Resistive Switching Research Articles

Large resistive switching in ultrathin BiFeO3 thin films

Electrically induced resistive switching (RS) effects have been proposed as the basis for future non-volatile memories. In this work, 9 nm-thick BiFeO3 (BFO) epitaxial thin films were deposited on (001)-oriented SrTiO3 substrates by pulsed laser deposition and their resistive switching (RS) behaviors were investigated. A large resistive switching with ON/OFF ratio of ∼106 is observed, surpassing the performance of most resistive random access memories ever reported. The conducting filament is proposed to dominate the RS behavior in the positive voltage region, while the modulation of ferroelectric polarization is suggested to play a significant role in the negative voltage region. Our study significantly deepens the understanding of the physical origin of RS and could provide a reference for designing high-performance memories and memristors based on ultrathin ferroelectric films.

A multilevel resistive switching memristor based on flexible organic–inorganic hybrid film with recognition function

Abstract Brain-inspired neuromorphic computing systems fueled the emergence of memristor-based artificial synapses, however, conventional silicon-based devices restricted their usage in the wearable field because of their difficulty in bending. To tackle the above challenge, a vertically structured flexible memristor with aluminum-based hydroquinone organic–inorganic hybrid film and Al2O3 as the functional layer, ITO and Pt as the bottom and top electrodes, and PET as the substrate has been developed utilizing molecular/atomic layer deposition to achieve a tradeoff between the resistive transition properties and the flexibility of memristors. The obtained devices combine stable resistive switching behavior and flexibility, showing high switching ratio of 103, better retention (up to 105 s) and endurance properties (up to 104 cycles), and robustness at radius of curvature of 4.5 mm after 104 bending cycles. Furthermore, the presence of multilevel resistive states in these devices ensures that the memristor can emulate synaptic properties such as paired-pulse facilitation, transition from short-term plasticity to long-term plasticity, long-term potentiation and depression, and spike-time-dependent plasticity. The resistive switching mechanism and the role of the bending state on the electrical performance of the device are explored. The fully connected artificial neural network based on the memristor can achieve a recognition accuracy of 90.2% for handwritten digits after training and learning. Flexible memristor will bring feasible advances to the integration of neuromorphic computing and wearable functionality.

Reset-Voltage Controlled Resistance-State and Applications of Forming-Free Fe-Doped SrTiO3 Thin-Film Memristor.

In this study, we prepared a strontium ferrite titanate (STF) thin film using a sol-gel process to insulate resistive random-access memory (RRAM) applications. Compared to the typical strontium titanate (STO) RRAM, the improvement in the resistive switching characteristics in STF RRAM is obvious. The Al/STO/ITO/Glass RRAM set/reset voltages of -1.4 V/+3.3 V and the Al/STF/ITO/Glass RRAM set/reset voltages of -0.45 V/+1.55 V presented a memory window larger than 103, a low operating voltage and device stability of more than 104 s. In this study, the influence of Fe on the conducting paths and the bipolar resistive switching properties of Al/STF/ITO/Glass RRAM devices is investigated.

The Role of Hydrogen in ReRAM.

Previous research on transistor gate oxides reveals a clear link between hydrogen content and oxide breakdown. This has implications for redox-based resistive random access memory (ReRAM) devices, which exploit soft, reversible, dielectric breakdown, as hydrogen is often not considered in modeling or measured experimentally. Here quantitative measurements, corroborated across multiple techniques are reported, that reveal ReRAM devices, whether manufactured in a university setting or research foundry, contain concentrations of hydrogen at levels likely to impact resistance switching behavior. To the knowledge this is the first empirical measurement depth profiling hydrogen concentration through a ReRAM device. Applying a recently-developed Secondary Ion Mass Spectrometry analysis technique enables to measure hydrogen diffusion across the interfaces of SiOx ReRAM devices as a result of operation. These techniques can be applied to a broad range of devices to further understand ReRAM operation. Careful control of temperatures, precursors, and exposure to ambient during fabrication should limit hydrogen concentration. Additionally, using thin oxynitride or TiO2 capping layers should prevent diffusion of hydrogen and other contaminants into devices during operation. Applying these principles to ReRAM devices will enable considerable, informed, improvements in performance.

Scalable In2S3 based optical memristor devices as artificial synapse for logic realization and neuromorphic computing

This paper presents the scalable production of indium sulfide (In2S3) based optical memristors as an artificial synapse for logic realization and neuromorphic computing applications. The optical memristor device's performance was tested using the electrical and optical stimulation (ultraviolet (UV) to near infrared (NIR)) at room temperature. The memristor has shown the improved performance metrics for optical stimulation as compared to electrical stimulation. The In2S3 based optical memristor offers a resistance switching ratio of ∼103 at room temperature. In addition, the memristor has ultra-fast program and reprogram capability (38.8/39 μs) at 880 nm. Moreover, stability/scalability of the device was tested using the cycle-to-cycle variability test at different modulated frequencies. The electrical and optical signals were used as an input for logic gate realization. The neuromorphic computing model was implemented to predict the digits and alphabets with an accuracy of 98.19 % and 99.18 % respectively. These demonstrated optical memristors can be the key technology for future memory devices that surpass the limitations of von-Neumann bottleneck.

Effects of Halide Composition on Endurance and Retention Performance in Double Perovskite Resistive Switching Memory

Effects of Halide Composition on Endurance and Retention Performance in Double Perovskite Resistive Switching Memory

Oxygen vacancy order–disorder transition process during topotactic filament formation in a perovskite oxide tracked by Raman microscopy and transmission electron microscopy

Vacancy-ordered perovskite oxides are attracting attention due to their diverse functions such as resistive switching, electrocatalytic activity, oxygen diffusivity, and ferroelectricity. It is important to clarify the chemical lattice strains arising from compositional changes and the associated vacancy order–disorder phase transitions at the atomic scale. Here, we elucidate the intermediate process of a topotactic phase transition in Ca-doped bismuth ferrite films consisting of alternating stacks of oxygen perovskite layers and a brownmillerite-type oxygen vacancy layer. We use Raman spectroscopy and transmission electron microscopy to closely examine the evolution of local strains exerted on the constituent sub-layers by electrochemical oxidation. A negative Raman chemical shift is observed during oxidation, which is linearly correlated with the local negative chemical expansivity of the oxygen layer. It seemingly contradicts with the general trend that oxides undergo lattice contraction upon oxidation. Oxygen vacancies initially confined in the vacancy layers can be understood to diffuse into the oxygen layers during melting of the ordered structure. The finding deepens our understanding of the electro-chemo-mechanical coupling of vacancy-ordered oxides.

Analog‐Digital Hybridity of Resistive Switching in Ion‐Irradiated BiFeO3 Memristor for Synergistic Neuromorphic Functionality and Artificial Learning

AbstractMemristors‐based neuromorphic devices represent emerging computing architectures to perform complex tasks by outpacing the traditional Von‐Neumann architectures in terms of speed, and energy efficiency. In this work, the resistive switching (RS) behavior of sol‐gel grown and ion‐irradiated BFO films is investigated under electrical stimulus. The Ag/BFO/FTO memristors emulate a combination of digital and analog RS behavior within a single device. The possible mechanism of analog digital hybridity is addressed by considering the formation of the conducting filament by oxygen vacancies, Ag+ ions and Schottky barrier height modulation. The ion‐irradiated BFO samples are analyzed using the Raman, XRD, and XPS studies. To uphold bioinspired synaptic actions, crucial synaptic functionalities like pair‐pulse facilitation and long‐term potentiation/depression are effectively achieved. More intricate synaptic behaviors are also demonstrated such as spike‐time‐dependent plasticity and Pavlovian classical conditioning, which represent the prominent attributes of both learning and forgetting behavior. Additionally, high pattern recognition accuracy (96.1%) is achieved in an artificial neural network simulation by using the synaptic weights of the memristors. This synergistic effect of digital and analog RS in ion‐irradiated BFO can be beneficial for the emulation of complex learning behavior as well as its incorporation into low‐power neuromorphic computing.

Impact of electrical testing strategies on the performance metrics of bio-organic-based resistive switching memory

Impact of electrical testing strategies on the performance metrics of bio-organic-based resistive switching memory

Robust resistance switching performance in a Ca3Ti2O7/La0.67Sr0.33MnO3 heterostructure induced by the interface

Ruddlesden–Popper phase oxides, such as Ca3Ti2O7, have been established as hybrid improper ferroelectrics. However, investigations into Ca3Ti2O7 have primarily concentrated on their structural and ferroelectric properties. In this study, we prepared epitaxial Ca3Ti2O7 thin films via magnetron sputtering. Conducting atomic force microscopy was employed to characterize local current variations under an applied bias voltage. Electron paramagnetic resonance measurements of the Ca3Ti2O7/La0.67Sr0.33MnO3 film were conducted to assess its defect characteristics. Interestingly, the Ca3Ti2O7/La0.67Sr0.33MnO3 stacks exhibited remarkable macroscopic resistance switching, with a resistance on/off ratio reaching 100, alongside robust retention (∼2500 s) and endurance (∼2000 cycles) features. Additionally, density functional theory calculations suggest that the resistance switching is attributable to the interface barrier of the Ca3Ti2O7/La0.67Sr0.33MnO3 interface and the efficacy of space charge limitation. This work proposes an avenue for the utilization of Ruddlesden–Popper phase Ca3Ti2O7 in various applications.

Effect of SiCN thin film interlayer for ZnO-based RRAM.

This study investigates the effect of silicon carbon nitride (SiCN) as an interlayer for ZnO-based resistive random access memory (RRAM). SiCN was deposited using plasma-enhanced chemical vapor deposition (PECVD) with controlled carbon content, achieved by varying the partial pressure of tetramethylsilane (4MS). Our results indicate that increasing the carbon concentration enhances the endurance of RRAM devices but reduces the on/off ratio. Devices with SiCN exhibited lower operating voltages and more uniform resistive switching behavior. Oxygen migration from ZnO to SiCN is examined by X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses, promoting the formation of conductive filaments (CFs) and lowering set voltages. Additionally, we examined the impact of top electrode oxidation on RRAM performance. The oxidation of the Ti top electrode was found to reduce endurance and increase low resistive state (LRS) resistance, potentially leading to device failure through the formation of an insulating layer between the electrode and resistive switching material. The oxygen storage capability of SiCN was further confirmed through high-temperature stress tests, demonstrating its potential as an oxygen reservoir. Devices with a 20 nm SiCN interlayer showed significantly improved endurance, with over 500 switching cycles, compared to 62 cycles in those with a 5 nm SiCN layer. However, the thicker SiCN layer resulted in a notably lower on/off ratio due to reduced capacitance. These findings suggest that SiCN interlayers can effectively enhance the performance and endurance of ZnO-based RRAM devices by acting as an oxygen reservoir and mitigating the top electrode oxidation effect.

Synaptic Feature of Quantum Dot Light-Emitting Diodes for Visualization of Learning Process.

Brain-inspired electronics with synaptic functions hold significant promise for advancing artificial intelligent applications. In this study, we demonstrate the synaptic feature of quantum-dot light-emitting diodes (QLEDs), which can convert electrical pulses into synapse-like light signals (the brightness gradually increases as the electrical pulses are prolonged). These features are analogous to learning and forgetting in biological synapses. The enhancement of brightness can be attributed to the reduction of charge transfer from the quantum dots to ZnO electron transport layer and resistive switching effect. With an integrated complementary metal-oxide-semiconductor (CMOS) drive, arrayed synaptic QLEDs can simulate the visualization of brain-like learning processes, which can reduce the noise toward high image recognition rate (>95.0%) by deep neural networks. Our findings introduce a novel brain-inspired optoelectronic approach with potential applications in optical neuromorphic systems.

Controlling the digital-to-analog switching in HfO2-based memristors via modulating the oxide thickness

The HfO2-based memristors have been acknowledged as a highly potential candidate for nonvolatile memory and neuromorphic computing applications. However, the analog resistive switching behavior of the HfO2-based memristors still needs improvement. In this work, Cu/HfO2/Pd devices with different oxide layer thicknesses were prepared by the magnetron sputtering process. The resistance switching characteristics related to oxide layer thickness were explored, revealing significant differences in the forming, SET, and RESET characteristics depending on oxide thickness. The conduction mechanism of the Cu/HfO2/Pd memristors is mainly attributed to the space charge limited current (SCLC) model. Thinner devices tend to show a more abrupt SET behavior and larger SET voltage, while thicker devices exhibit more gradual SET behavior and a lower SET voltage. In addition, as the thickness of the oxide layer increases, the Cu/HfO2/Pd memristors transition from digital resistive switching to analog resistive switching. The formation and rupture of oxygen vacancy filaments are predominant in thicker device, and the shape of the conduction filaments has been proposed as responsible for the abrupt and gradual changes in resistive switching. This work demonstrates that the thickness of the oxide layer plays an important role in engineering digital logic and neuromorphic behavior in HfO2-based memristors.

LiNbO3-based ferroelectric tunnel junctions with changeable electroresistance for data storage

Ferroelectric tunnel junctions (FTJs) have attracted considerable attention for potential applications in the next-generation data storage technologies. In this work, we have grown high-quality LiNbO3 single crystal films on STO (111) substrates by rotational epitaxy. The certain ferroelectricity was achieved in nanoscale epitaxial LiNbO3 films. Then, the Au/LiNbO3/Nb: SrTiO3 FTJ was fabricated, and the nonvolatile resistive switching controlled by the nonvolatile polarization switching was observed. The Au/LiNbO3/Nb: SrTiO3 FTJs regulate the quantum tunneling effect through ferroelectric polarization reversal to obtain multi-level resistive states, thereby achieving data storage functionality. At room temperature, the ON/OFF current ratio can exceed 103. Furthermore, the FTJs also exhibit excellent retention for more than 103 s and good switching endurance for 2000 cycles. The results suggest the application potential of this LiNbO3-based FTJ for next generation nonvolatile ferroelectric memories.

Mechanisms of Defect-Mediated Memristive Behavior in MoS2 Monolayer.

The switching dynamics of a Au∥VS2@MoS2 atomristor is explored by first-principles computations of the atomic-configuration energy and electron transport. It is found that external bias can reduce the energy barrier between the two (high- and low-) conduction states, to achieve nonvolatile resistive switching. We find that the force acting on the switching atom is a combination of electrostatic force (while its charge is induced both electrostatically and chemically) and also by electron-wind, whose effect may hinder the writing process at larger bias. The analysis uncovers how the writing and reading processes of the atomristor depend on several factors: (i) atomic structure details of the Au tip; (ii) the space-gap distance between the tip and MoS2 layer; and (iii) tip metal choice. The fundamental understanding of switching events provides useful guidance for memristor design and possible limitations.

Enhanced Electrical Polarization in van der Waals α-In2Se3 Ferroelectric Semiconductor Field-Effect Transistors by Eliminating Surface Screening Charge.

A van der Waals (vdW) α-In2Se3 ferroelectric semiconductor channel-based field-effect transistor (FeS-FET) has emerged as a next-generation electronic device owing to its versatility in various fields, including neuromorphic computing, nonvolatile memory, and optoelectronics. However, screening charges cause by the imperfect surface morphology of vdW α-In2Se3 inhibiting electrical polarization remain an unresolved issue. In this study, for the first time, a method is elucidated to recover the inherent electric polarization in both in- and out-of-plane directions of the α-In2Se3 channel based on post-exfoliation annealing (PEA) and improve the electrical performance of vdW FeS-FETs. Following PEA, an ultra-thin In2Se3-3xO3x layer formed on the top surface of the α-In2Se3 channel is demonstrated to passivate surface defects and enhance the electrical performance of FeS-FETs. The on/off current ratio of the α-In2Se3 FeS-FET has increased from 5.99 to 1.84 × 106, and the magnitude of ferroelectric resistance switching has increased from 1.20 to 26.01. Moreover, the gate-modulated artificial synaptic operation of the α-In2Se3 FeS-FET is demonstrated and illustrate the significance of the engineered interface in the vdW FeS-FET for its application to multifunctional devices. The proposed α-In2Se3 FeS-FET is expected to provide a significant breakthrough for advanced memory devices and neuromorphic computing.

Non-Volatile Resistive Switching in Nanoscaled Elemental Tellurium by Vapor Transport Deposition on Gold.

Two-dimensional (2D) materials are promising for resistive switching in neuromorphic and in-memory computing, as their atomic thickness substantially improve the energetic budget of the device and circuits. However, many 2D resistive switching materials struggle with complex growth methods or limited scalability. 2D tellurium exhibits striking characteristics such as simplicity in chemistry, structure, and synthesis making it suitable for various applications. This study reports the first memristor design based on nanoscaled tellurium synthesized by vapor transport deposition (VTD) at a temperature as low as 100°C fully compatible with back-end-of-line processing. The resistive switching behavior of tellurium nanosheets is studied by conductive atomic force microscopy, providing valuable insights into its memristive functionality, supported by microscale device measurements. Selecting gold as the substrate material enhances the memristive behavior of nanoscaled telluriumin terms of reduced values of set voltage and energy consumption. In addition, formation of conductive paths leading to resistive switching behavior on the gold substrate is driven by gold-tellurium interface reconfiguration during the VTD process as revealed by energy electron loss spectroscopy analysis. These findings reveal the potential of nanoscaled tellurium as a versatile and scalable material for neuromorphic computing and underscore the influential role of gold electrodes in enhancing its memristive performance.

Synthesis of Copper Sulfides by Anion Substitution and their Resistive Switching Properties in the Presence of Cuprou‘s

AbstractCopper sulfides exhibit various significant physical properties and have wide potential applications. In order to synthesize copper sulfides and investigate the anion substitution possibility of Cu3P, we immersed Cu3P in sodium sulfide solution. From X‐ray diffraction spectra results, copper sulfides, namely Cu2S and Cu7.2S4, were observed, indicating that anion substitution between S2− and P3− ions did occur. Consequently, we investigated the resistive switching (RS) properties of these two phases in the presence of Cu3P. We found that the Cu2S‐Cu3P composite exhibited a high Off/On ratio (88) and a long retention time (>103 s). However, the Cu7.2S4‐Cu3P composite exhibited no RS performance. In addition, we discussed the conduction and resistive switching mechanisms. Our work enriches the preparation method of copper sulfides and provides a reference for enhancing RS performance.

Reliable resistive switching and synaptic simulation behaviors in ammonium polyphosphate-based memristor with non-inert Al electrode

Abstract Memristive devices that integrate storage and computing capabilities are highly promising candidates for artificial synapses in neuromorphic systems. However, achieving both cost-effectiveness and high-performance in memristors remains a substantial challenge. Ammonium polyphosphate (APP), an all-inorganic ionic polymer, has been utilized in the fabrication of memristive devices due to its distinctive poly-ionic properties and exceptional ion mobility. In this study, a two-terminal APP-based memristor with an Al/APP/ITO structure was fabricated. The experimental results revealed improved bipolar resistive switching behavior, characterized by lower operating voltages, enhanced endurance performance, and extended retention time. Detailed data fitting and chemical bonding analysis suggest that the physical mechanism underlying resistive switching involves a combination of interfacial Schottky barrier and conductive filaments. Furthermore, adjustable device conductance is achieved by applying consecutive positive and negative voltage sweeps. Various synaptic functions, including excitatory postsynaptic current, short-term paired-pulse facilitation, long-term potentiation /depression, and spike-timing-dependent plasticity, are effectively emulated. This study presents an effective approach to enhancing the memristive characteristics of APP-based devices and positions APP as a viable candidate for innovative neuromorphic architectures.

GeTe/MoTe2 Van der Waals Heterostructures: Enabling Ultralow Voltage Memristors for Nonvolatile Memory and Neuromorphic Computing Applications.

Advanced electronic semiconducting Van der Waals heterostructures (HSs) are promising candidates for exploring next-generation nanoelectronics owing to their exceptional electronic properties, which present the possibility of extending their functionalities to diverse potential applications. In this study, GeTe/MoTe2 HS are explored for nonvolatile memory and neuromorphic-computing applications. Sputter-deposited Ag/GeTe/MoTe2/Pt HS cross-point devices are fabricated, and they demonstrate memristor behavior at ultralow switching voltages (VSET: 0.15V and VRESET: -0.14V) with very low energy consumption (≈30 nJ), high memory window, long retention time (104 s), and excellent endurance (105 cycles). Resistive switching is achieved by adjusting the interface between the Ag top electrode and the heterojunction switching layer. Cross-sectional transmission electron microscope images and conductive atomic force microscopy analysis confirm the presence of a conducting filament in the heterojunction switching layer. Further, emulating various synaptic functions of a biological synapse reveals that GeTe/MoTe2 HS can be utilized for energy-efficient neuromorphic-computing applications. A multilayer perceptron is implemented using the synaptic weights of the Ag/GeTe/MoTe2/Pt HS device, revealing high pattern accuracy (81.3%). These results indicate that HS devices can be considered a potential solution for high-density memory and artificial intelligence applications.