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Results for “analog resistive switching”

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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7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Interface–Type Memristive Device for Artificial Synapse and Neuromorphic Computing

Interface-type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament-type (FT) devices for neuromorphic computing because of their uniform, filament-free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface-dominated memristive device is demonstrated using a simple Au/Nb-doped SrTiO 3 (Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible for the analog resistive switching characteristics. Because of its interface-controlled RS, the proposed device shows low device-to-device, cell-to-cell, and cycle-to-cycle variability while maintaining high repeatability and stability during endurance and retention tests. Furthermore, the Au/Nb:STO IT memristive device exhibits versatile synaptic functions with an excellent uniformity, programmability, and reliability. A simulated artificial neural network with Au/Nb:STO synapses achieves a high recognition accuracy of 94.72% for large digit recognition from MNIST database. These results suggest that IT resistive switching can be potentially used for artificial synapses to build next-generation neuromorphic computing.

36 MATERIALS SCIENCE↗
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 OSTI2026

Multifunctional electrochemical memory stabilized by phase coexistence

Our growing computing needs, especially in applications that heavily rely on artificial intelligence (AI), motivate a search for new components that could substantially augment the performance of general-purpose digital computers. Beyond ON/OFF switching, new components with linear multistate analog resistive tuning, nonlinear volatile switching, spiking, oscillatory, stochastic and other complex functionalities could enable highly efficient neuromorphic computing schemes for AI information processing. Compared to the extreme multifunctionality of biological neurons, realizing all the above characteristics in a single, scalable analog component remains a grand challenge. Here we investigate electrochemical gating combined with localized thermal activation to program and switch a single, vertically integrated and dimensionally scaled electrothermal chemical random access memory (ETCRAM) with a channel and reservoir composed of phase-separated vanadium oxide. Closely related to electrochemical RAM (ECRAM), ETCRAM uses an integrated gate-heater electrode to overcome kinetic barriers that help retain states at ambient temperatures. In addition to synapse-like stable and programmable analog resistance states arising from redox-tunable phase coexistence, a single component exhibits neuron-like nonlinear conductance switching with a tunable threshold and self-driven dynamics owing to the thermally driven metal-insulator phase transition in vanadium dioxide. More broadly, we demonstrate that electrochemically stabilized phase coexistence could unlock analog electronics with novel functionality, stability, reconfigurability, and scalability.

Oh, Sangheon [Sandia National Lab. (SNL-CA), Liver↗
DOE OSTI2026

Harnessing the Second-Order Metal−Insulator Transition for Neuromorphic Computing

Vanadium oxides are widely studied phase change materials for brain-inspired computing architectures. Systems like VO 2 and V 2 O 3 exhibit first-order metal−insulator transitions (MITs) with hysteresis and percolative switching, increasing stochasticity and device variability. Here, we focus on the less explored Magnéli phase V 4 O 7 , which undergoes a continuous, non-hysteretic, second-order MIT. This surprisingly enables highly reproducible volatile resistive switching in spiking-neuron-type devices. We synthesize V 4 O 7 films, characterize their structural and transport properties, and demonstrate voltage and current-driven threshold switching with electrothermal feedback. In a Pearson–Anson oscillator, V 4 O 7 devices produce stable, tunable spiking across 20–200 kHz, with consistent operation among multiple devices. We introduce a numerical analog leaky-integrate-and-fire (aLIF) model that captures waveform shapes and their dependence on load resistance, temperature, and voltage. Furthermore, these findings suggest that second-order MIT materials like V 4 O 7 are promising for deterministic, scalable spiking neuron arrays for neuromorphic computing.

V4O7↗
DOE OSTI2023

Switch leakage mitigation through differential cancellation

High speed analog-to-digital converters (ADC), switched-capacitor delay elements, and pulsed radio frequency (RF) systems all require switches in the signal path operating at high switching speeds, providing low resistance when enabled, and providing high signal isolation when disabled. In semiconductor technologies such as CMOS, the enabled state resistance directly scales with the sizing of the switch device, where a larger width switch provides a lower enabled state resistance. As the device width is increased, so is the capacitance formed between the gate, drain, and source of the device.

42 ENGINEERING↗
DOE OSTI2026

Josephson dynamics in two-dimensional ring-shaped condensates

We investigate Josephson transport in a fully closed, two-dimensional superfluid circuit formed by a ring-shaped 87 Rb Bose-Einstein condensate that contains two optical barriers acting as movable weak links. Translating these barriers at controlled speeds imposes a steady bias current, enabling direct mapping of the current-chemical-potential (𝐼−Δ⁢𝜇) characteristics. For narrow junctions (𝑤 ≈ 1µ⁢m), the circuit exhibits a pronounced dc branch that terminates at a critical current 𝐼 𝑐 = 9⁢(1) × 10 3 s −1 ; above this threshold, the system switches to an ac, resistive regime. Classical-field simulations that include the moving barriers quantitatively reproduce both the nonlinear 𝐼−Δ⁢𝜇 curve and the measured 𝐼 𝑐 , validating the underlying microscopic picture. Analysis of the ensuing phase dynamics shows that dissipation is mediated by the nucleation and traversal of vortex-antivortex pairs through the junctions, while the bulk condensate remains globally phase locked—direct evidence of the ring's topological constraint enforcing quantized circulation. These results establish a cold-atom analog of a superconducting quantum interference device in which Josephson dynamics can be resolved at the single-vortex level, providing a versatile platform for atomtronic circuit elements, nonreciprocal Josephson devices, and on-chip Sagnac interferometers for multiaxis rotation sensing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors and electrochemical RAM. Equally important, Abisko uses a deep codesign approach to pursue this goal by engaging experts from across the entire range of disciplines: materials, devices and circuits, architectures and integration, software, and algorithms. Here, the key objectives of our Abisko project are threefold. First, we are designing an energy-optimized high-performance neuromorphic accelerator based on SNNs. This architecture is being designed as a chiplet that can be deployed in contemporary computer architectures and we are investigating novel neuromorphic materials to improve its design. Second, we are concurrently developing a productive software stack for the neuromorphic accelerator that will also be portable to other architectures, such as field-programmable gate arrays and GPUs. Third, we are creating a new deep codesign methodology and framework for developing clear interfaces, requirements, and metrics between each level of abstraction to enable the system design to be explored and implemented interchangeably with execution, measurement, a model, or simulation. As a motivating application for this codesign effort, we target the use of SNNs for an analog event detector for a high-energy physics sensor.

97 MATHEMATICS AND COMPUTING↗