amount of infiltrated AlO x in the hybrid. Furthermore, a significant reduction in the stochastic, cycle-to-cycle variations of switching parameters is enabled by AlO x infiltration, driven by the infiltration-induced changes in mechanical, dielectric, and chemical properties of organic medium and their influence on the dimension and formation characteristics of conductive filaments. Finally, multi-level analog switching potentially useful for neuromorphic applications are demonstrated, along with direct, one-step device patterning exploiting the negative-tone resist feature of SU-8. With the demonstrated control over switching characteristics and stochastic variation, combined with analog switching and one-step patterning capabilities, the results not only present a novel hybrid medium for RRAM applications but also showcase the utility of VPI for developing new, high-performance hybrid RRAM devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors

With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine learning algorithms. Unconventional computing approaches such as neuromorphic computing that leverage spiking neural networks (SNNs) to perform computation are gaining traction and seek the paradigm shift necessary to sustain the increasing demands of modern applications. Novel memory technologies, such as resistive RAM (ReRAM), employ a crossbar architecture that possesses the inherent capability of efficiently computing vector-matrix multiplication—a dominant operation in SNNs. The prospect of naturally mapping SNNs to the crossbar structures provides a unique opportunity for achieving a high-performance, power-efficient neuromorphic system. In this work, we present ReSpike, which is a new framework, behavioral simulator, and architectural design based on ReRAM crossbar architectures, enabling modeling and co-design to achieve efficient execution of SNNs. We drive this co-design forward by quantifying the impact that ReRAM cell nonidealities have on the corresponding accuracy of an SNN application.

Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)↗
DOE OSTI2020

Quantum Memristors in Frequency-Entangled Optical Fields

A quantum memristor is a passive resistive circuit element with memory, engineered in a given quantum platform. It can be represented by a quantum system coupled to a dissipative environment, in which a system–bath coupling is mediated through a weak measurement scheme and classical feedback on the system. In quantum photonics, such a device can be designed from a beam splitter with tunable reflectivity, which is modified depending on the results of measurements in one of the outgoing beams. Here, we show that a similar implementation can be achieved with frequency-entangled optical fields and a frequency mixer that, working similarly to a beam splitter, produces state superpositions. We show that the characteristic hysteretic behavior of memristors can be reproduced when analyzing the response of the system with respect to the control, for different experimentally attainable states. Since memory effects in memristors can be exploited for classical and neuromorphic computation, the results presented in this work could be a building block for constructing quantum neural networks in quantum photonics, when scaling up.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering of Grain Boundaries in CeO 2 Enabling Tailorable Resistive Switching Properties

Abstract Defect engineering in valence change memories aimed at tuning the concentration and transport of oxygen vacancies are studied extensively, however mostly focusing on contribution from individual extended defects such as single dislocations and grain boundaries. In this work, the impact of engineering large numbers of grain boundaries on resistive switching mechanisms and performances is investigated. Three different grain morphologies, that is, “random network,” “columnar scaffold,” and “island‐like,” are realized in CeO 2 thin films. The devices with the three grain morphologies demonstrate vastly different resistive switching behaviors. The best overall resistive switching performance is shown in the devices with “columnar scaffold” morphology, where the vertical grain boundaries extending through the film facilitate the generation of oxygen vacancies as well as their migration under external bias. The observation of both interfacial and filamentary switching modes only in the devices with a “columnar scaffold” morphology further confirms the contribution from grain boundaries. In contrast, the “random network” or “island‐like” structures result in excessive or insufficient oxygen vacancy concentration migration paths. The research provides design guidelines for grain boundary engineering of oxide‐based resistive switching materials to tune the resistive switching performances for memory and neuromorphic computing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nonvolatile memory cells from hafnium zirconium oxide ferroelectric tunnel junctions using Nb and NbN electrodes

Ferroelectric tunnel junctions (FTJs) utilizing hafnium zirconium oxide (HZO) have attracted interest as non-volatile memory for microelectronics due to ease of integration into back-end-of-line (BEOL) complementary metal oxide semiconductor fabrication. This work examines asymmetric electrode NbN/HZO/Nb devices with 7 nm thick HZO as FTJs in a memory structure, with an output resistance that can be controlled by read and write voltages. The individual FTJs are measured to have a tunneling electroresistance of 10 during the read state without significant filament conduction formation and reasonable ferroelectric performance. Endurance and remanent polarizations of up to 10 5 cycles and 20 μC/cm 2 , respectively, are measured and are shown to be dependent on the cycling voltage. Electrical measurements demonstrate how magnitude of the write pulse can modulate the high state resistance and the read pulse influences both resistance values as well as separation of resistance states. Then, by using two opposite switching FTJ devices in series, a programmable nonvolatile resistor divider is demonstrated. Measurements of these two FTJ unit memory cells show wide applicability to a BEOL microfabrication process for a re-readable, rewritable, and nonvolatile memory cell.

42 ENGINEERING↗
DOE OSTI2022

Scalable Al 2 O 3 –TiO 2 Conductive Oxide Interfaces as Defect Reservoirs for Resistive Switching Devices

Abstract Resistive switching devices herald a transformative technology for memory and computation, offering considerable advantages in performance and energy efficiency. Here, a simple and scalable material system of conductive oxide interfaces is employed, and their unique properties are leveraged for a new type of resistive switching device. An Al 2 O 3 –TiO 2 ‐based valence‐change resistive switching device, where the conductive oxide interface serves both as the bottom electrode and as a reservoir of defects for switching, is demonstrated. The amorphous–polycrystalline Al 2 O 3 –TiO 2 conductive interface is obtained following the technological path of simplifying the fabrication of the 2D electron gases (2DEGs), making them scalable for practical mass integration. Physical analysis of the device chemistry and microstructure with comprehensive electrical analysis of its switching behavior and performance is combined. The origin of the resistive switching is pinpointed to the conductive oxide interface, which serves both as the bottom electrode and as a reservoir of oxygen vacancies. The latter plays a key role in valence‐change resistive switching devices. The new device, based on scalable and complementary metal–oxide–semiconductor (CMOS)‐technology‐compatible fabrication processes, opens new design spaces toward increased tunability and simplification of the device selection challenge.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Two-terminal electronic charge resistance switching device

A two-terminal memory device and methods for its use are provided. In the device, a bottom electrode is electrically continuous with a first operating terminal, and a control gate electrode is electrically continuous with a second operating terminal. A stack of insulator layers comprising a hopping conduction layer and a tunnel layer is contactingly interposed between the bottom electrode and the control gate electrode. The tunnel layer is thinner than the hopping conduction layer, and it has a wider bandgap than the hopping conduction layer. The hopping conduction layer consists of a material that supports electron hopping transport.

Marinella, Matthew↗
DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗
DOE OSTI2020

Thermal conductivity of (Ge 2 Sb 2 Te 5 ) 1–x Cx phase change films

Germanium–antimony–telluride has emerged as a nonvolatile phase change memory material due to the large resistivity contrast between amorphous and crystalline states, rapid crystallization, and cyclic endurance. Improving thermal phase stability, however, has necessitated further alloying with optional addition of a quaternary species (e.g., C). In this work, the thermal transport implications of this additional species are investigated using frequency-domain thermoreflectance in combination with structural characterization derived from x-ray diffraction and Raman spectroscopy. Specifically, the room temperature thermal conductivity and heat capacity of (Ge 2 Sb 2 Te 5 ) 1–x C x are reported as a function of carbon concentration (x ≤ 0:12) and anneal temperature (T ≤ 350 °C) with results assessed in reference to the measured phase, structure, and electronic resistivity. Phase stability imparted by the carbon comes with comparatively low thermal penalty as materials exhibiting similar levels of crystallinity have comparable thermal conductivity despite the addition of carbon. The additional thermal stability provided by the carbon does, however, necessitate higher anneal temperatures to achieve similar levels of structural order.

42 ENGINEERING↗
DOE OSTI2025

SULI Deliverables Using: Python-B1500 [Slides]

A new electrical setup for testing ECRAM devices is described in this presentation. This presentation details the background of ECRAM devices, how the B1500 is used to program ECRAM devices, and the python GUI that was created for controlling the B1500. ECRAM devices are a form of non-volatile memory. The stored data is the resistance between two of the terminals on the device. Using only the B1500, the ECRAM devices can be programmed and the state read out. This creates a simple, logical testing setup. The overall setup was successful, ECRAM devices could easily be programmed and measured. However, there is still room for improvement. Specifically, in the creation of an automated “Program” feature and a “Data Collection” feature. These features will require additional advances in the understanding of ECRAM devices but will greatly automate and improve the current data collection and application of ECRAM devices.

42 ENGINEERING↗
DOE OSTI2025

CRADA 2022-03 Final Report: Advanced Bearing Materials for Harsh Service Conditions

Develop advanced bearing materials for hydrogen gas turbines and wind turbines. Two candidate materials have been selected based on Ames lab’s recent work on high entropy alloys and shape memory alloys. These materials are designed to exhibit a balance of hardness, strength, toughness, and corrosion resistance. The hydrogen diffusion coefficient in the NiTi based shape memory alloy is two order of magnitude lower than that of the conventional case hardened bearing steel. We plan to atomize these materials into powders, additive manufacture cylindrical bearings, then test these bearing for rolling-contact fatigue, corrosion properties, and hydrogen embrittlement. We are a vertically integrated team comprises of national labs, bearing manufacturers, raw material powders makers, and aircraft gas turbine manufacturer.

Argibay, Nicolas [Ames Laboratory (AMES), Ames, IA↗
DOE OSTI2022

Ultraefficient resistance switching between charge ordered phases in 1 T -TaS 2 with a single picosecond electrical pulse

Progress in high-performance computing demands significant advances in memory technology. Among novel memory technologies that promise efficient device operation on a sub-ns timescale, resistance switching between charge ordered phases of 1T-TaS 2 has shown to be potentially useful for development of high-speed, energy efficient nonvolatile memory devices. Measurement of the electrical operation of such devices in the picosecond regime is technically challenging and hitherto still largely unexplored. Here, we use an optoelectronic “laboratory-on-a-chip” experiment for measurement of ultrafast memory switching, enabling accurate measurement of electrical switching parameters with 100 fs temporal resolution. Photoexcitation and electro-optic sampling on a (Cd,Mn)Te substrate are used to generate and, subsequently, measure electrical pulse propagation with intra-band excitation and sub-gap probing, respectively. We demonstrate high contrast nonvolatile resistance switching from high to low resistance states of a 1T-TaS 2 device using single sub-2ps electrical pulses. Using detailed modeling, we find that the switching energy density per unit area is exceptionally small, E A =9.4 fJ/μm 2 . Finally, the speed and energy efficiency of an electronic “write” process place the 1T-TaS 2 devices into a category of their own among new generation nonvolatile memory devices.

42 ENGINEERING↗