Resistive Switching Materials Research Articles

Exploring the role of Germanium on the optoelectronic and thermoelectric response in making ductile lead-free perovskite halide using DFT

Abstract The structural instability observed owing to Sn2+ and the toxic effects of lead has prohibited the commercial use of all inorganic CsPb1-xSnxBr3 for optoelectronic memory device applications. In this work, we have inspected the structural, mechanical, electronic, optical, and thermoelectric response of all inorganic halide perovskite CsPb1-xGexBr3 (x = 0, 0.25, 0.50, 0.75, 1) to overcome the stability and toxicity of this optoelectronic resistive switching material using the full-potential linearized augmented-plane wave (FP-LAPW) technique grounded on density functional theory (DFT). Tran Blaha-modified Becky Johnson (TB-mBJ) approximation is used for the self-consistent field (SCF) calculations of considered halide perovskite CsPb1-xGexBr3. It is clear from the band structure that all compounds are semiconductors in nature. Moreover, the bandgap decreased with the increase in the concentration of Germanium (Ge) caused thebandgap tununig. The overall absorption of incident radiations increased and energy loss decreased with the increase in the concentration of doping, especially in the visible region. The thermoelectric properties have also been studied by using the BoltzTraP2 code. All the results computed physical properties confirmed the feasibility of these all-inorganic materials for their use in the fabrication of ductile, optical resistive switching memory RRAM devices.

Orientation-Selective Memory Switching in Quasi-1D NbSe3 Neuromorphic Device for Omnibearing Motion Detection.

Intelligent neuromorphic hardware holds considerable promise in addressing the growing demand for massive real-time data processing in edge computing. Resistive switching materials with intrinsic anisotropy and a compact design of non-volatile memory devices with the capability of handling spatiotemporally reconstructed data is crucial to perform sophisticated tasks in complex application scenarios. In this study, an anisotropic resistive switching cell with a planar configuration based on lithiated NbSe3 nanosheets is demonstrated. Benefitting from the highly aligned diffusive channel associated with a quasi-1D van der Waals structure, the memristor patterned along NbSe3 atomic chains presents robust memory switching behavior with superior stability, particularly the low set/reset voltages (0.4V/-0.36V) and extremely small standard deviation (0.041V/0.051V), among the best compared to state-of-the-art devices. More importantly, unlike traditional resistive switching materials, anisotropic ion migration in NbSe3 crystals leads to a high orientation selectivity in the conductance update. Custom-designed neuromorphic hardware contributes to the implementation of omnibearing motion recognition for automatic pilot applications, yielding a high accuracy of 95.9% considering variations. This article presents a new strategy based on NbSe3 crystals to develop a neuromorphic computing system with intelligent application scenarios.

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.

Synergetic engineering of oxidizable, redox, and inert metal decorated copper oxide for non-volatile memory and neuromorphic computing applications

Abstract In the quest for efficient resistive switching (RS) materials for both non-volatile memory and neuromorphic computing applications, a variety of functional materials have been researched in the last few years. Herein, we systematically synthesized Ni, Ag, and Au decorated copper oxide (CuxO) by using an electrochemical approach and investigated their RS performance for both non-volatile memory storage and neuromorphic computing applications. By tuning various electrochemical parameters, we optimized Ni, Ag, and Au decoration over the CuxO switching layers to understand the effect of oxidizable, redox, and inert metal decoration, respectively. Fabricated Ni-CuxO/FTO, Ag-CuxO/FTO, and Au-CuxO/FTO devices show forming-free bipolar and analog properties of RS behavior. The electrical measurements asserted that the electrodeposited Ni-CuxO/FTO RS device shows excellent RS, non-volatile memory, and synaptic learning properties compared to the Ag-CuxO/FTO, and Au-CuxO/FTO devices. Moreover, the statistical and Weibull distribution parameters suggested that the Ni-CuxO/FTO RS device has lower switching variation than the other two devices. The conduction mechanisms of all devices are investigated by fitting the appropriate physics-oriented models. It was found that Ohmic and Child's square law were dominated during the charge transport and the RS process occurred due to the filamentary switching effect. Results suggested the electro-decorated/-deposited Ni-CuxO is a suitable switching layer for memory as well as neuromorphic computing applications.

Laser assembly of CeO2 nanobrushes and their resistive switching performance

Memristors in a metal/oxide/metal configuration emerge as an advanced non-volatile information storage technology due to their high operating speed and low power consumption. Understanding the role of the microstructure of the active oxide layer in its resistive switching (RS) performance is scientifically important for revealing the conduction mechanism of oxides, and technically critical for the development of high-performance memristors. Here, self-assembly of vertically aligned CeO2 nanobrushes, a typical RS material, is demonstrated in pulsed laser epitaxy. The growth map of CeO2 is fully explored, and optimized growth conditions for CeO2 nanobrushes are established. Microstructure and crystallinity characterizations reveal the single-crystalline epitaxy nature of CeO2 nanobrushes. A nanobrush memristor exhibits a threshold switching feature with an On/Off ratio of 50, as 16 times high as a thin-film memristor, and excellent endurance of up to 500 cycles and retention time of up to 104 seconds. Theoretical fitting of the I-V curves of the thin-film and nanobrush memristors show interfacial switching in the thin-film memristor and filamentary switching in the nanobrush memristor. The distinct RS mechanisms between thin films and nanobrushes suggest the fundamental role of the structural design of active oxide layers in the RS performance of oxide-based memristors.

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.

2D and Quasi-2D Halide Perovskite-Based Resistive Switching Memory Systems

Resistive switching (RS) memory devices are gaining recognition as data storage devices due to the significant interest in their switching material, Halide perovskite (HP). The electrical characteristics include hysteresis in its current–voltage (I–V) relationship. It can be attributed to the production and migration of defects. This property allows HPs to be used as RS materials in memory devices. However, 3D HPs are vulnerable to moisture and the surrounding environment, making their devices more susceptible to deterioration. The potential of two-dimensional (2D)/quasi-2D HPs for optoelectronic applications has been recognized, making them a viable alternative to address current restrictions. Two-dimensional/quasi-2D HPs are created by including extended organic cations into the ABX3 frameworks. By adjusting the number of HP layers, it is possible to control the optoelectronic properties to achieve specific features for certain applications. This article presents an overview of 2D/quasi-2D HPs, including their structures, binding energies, and charge transport, compared to 3D HPs. Next, we discuss the operational principles, RS modes (bipolar and unipolar switching), in RS memory devices. Finally, there have been notable and recent breakthroughs in developing RS memory systems using 2D/quasi-2D HPs.

Compliance-free, analog RRAM devices based on SnOx

Brain-inspired resistive random-access memory (RRAM) technology is anticipated to outperform conventional flash memory technology due to its performance, high aerial density, low power consumption, and cost. For RRAM devices, metal oxides are exceedingly investigated as resistive switching (RS) materials. Among different oxides, tin oxide (SnOx) received minimal attention, although it possesses excellent electronic properties. Herein, we demonstrate compliance-free, analog resistive switching behavior with several stable states in Ti/Pt/SnOx/Pt RRAM devices. The compliance-free nature might be due to the high internal resistance of SnOx films. The resistance of the films was modulated by varying Ar/O2 ratio during the sputtering process. The I–V characteristics revealed a well-expressed high resistance state (HRS) and low resistance states (LRS) with bipolar memristive switching mechanism. By varying the pulse amplitude and width, different resistance states have been achieved, indicating the analog switching characteristics of the device. Furthermore, the devices show excellent retention for eleven states over 1000 s with an endurance of > 100 cycles.

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.

Research progress on the resistive switching materials in optoelectronic memristors

Research progress on the resistive switching materials in optoelectronic memristors

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.