Resistive Switching Materials Research Articles

Preparation and patterning of HfO2 film via sol–gel method and resistive switching effect of Pt/HfO2/LaNiO3

Sol–gel method is a low-cost material preparation method; however, it is difficult to obtain a stable sol containing easily hydrolyzable metal ions via this method. In this study, a stable hafnium(IV) oxide (HfO2) sol was prepared by adding benzoyl acetone (BzAcH) modifier. Infrared absorption spectroscopy results showed that the BzAcH additive chelated with the Hf4+ ions in the sol, thus improving the hydrolysis resistance of the HfO2 sol, which in turn improved its stability. It was also found that the BzAcH-modified HfO2 gel film exhibited ultraviolet (UV) photosensitivity. After UV exposure, the film did not dissolve easily in organic solvents. Based on these properties, the micro processing of the HfO2 film was preliminarily explored, and HfO2 microstructures were successfully obtained. Additionally, the relative permittivity (εr) of HfO2 exhibited minimum (∼10.9) and maximum (∼20.6) values at heat-treatment (HT) temperatures of 350 and 450 °C, respectively. With the continuous increase in the HT temperature, εr first decreased and then increased slightly. Moreover, the current–voltage curves showed that the Pt/HfO2/LaNiO3 (LNO) structure exhibited a pronounced bipolar resistive switching (RS) effect, which was attributed to the fact that LNO could be used as an electrode and an oxygen vacancy (OV2+) storage layer for RS materials. Notably, the oxygen ions in HfO2 with a low degree of crystallinity are more likely to migrate within its body (which makes it easier to form OV2+s), therefore, the “Set” voltage of low-crystallinity HfO2 films is lower than that of high-crystallinity HfO2 films. The RS mechanism can be explained by the OV2+ conductive filament model. These results are of great practical significance for the low-cost preparation of HfO2 and the application of LNO as an oxide electrode.

Formation-free resistive switching in nanocrystalline tellurium oxide

In this work, we report on the observation of resistive switching (RS) in the nanocrystalline tellurium oxide (TeO x ) in ITO/TeO x /Ag device configuration. The TeO x films grown in an O2/Ar environment have dominant β-TeO2 along with other polymorphs and amorphous TeO2. From the RS characteristics, it is suggestive that the β-TeO2 phase promotes the conductive filament formation across the highly insulating amorphous matrix. The memory device demonstrates bipolar RS with excellent endurance, retention and on–off ratio. The device also features formation-free switching with low set and reset voltage (0.6 V and −0.8 V respectively) and displays multilevel switching upon varying compliance current. Current-Voltage characterization clarifies the conduction path is indeed filamentary type. The result highlights that TeO x can be a prominent RS material for memory and brain-inspired computing devices.

Investigation of Resistive Switching of Insulating Hafnium Nitride for Nonvolatile Memory Applications

In this study, nitrogen-rich Hafnium Nitride (HfN) featuring insulating properties was investigated for achieving resistive switching, crucial for the functionality of resistive random-access memory (ReRAM) devices. Devices were fabricated with a 15-nm HfN resistive switching layer using a Radio Frequency (RF) sputtering system. The fabricated devices successfully exhibited a bipolar switching characteristic with a high On/Off ratio (up to 104). An interesting 2-step behavior was also observed during the formation of the conduction filament which was suspected to be tied to the migration of the nitrogen ions. This is the first attempt at using HfN as the resistive switching material for nonvolatile memory applications.

Elucidating dynamic conductive state changes in amorphous lithium lanthanum titanate for resistive switching devices

Exploration of novel resistive switching materials attracts attention to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Battery materials priorly used to serve as an electrode or electrolyte have demonstrated metal-insulator transitions upon an electrical biasing due to resulting compositional change, which is desirable property for future resistive switching devices. For example, it has been suggested that solid-state electrolyte amorphous lithium lanthanum titanate (a-LLTO) changes in electronic conductivity depending on oxygen content. In this work, switching behavior of a-LLTO was investigated at both bulk- and nano-scale by employing a range of voltage sweep techniques, ultimately establishing a stable and optimal operating condition within the voltage window of − 3.5 V to 3.5 V. This voltage range effectively balances the desirable trait of a substantial resistance change by three orders of magnitude with the imperative avoidance of LLTO decomposition. Experiment and computation with different LLTO composition shows that LLTO has two distinct conductivity states due to Ti reduction. The distribution of these two states is discussed using simplified binary model, implying the conductive filament growth during low resistance state. Consequently, our study deepens understanding of LLTO electronic properties and encourages the interdisciplinary application of battery materials for resistive switching devices.

Emerging Robust Polymer Materials for High-Performance Two-Terminal Resistive Switching Memory.

Facing the era of information explosion and the advent of artificial intelligence, there is a growing demand for information technologies with huge storage capacity and efficient computer processing. However, traditional silicon-based storage and computing technology will reach their limits and cannot meet the post-Moore information storage requirements of ultrasmall size, ultrahigh density, flexibility, biocompatibility, and recyclability. As a response to these concerns, polymer-based resistive memory materials have emerged as promising candidates for next-generation information storage and neuromorphic computing applications, with the advantages of easy molecular design, volatile and non-volatile storage, flexibility, and facile fabrication. Herein, we first summarize the memory device structures, memory effects, and memory mechanisms of polymers. Then, the recent advances in polymer resistive switching materials, including single-component polymers, polymer mixtures, 2D covalent polymers, and biomacromolecules for resistive memory devices, are highlighted. Finally, the challenges and future prospects of polymer memory materials and devices are discussed. Advances in polymer-based memristors will open new avenues in the design and integration of high-performance switching devices and facilitate their application in future information technology.

Solution-Processed Hydrogen-Bonded Organic Framework Nanofilms for High-Performance Resistive Memory Devices.

The integration of hydrogen-bonded organic frameworks (HOFs) into electronic devices holds great promise due to their high crystallinity, intrinsic porosity, and easy regeneration. However, despite their potential, the utilization of HOFs in electronicdevices remains largely unexplored, primarily due to the challenges associated with fabricating high-quality films. Herein, a controlled synthesis of HOFnanofilms with smooth surface, good crystallinity, and high orientation is achieved using a solution-processed approach. The memristors exhibit outstanding bipolar switching performance with alow set voltage of 0.86V, excellent retention of 1.64 × 104 s, and operational endurance of 60 cycles. Additionally, these robust memristors display remarkable thermal stability, maintaining their performance even at elevated temperatures of up to 200 °C. More strikingly, scratched HOFfilms can be readily regenerated through a simple solvent rinsing process, enabling their reuse for the fabrication of new memristors, which is difficult to achieve with traditional resistive switching materials. Additionally, a switching mechanism based on the reversible formation and annihilation of conductive filaments is revealed. This work provides novel and invaluable insights that have a significant impact on advancing the widespread adoption of HOFs as active layers in electronic devices.

Effects of BiFeO3 Thickness on the Write‐Once‐Read‐Many‐Times Resistive Switching Behavior of Pt/BiFeO3/LaNiO3 Heterostructure

Thickness of the resistive switching materials is an essential factor to determine the integration density of resistive switching devices. Herein, the effect of the thickness of BFO on the write‐once‐read‐many‐times (WORM) resistive switching behavior of Pt/BFO/LNO‐based devices is investigated. The thicknesses of BFO thin films are controlled in the range of 70–220 nm. All the devices exhibit WORM resistive switching behavior with high ON/OFF ratio (≈10−2–10−4), long‐term data retention (>3600 s), and reliable endurance (>1000 cycles). The set voltages (Vset) of the devices exhibit an approximately linear relation to the BFO thicknesses, while the highest ON/OFF ratio appears in the device with BFO thickness of 150 nm. The thickness‐dependent resistive switching characteristic is attributed to the variation of oxygen vacancies and OFF state resistances with the increase of BFO thickness. The results underline the importance of the thickness of resistive switching materials for the future device applications.

Resistive switching localization by selective focused ion beam irradiation

Materials displaying resistive switching have emerged as promising candidates for implementation as components for neuromorphic computing. Under an applied electric field, certain resistive switching materials undergo an insulator-to-metal transition through the formation of a percolating filament, resulting in large resistance changes. The location and shape of these filaments are strongly influenced by hard-to-control parameters, such as grain boundaries or intrinsic defects, making the switching process susceptible to cycle-to-cycle and device-to-device variation. Using focused Ga+ ion beam irradiation, we selectively engineer defects in VO2 and V2O3 thin films as a case study to control filament formation. Using defect pre-patterning, we can control the position and shape of metallic filaments and reduce the switching power significantly. A greater than three orders of magnitude reduction of switching power was observed in V2O3, and a less than one order of magnitude reduction was observed in VO2. These experiments indicate that selective ion irradiation could be applied to a variety of materials exhibiting resistive switching and could serve as a useful tool for designing scalable, energy efficient circuits for neuromorphic computing.

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. 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.

Engineering of Grain Boundaries in CeO2 Enabling Tailorable Resistive Switching Properties

AbstractDefect 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 CeO2 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.

2D Ti3C2Tx MXene-derived self-assembled 3D TiO2nanoflowers for nonvolatile memory and synaptic learning applications

Two-dimensional (2D) semiconducting materials and transition-metal oxides are promising materials for nonvolatile memory and brain-inspired neuromorphic computing applications. However, it remains challenging to obtain high-quality stacked 2D films with low energy consumptions (or drive currents) because of their high interfacial resistance. In this study, we synthesized 2D Ti3C2Tx MXene-derived three-dimensional (3D) TiO2 nanoflowers (NFs) as a feasible resistive switching (RS) material with outstanding electronic properties and synaptic learning capabilities. The electrical and optical characteristics of the synthesized material were determined through density functional theory calculations. Electrical measurements of the Al/Ti3C2Tx-TiO2 NF/Pt memory device indicated the occurrence of forming-free switching phenomena with extremely low switching voltages (0.68–0.53 V), stable ON/OFF ratio (2.3 × 103), and retention greater than 105 s. The Holt–Winters exponential smoothing technique was used for modeling and predicting the switching voltages of the RS device. The mechanism underlying the reliable RS was confirmed by observing the dense conductive filaments through conductive atomic force microscopy. Interestingly, the 2D Ti3C2Tx MXene-derived 3D TiO2 NF-based RS device mimicked the potentiation/depression and spike-time-dependent plasticity of a biological synapse. Finally, a convolutional neural network was implemented based on the observed synaptic weights of Al/Ti3C2Tx-TiO2 NF/Pt for image-edge detection.

Intact Metal/Metal Halide van der Waals Junction Enables Reliable Memristive Switching with High Endurance

AbstractOrganic–inorganic or inorganic metal halide materials have emerged as a promising candidate for a resistive switching material owing to their ability to achieve low operating voltage, high on–off ratio, and multi‐level switching. However, the high switching variation, limited endurance, and poor reproducibility of the device hinder practical use of the memristors. In this study, a universal approach to address the issues using a van der Waals metal contact (vdWC) is reported. By transferring the pre‐deposited metal contact onto the active layers, an intact junction between the metal halide and contact layer is formed without unintended damage to the active layer caused by a conventional physical deposition process of the metal contacts. Compared with the thermally evaporated metal contact (EVC), the vdWC does not degrade the optoelectronic quality of the underlying layer to enable memristors with reduced switching variation, significantly enhanced endurance, and reproducibility relative to those based on the EVC. By adopting various metal halide active layers, versatile utility of the vdWC is demonstrated. Thus, this vdWC approach can be a useful platform technology for the development of high‐performance and reliable memristors for future computing.

Perovskite-phase interfacial intercalated layer-induced performance enhancement in SrFeO<sub><i>x</i></sub>-based memristors

SrFeO<sub><i>x</i></sub> (SFO) is a kind of material that can undergo a reversible topotactic phase transformation between an SrFeO<sub>2.5</sub> brownmillerite (BM) phase and an SrFeO<sub>3</sub> perovskite (PV) phase. This phase transformation can cause drastic changes in physical properties such as electrical conductivity, while maintaining the lattice framework. This makes SFO a stable and reliable resistive switching (RS) material, which has many applications in fields like RS memory, logic operation and neuromorphic computing. Currently, in most of SFO-based memristors, a single BM-SFO layer is used as an RS functional layer, and the working principle is the electric field-induced formation and rupture of PV-SFO conductive filaments (CFs) in the BM-SFO matrix. Such devices typically exhibit abrupt RS behavior, i.e. an abrupt switching between high resistance state and low resistance state. Therefore, the application of these devices is limited to the binary information storage. For the emerging applications like neuromorphic computing, the BM-SFO single-layer memristors still face problems such as a small number of resistance states, large resistance fluctuation, and high nonlinearity under pulse writing. To solve these problems, a BM-SFO/PV-SFO double-layer memristor is designed in this work, in which the PV-SFO layer is an oxygen-rich interfacial intercalated layer, which can provide a large number of oxygen ions during the formation of CFs and withdraw these oxygen ions during the rupture of CFs. This allows the geometric size (e.g., diameter) of the CFs to be adjusted in a wide range, which is beneficial to obtaining continuously tunable, multiple resistance states. The RS behavior of the designed double-layer memristor is studied experimentally. Compared with the single-layer memristor, it exhibits good RS repeatability, small resistance fluctuation, small and narrowly distributed switching voltages. In addition, the double-layer memristor exhibits stable and gradual RS behavior, and hence it is used to emulate synaptic behaviors such as long-term potentiation and depression. A fully connected neural network (ANN) based on the double-layer memristor is simulated, and a recognition accuracy of 86.3% is obtained after online training on the ORHD dataset. Comparing with a single-layer memristor-based ANN, the recognition accuracy of the double-layer memristor-based one is improved by 69.3%. This study provides a new approach to modulating the performance of SFO-based memristors and demonstrates their great potential as artificial synaptic devices to be used in neuromorphic computing.

Theoretical expolartion of site selective Perovskites for the application of electronic and optoresponsive memory devices

Now a days, the advent of energy efficient artificial neuromorphic hardware is facing variability and uniformity related state of art issues. DFT deals with this plethora at the atomistic level by introducing innovative composites of improved neuromorphic performance. In this theoretical study unprecedented potential of non-toxic and high dielectric strength of BaHfO 3 is investigated for storage devices. For improving the variability and uniformity related state of art issues, the influence of substitutional doping ofsingle rare earth metal cation at “A” (Ba atom) and “B” (Hf atom) sites of the studied cubic ABO 3 supercell is explored in formation of conducting filaments (CFs). Formation of strongly confined CFs in BaHf 1-x SmO 3 will provide an intriguing roadmap for practical application by resolving the variability and uniformity issues in electronic and optoresponsive memory devices. Alterations of structural and electronic properties by single rare earth dopants will assist in understanding the filamentary based resistive switching in BaHfO 3 . Change in resistance state caused by incident photon stimuli based extrinsic trigger revealed the intriguing neuromorphic nature of BaHfO 3 . The findings of this study will enrich the research exploring the perovskite based resistive switching materials for low power consuming resistive random access memory devices in neuromorphic applications. • The electronic modification subsequently with the creation of the rare earth metal (REM) ion dopant in cubic BaHfO 3 using Perdew-Burke-Ernzerhof Generalized gradient approximation (PBE-GGA) in addition to Hubbered parameter (GGA + U) are performed to investigate the A (Ba atom) and B (Hf atom) site impact of REM (Ce, La, Sm) dopant for switching process and application of optoelectronic devices. • Electronic properties showed sensitivity towards A and B site doping. • Integrated charge density plots depicted charge transfer mechanism. • The conductivity of the phases increased with substitutional replacement of A and B site atom by REM; and eventually resulted that the considered phase opted for low resistance state. • BaHf (1-x) Sm x O 3 is found to be composite with better optoelectronic properties.

An ab initio investigation of the structural, mechanical, electronic, optical, and thermoelectric characteristics of novel double perovskite halides Cs2CaSnX6 (X = Cl, Br, I) for optically influenced RRAM devices.

Hybrid lead halide perovskites have been considered as promising candidates for a large variety of optoelectronic applications. By exploring novel combinations of lead-free double perovskite halides, it is possible to find a suitable replacement for poisonous lead halide perovskites, enhancing electronic and optical response for their application as optically-influenced resistive switching random access memory (RRAM). In this work, the structural, mechanical, elastic, electronic, optical, and thermoelectric characteristics of lead-free double halide perovskites were investigated by Vienna ab initio simulation package (VASP) to explore their role in RRAM. From the analysis of mechanical constraints, it is clear that all three composites of Cs2CaSnX6 (X = Cl, Br, I) are mechanically stable and ductile in nature. The electronic bandgap with and without spin-orbit coupling (SOC), and total and sub-total density of states (TDOS, sub-TDOS) have been calculated using the Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA) potentials. The observed direct band gaps of 3.58 eV, 3.09 eV, and 2.60 eV for Cs2CaSnCl6, Cs2CaSnBr6, and Cs2CaSnI6, respectively, reveal the suitability of these specified composites as resistive switching material for RRAM devices. Additionally, the optical characteristics, such as complex refractive index, absorption coefficient, and reflectivity of the compounds under consideration have been calculated under the action of incident photons of 0 to 14 eV energy. The thermoelectric properties of Cs2CaSnX6 (X = Cl, Br, I) double perovskite halide were computed and analyzed with the help of the BoltzTraP Code.

Investigation of α-Fe2O3 and Cr dopedα-Fe2O3 Based Nano-Film as Resistive Switching Material for ReRAM Device Application

Investigation of α-Fe2O3 and Cr dopedα-Fe2O3 Based Nano-Film as Resistive Switching Material for ReRAM Device Application

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.

Interfacial Resistive Switching by Multiphase Polarization in Ion-Intercalation Nanofilms.

Nonvolatile resistive-switching (RS) memories promise to revolutionize hardware architectures with in-memory computing. Recently, ion-interclation materials have attracted increasing attention as potential RS materials for their ion-modulated electronic conductivity. In this Letter, we propose RS by multiphase polarization (MP) of ion-intercalated thin films between ion-blocking electrodes, in which interfacial phase separation triggered by an applied voltage switches the electron-transfer resistance. We develop an electrochemical phase-field model for simulations of coupled ion-electron transport and ion-modulated electron-transfer rates and use it to analyze the MP switching current and time, resistance ratio, and current-voltage response. The model is able to reproduce the complex cyclic voltammograms of lithium titanate (LTO) memristors, which cannot be explained by existing models based on bulk dielectric breakdown. The theory predicts the achievable switching speeds for multiphase ion-intercalation materials and could be used to guide the design of high-performance MP-based RS memories.

Continual Learning Electrical Conduction in Resistive‐Switching‐Memory Materials

AbstractThe authors apply the concept of continual learning to modeling conductive‐filament growth in resistive‐switching materials (RSM). The approach permits computation of compliance current without knowing the geometries of conductive filaments and switching behaviors. This avoids the need to retrain the entire dataset when additional compliance currents are considered and is thus ideal for resistive switching (RS) thin films, doped layers, and other material systems. Computation of compliance current is consistent with experimental data for a wide range of parameters and learning tasks and demonstrates switching behavior not captured by traditional models. Lesion calculations elucidate the brain‐inspired‐modification‐facilitated increase in compliance‐current‐computation‐accuracy. A state‐of‐the‐art performance on challenging compliance‐current learning tasks without storing data is achieved (“brain inspired replay (BIR) – gating based on internal context (Gat)” method, ≈89%; above a benchmark of ≈50% for synaptic‐intelligence (SI)/elastic‐weight‐consolidation (EWC) methods), and it provides a novel model for computing compliance current based on replay of the brain. This intuitive approach combined with a simple solver tool, allows researchers with little computation experience to perform realistic and accurate modeling.

Systematic Evolution of Optical Bandgap and Local Chemical State in Transparent MgO and HfO2 Resistive Switching Materials

Herein, a comprehensive investigation into the optical, local chemical state, and electrical properties of the less explored magnesium oxide (MgO) are presented for resistive switching data storage applications in reference to the well‐documented hafnium oxide (HfO2). The observed local chemical state from X‐ray photoelectron spectroscopy (XPS) analysis yields a nonlattice oxygen peak in O 1s spectra, indicating the resistive switching potential of polycrystalline MgO analogous to the amorphous HfO2 as‐deposited thin films. The optical investigation through UV–visible spectroscopic and photoluminescence examination reveals the high transmissivity of HfO2 (84–98%) and MgO (86–88%) thin films in visible and near‐infrared domains, with a high bandgap of 5.6 and 4.2 eV, respectively, implying the possibility of two distinct stable states essential for resistive switching phenomena. Additionally, the electrical characterization manifests bipolar switching phenomena in HfO2 and MgO metal–oxide–metal stacks with SET transitions at 0.6 and 0.5 V, followed by RESET transitions at −0.6 and −0.5 V, respectively. Both oxides in respective stacks exhibit dominant Ohmic conduction in high‐resistive and low‐resistive regions during positive and negative bias. These observations propose MgO as a preferable resistive switching material for nonvolatile data storage applications, showing similar properties of widely studied HfO2.