Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “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.

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

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Origins of anisotropic transport in the electrically switchable antiferromagnet Fe 1/3 NbS 2

Recent experiments on the antiferromagnetic intercalated transition metal dichalcogenide Fe 1/3 NbS 2 have demonstrated reversible resistivity switching by application of orthogonal current pulses below its magnetic ordering temperature, making Fe 1/3 NbS 2 promising for spintronics applications. Here, we perform density functional theory calculations with Hubbard U corrections of the magnetic order, electronic structure, and transport properties of crystalline Fe 1/3 NbS 2 , clarifying the origin of the different resistance states. The two experimentally proposed antiferromagnetic ground states, corresponding to in-plane stripe and zigzag ordering, are computed to be nearly degenerate. In-plane cross sections of the calculated Fermi surfaces are anisotropic for both magnetic orderings, with the degree of anisotropy sensitive to the Hubbard U value. The in-plane resistance, computed within the Kubo linear response formalism using a constant relaxation time approximation, is also anisotropic, supporting a hypothesis that the current-induced resistance changes are due to a repopulating of antiferromagnetic domains. Our calculations indicate that the transport anisotropy of Fe 1/3 NbS 2 in the zigzag phase is reduced relative to stripe, consistent with the relative magnitudes of resistivity changes in experiment. Finally, our calculations reveal the likely directionality of the current-domain response, specifically, which domains are energetically stabilized for a given current direction.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electrically-driven IMT and volatile memristor behavior in NdNiO 3 films

Abstract Transition metal oxides with insulator-metal transitions (IMTs) are uniquely suited for volatile memristor devices that mimic the spiking of biological neurons. Unlike most non-volatile memristors, which often operate via ion migration into filaments, volatile devices utilize a reversible phase change that returns to a ground state in the absence of applied stimulus. In these devices, Joule heating triggers the IMT and changes the bulk resistivity rather than influencing conduction through defects, as in previous studies. This volatile resistive switching behavior has previous been leveraged in niobium and vanadium oxides, but not in rare-earth nickelates, despite their tunable transition temperatures. This study demonstrates an electrically driven IMT in the prototypical rare-earth nickelate, NdNiO 3 , in large area devices. While previous work examining the electrically-driven IMT in NdNiO 3 suggests defect-dominated conduction, this study shows clear s-type negative differential resistance (NDR) consistent with temperature-dependent resistivity measurements. The NDR peak-to-valley voltage scales linearly with temperature as expected for conductivity pathways dominated by bulk IMT behavior. Unlike other transition metal oxides, which are modeled using the insulator-metal phase fraction as the internal state variable, a thermoelectric model with temperature as the internal state variable is found to more accurately describe the current–voltage characteristic of NdNiO 3 volatile memristors. Overall, we report the synthesis, fabrication, and characterization of NdNiO 3 volatile memristors with resistivity dominated by bulk-like IMT behavior which is scalable and not dependent upon oxygen vacancy migration or defect mediated conduction pathways.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electrical Control of Magnetic Resonance in Phase Change Materials

Metal–insulator transitions (MITs) in resistive switching materials can be triggered by an electric stimulus that produces significant changes in the electrical response. When these phases have distinct magnetic characteristics, dramatic changes in the spin excitations are also expected. The transition metal oxide La 0.7 Sr 0.3 MnO 3 (LSMO) is a ferromagnetic metal at low temperatures and a paramagnetic insulator above room temperature. When LSMO is in its metallic phase, a critical electrical bias has been shown to lead to an MIT that results in the formation of a paramagnetic resistive barrier transverse to the applied electric field. Using spin-transfer ferromagnetic resonance spectroscopy, we show that even for electrical biases less than the critical value that triggers the MIT, there is magnetic phase separation, with the spin-excitation resonances varying systematically with applied bias. Therefore, voltage-triggered MITs in LSMO can alter magnetic resonance characteristics, offering an effective method for tuning synaptic weights in neuromorphic circuits.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In operando cryo-STEM of pulse-induced charge density wave switching in TaS 2

The charge density wave material 1T-TaS 2 exhibits a pulse-induced insulator-to-metal transition, which shows promise for next-generation electronics such as memristive memory and neuromorphic hardware. However, the rational design of TaS 2 devices is hindered by a poor understanding of the switching mechanism, the pulse-induced phase, and the influence of material defects. Here, we operate a 2-terminal TaS 2 device within a scanning transmission electron microscope at cryogenic temperature, and directly visualize the changing charge density wave structure with nanoscale spatial resolution and down to 300 μs temporal resolution. We show that the pulse-induced transition is driven by Joule heating, and that the pulse-induced state corresponds to the nearly commensurate and incommensurate charge density wave phases, depending on the applied voltage amplitude. With our in operando cryogenic electron microscopy experiments, we directly correlate the charge density wave structure with the device resistance, and show that dislocations significantly impact device performance. This work resolves fundamental questions of resistive switching in TaS 2 devices, critical for engineering reliable and scalable TaS 2 electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Heteroepitaxial control of thickness, strain, and domain architecture in few-layer ferroelectric tin monochalcogenides

Thin-film epitaxy and epitaxial strain have been widely exploited to tune domain configurations, switching behavior, and ferroic properties in conventional three-dimensional ferroelectric thin films; however, its application to controlling the properties of two-dimensional (2D) ferroelectrics has remained largely unexplored. Here, using SnX (X = Se, S) as a model system, we demonstrate heteroepitaxial control of thickness, strain state, and domain architecture in few-layer ferroelectric SnX via growth on monolayer MoS2 van der Waals (vdW) templates. Compared with conventional growth, MoS2-templated heteroepitaxy promotes epitaxial alignment, yielding ultrathin SnSe films with improved crystalline quality, full areal coverage, and enlarged lateral dimensions. Strong interfacial epitaxial coupling induces pronounced in-plane strain and stabilizes a hierarchical ferroelastic domain architecture, in which long-range 90° stripe domains are further subdivided into nanoscale rotational variants, as revealed by scanning transmission electron microscopy and synchrotron X-ray microscopy. Piezoresponse force microscopy and second-harmonic polarimetry confirm robust in-plane polarization, while ferroelectricity in SnSe is established through polarization-electric field hysteresis and nonvolatile ferroelectric resistive switching with on/off ratios approaching 1000. A nonvolatile, switchable ferroelectric diode effect further evidences direct coupling between polarization and charge transport. Notably, ferroelectric switchability exhibits a strong thickness dependence and is preserved only below ∼10 layers. This vdW heteroepitaxial strategy is further extended to ferroelectric SnS. The seamless heteroepitaxial integration of 2D ferroelectrics with CMOS-compatible, wafer-scale MoS2 templates provides a general and scalable route for strain-enabled structural and ferroelectric engineering in emerging memory and low-power optoelectronic applications.

Wang, Yueyin↗
DOE OSTI2024

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↗
DOE OSTI2021

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. Further, the different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantum Sensing of Insulator‐to‐Metal Transitions in a Mott Insulator

Nitrogen vacancy (NV) centers, optically active atomic defects in diamond, have attracted tremendous interest for quantum sensing, network, and computing applications due to their excellent quantum coherence and remarkable versatility in a real, ambient environment. Taking advantage of these strengths, this paper reports on NV-based local sensing of the electrically driven insulator-to-metal transition (IMT) in a proximal Mott insulator. The resistive switching properties of both pristine and ion-irradiated VO 2 thin film devices are studied by performing optically detected NV electron spin resonance measurements. These measurements probe the local temperature and magnetic field in electrically biased VO 2 devices, which are in agreement with the global transport measurement results. In pristine devices, the electrically driven IMT proceeds through Joule heating up to the transition temperature while in ion-irradiated devices, the transition occurs nonthermally, well below the transition temperature. Here, the results provide direct evidence for nonthermal electrically induced IMT in a Mott insulator, highlighting the significant opportunities offered by NV quantum sensors in exploring nanoscale thermal and electrical behaviors in Mott materials.

McLaughlin, Nathan J.↗
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 OSTI2024

Multiparametric AFM Insights into Electron Transport Mechanisms in Biomemristors

Biomemristors have attracted significant attention due to their applications in biodegradable and flexible electronic devices, and their prospective functions in information storage, neural synapses, and neuromorphic computation. Hence, understanding biomaterials' resistive switching (RS) mechanism is essential to design novel biomemristors with enhanced performance. In the last decade, various atomic force microscopy (AFM) modes, such as Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (cAFM), in situ/operando visualize the electron transport behaviors within biomemristors at the nanoscale. This review provides a comprehensive discussion of multiparametric AFM techniques to characterize biomemristors and inspire new ideas in developing next-generation consumer electronics. We also summarize the progress of revealing the internal mechanism of biomemristors with functional AFM to visualize and understand the switching behavior. Finally, the opportunities and challenges of further utilizing multiparametric AFM to explore the electron transport mechanisms in biomemristors are presented.

Shi, Chenyang↗
DOE OSTI2021

Predicting the onset of metal-insulator transitions in transition metal oxides-A first step in designing neuromorphic devices.

Several transition metal oxides, including La1-xSrxCoO3, are promising materials to realize resistive switching devices for neuromorphic applications, as they can undergo a metal-to-insulator transition (MIT) upon small perturbations to their electronic structure. Here, we focus on the MIT induced by varying the oxygen vacancy concentration, and we propose a model to predict the required electrical bias, based on three fundamental quantities: the vacancy formation energy, the permanent polarization in the material, and its dielectric constant. We obtain these quantities using first-principles electronic structure calculations, and we discuss strategies to minimize the electrical bias which may be adopted experimentally to design and optimize neuromorphic devices.

Zhang, Shenli↗
DOE OSTI2024

Localized Conduction Channels in Memristors

Since the early 2000s, the impending end of Moore’s scaling, as the physical limits to shrinking transistors have been approached, has fueled interest in improving the functionality and efficiency of integrated circuits by employing memristors or two-terminal resistive switches. Formation (or avoidance) of localized conducting channels in many memristors, often called “filaments”, has been established as the basis for their operation. While we understand some qualitative aspects of the physical and thermodynamic origins of conduction localization, there are not yet quantitative models that allow us to predict when they will form or how large they will be. Here, in this work, we compile observations and explanations of channel formation that have appeared in the literature since the 1930s, show how many of these seemingly unrelated pieces fit together, and outline what is needed to complete the puzzle. This understanding will be a necessary predictive component for the design and fabrication of post-Moore’s-era electronics.

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

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. In this report we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Electron Doping-Induced Metal–Insulator Transition in LaNiO 3 and Memory Devices

LaNiO 3 (LNO) is the only rare-earth nickelate that does not undergo a temperature-driven insulator-metal transition. Here, we report the successful deposition of epitaxial LNO thin films on LaAlO 3 substrates by a chemical solution deposition method. We report a metal-insulator transition driven by electron doping from hydrogen using catalytic Pd electrodes. A series of in-plane devices with LNO thin films and Pd-Au as the two working terminals were designed and fabricated by photolithography. Further, we report their resistance switching behavior and synaptic multiresistance states under voltage pulses. The results demonstrate the universality of electron doping-driven phase transitions in the rare-earth nickelates and their relevance to emerging memory and computing technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Integration of CeO 2 -Based Memristor with Vertically Aligned Nanocomposite Thin Film: Enabling Selective Conductive Filament Formation for High-Performance Electronic Synapses

The CeO 2 -based memristor has attracted significant attention due to its intrinsic resistive switching (RS) properties, large on/off ratio, and great plasticity, making it a promising candidate for artificial synapses. However, significant challenges such as high power consumption and poor device reliability hinder its broad application in neuromorphic microchips. To tackle these issues, in this work, we design a novel bilayer (BL) memristor by integrating a CeO 2 -based memristor with a Co-CeO 2 vertically aligned nanocomposite (VAN) layer and compare it with the single layer (SL) memristor. Preliminary electrical testing reveals that the BL memristor offers a reduced set/reset voltage (~67% lower), a higher on/off ratio (~5 × 10 2 ), enhanced device reliability, and improved device-to-device variation compared to the SL memristor. Insight from COMSOL simulation, coupled with microstructural analysis, provides a comprehensive elucidation on how the VAN layer facilitates the selective conductive filament (CF) formation. Subsequently, the plasticity of the BL memristor is evaluated through long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-time-dependent plasticity (STDP). The spiking neural network (SNN) built upon the BL memristor achieves remarkable accuracy (~94%) after only 12 iterations, underscoring its potential for high-performance neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗
DOE OSTI2020

Time- and strain-dependent nanoscale structural degradation in phase change epitaxial strontium ferrite films

Topotactic phase transition between metallic, perovskite SrFeO 3 and insulating, Brownmillerite SrFeO 2.5 has been extensively studied due to the potential applications in resistive switching devices for neuromorphic computing. However, its practical utilization as memristors has been hindered by the structural instability of SrFeO 3 , which is often ascribed to the generation of oxygen vacancies to form SrFeO 3-δ . Here we reveal the dominating defects generated in SrFeO 3 epitaxial thin films are atomic scale gaps as a result of interfacial strain. Our correlated time- and strain-dependent measurements show that tensile strained SrFeO 3 films form vertical, nanoscale gaps that are SrO-rich, which are accountable for the observed metal-to-insulator transition over time. While compressively strained or small lattice mismatched SrFeO 3 films mainly yield horizontal gaps with a smaller impact on the in-plane transport. The atomic scale origin of such defects and their impact on device performance need to be further understood in order to integrate phase change materials in oxide electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A caloritronics-based Mott neuristor

Abstract Machine learning imitates the basic features of biological neural networks at a software level. A strong effort is currently being made to mimic neurons and synapses with hardware components, an approach known as neuromorphic computing. While recent advances in resistive switching have provided a path to emulate synapses at the 10 nm scale, a scalable neuron analogue is yet to be found. Here, we show how heat transfer can be utilized to mimic neuron functionalities in Mott nanodevices. We use the Joule heating created by current spikes to trigger the insulator-to-metal transition in a biased VO 2 nanogap. We show that thermal dynamics allow the implementation of the basic neuron functionalities: activity, leaky integrate-and-fire, volatility and rate coding. This approach could enable neuromorphic hardware to take full advantage of the rapid advances in memristive synapses, allowing for much denser and complex neural networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗