Resistive Switching Memory Devices Research Articles

Sol-Gel Processed ZrO2 Based Forming-Free Resistive Switching Memory Devices

In this work, we fabricated ZrO2 based resistive random access memory by sol-gel spin coating technique and investigated its structural, optical and resistive switching properties. The X-ray diffraction pattern revealed that 400 °C annealed ZrO2 thin film has tetragonal structure. The optical band gap value of ZrO2 thin film obtained was 5.51 eV. The resistive switching behaviour of W/ZrO2/ITO capacitor like structure was studied. It was found that no initial electroforming process required for the device. The fabricated devices show a self-compliance bipolar resistive switching behaviour and have high on off ratio (>102). Our result suggests that solution processed ZrO2 has great potential to develop transparent and flexible resistive random access memory devices.

A two-dimensional polymer memristor based on conformational changes with tunable resistive switching behaviours

A resistive switching memory device based on a 2DPTPAK+TAPB film with the conformational change mechanism was prepared and the memory behaviors can be adjusted by the degree of conformational changes.

“Unraveling the Importance of Fabrication Parameters of Copper Oxide-Based Resistive Switching Memory Devices by Machine Learning Techniques”

“Unraveling the Importance of Fabrication Parameters of Copper Oxide-Based Resistive Switching Memory Devices by Machine Learning Techniques”

Performance Improvement in E-Gun Deposited SiOx- Based RRAM Device by Switching Material Thickness Reduction

A performance improvement by reduction in switching material thickness in a e-gun deposited SiOx based resistive switching memory device was investigated. Reduction in thickness cause thinner filamentary path formation during ON-state by controlling the vacancy defects. Thinner filament cause lowering of operation current from 500 μA to 100 μA and also improves the reset current (from >400 μA to <100 μA). Switching material thickness reduction also cause the forming free ability in the device. All these electrical parametric improvements enhance the device reliability performances. The device show >200 dc endurance, >3-hour data retention and >1000 P/E endurance with 100 ns pulses.

RRAM and WORM memory devices using Protamine Sulfate and Graphene Oxide

Biomaterials are extensively exploited as the resistive switching materials since last decade. Biomaterials such as proteins, DNA, enzymes, polysaccharides, starch, natural materials are being used as the active layer for the resistive switching memory devices. In this report we have investigated the Resistive Switching (RS) Memory behavior of a biomolecule Protamine Sulfate (PS), Graphene Oxide (GO) and their mixture. It has been observed that RS device having pure PS or GO as the active layer showed non-volatile memory behavior suitable for Write Once Read Many (WORM) memory applications. Dynamic transition of switching behavior from WORM to bipolar switching observed in the device designed with PS + GO mixed system. In case of the mixed film the set and reset power is found to be less than the individuals which is advantageous with respect to the power consumption. The memory window is also found to be increased multiple times.

Enhanced switching ratio of sol–gel-processed Y2O3 RRAM device by suppressing oxygen vacancy formation at high annealing temperatures

Sol–gel-processed Y2O3 films were used as an active-channel layer for resistive switching memory (RRAM) devices. The influence of post-annealing temperature on structural, chemical, and electrical properties was studied. Y2O3-RRAM devices comprising electrochemically active metal electrodes, Ag, and indium tin oxide (ITO) electrodes exhibited the conventional bipolar RRAM device operation. The fabricated Ag/Y2O3/ITO RRAM devices, which included 500 °C-annealed Y2O3 films, exhibited less oxygen vacancy and defect sites, reduced the leakage current, increased the high-/low-resistance state ratio of more than 105, and provided excellent nonvolatile memory properties without significant deterioration for 100 cycles and 104 s.

A nonlinear resistive switching behaviors of Ni/HfO2/TiN memory structures for self-rectifying resistive switching memory

This work reports forming free/self-rectifying resistive switching characteristics and dependency of the top electrode (TE) of a crystalline HfO2-based resistive switching memory device. In the memory cells, nonlinear bipolar resistive switching characteristics, i.e., an asymmetric current-voltage curve like the Schottky diode, was observed. In addition, the device exhibits resistive switching behaviors without forming process, which makes it possible to switch the resistance state under ultra-low current levels of <10 nA. In addition, compared to the resistive switching of the proposed resistive switching memory devices with different TEs, the VSET was decreased when using TE with lower work function, and the height read margin was obtained in the sample with the Ni TE, covering over 56 × 56 arrays. Consequently, these results indicate that the interface control resistive switching properties in memory structures having the Schottky junction warrant the realization of selector-free resistive switching memory cells in a high-density crossbar array.

Switching-Modulated Phase Change Memory Realized by Si-Containing Block Copolymers.

The phase change memory (PCM) is one of the key enabling memory technologies for next-generation non-volatile memory device applications due to its high writing speed, excellent endurance, long retention time, and good scalability. However, the high power consumption of PCM devices caused by the high switching current from a high resistive state to a low resistive state is a critical obstacle to be resolved before widespread commercialization can be realized. Here, a useful approach to reduce the writing current of PCM, which depends strongly on the contact area between the heater electrode and active layer, by employing self-assembly process of Si-containing block copolymers (BCPs) is presented. Self-assembled insulative BCP pattern geometries can locally block the current path of the contact between a high resistive film (TiN) and a phase-change material (Ge2 Sb2 Te5 ), resulting in a significant reduction of the writing current. Compared to a conventional PCM cell, the BCP-modified PCM shows excellent switching power reduction up to 1/20 given its use of self-assembled hybrid SiFex Oy /SiOx dot-in-hole nanostructures. This BCP-based bottom-up process can be extended to various applications of other non-volatile memory devices, such as resistive switching memory and magnetic storage devices.

Low-Frequency 1/f Noise Characteristics of Ultra-Thin AlOx-Based Resistive Switching Memory Devices with Magneto-Resistive Responses

Low-frequency 1/f voltage noise has been employed to probe stochastic charge dynamics in AlOx-based non-volatile resistive memory devices exhibiting both resistive switching (RS) and magneto-resistive (MR) effects. A 1/fγ noise power spectral density is observed in a wide range of applied voltage biases. By analyzing the experimental data within the framework of Hooge’s empirical relation, we found that the Hooge’s parameter α and the exponent γ exhibit a distinct variation upon the resistance transition from the low resistance state (LRS) to the high resistance state (HRS), providing strong evidence that the electron trapping/de-trapping process, along with the electric field-driven oxygen vacancy migration in the AlOx barrier, plays an essential role in the charge transport dynamics of AlOx-based RS memory devices.

Influence of aging on the resistive switching behavior of epitaxial strontium titanate based heterostructures

In this work, we investigated the impact of aging on the resistive switching behavior of high quality epitaxial heterostructure resistive switching devices [Pt/SrTiO3/LaNiO3/LaAlO3 (001) with SrTiO3 (STO) as switching layer, Pt as top electrode and LaNiO3 as bottom electrode]. For this study, the resistive switching memory devices of two different ultrathin switching layer (STO) thicknesses (5 and 10 nm) were fabricated with different shape and size of top electrode (Pt) i.e. 20 µm (circular shape) and 50 µm (square shaped). Subsequently, their resistive switching behavior at different instant of time i.e. freshly prepared, 4 months and 16 months were studied. With long aging, we find a decrease in the positive bais voltages for which current start rising exponentially (set voltages) for most of the devices besides emergence of various features such as multiple crossovers, noisy/spike region during set process and openness in the switching hysteresis loop. The existence of these behaviors is attributed to the fact that the moisture permeates through the interfacial region between top electrode (Pt) and switching layer (STO) irrespective of the thickness of switching layer and dimensions of top electrode.

Effect of Graphene Composite on Biological Egg Protein Resistance Switching Memory Properties

In this work, a resistive switching memory device was fabricated based on egg protein, a natural biomaterial. The effect of graphene composite on the resistive switching characteristics of the device was investigated. The experimental results show that both pure egg protein and graphene composite devices exhibit bipolar nonvolatile resistive conversion properties. Both devices have good data retention capability. Furthermore, the composite of graphene can effectively improve the device endurance and the consistency of the on-state current distribution of the device. Based on the theory of capture and de-capture of charge carrier, the mechanism of resistive switching is analyzed.

Conductive Path Mechanism for Bipolar Resistive Switching Characteristics in Lead‐Free Perovskite CsSnBr3‐Based Nonvolatile Memories

Halide perovskites are intensely studied due to their potential excellent properties in electronic devices. However, the toxicity of lead remains as an obstacle on their way toward large‐scale applications. Herein, the lead‐free all‐inorganic perovskite CsSnBr3 film is used as the switching layer to construct nonvolatile resistive switching (RS) memories and the underlying switching mechanism is systematically explicated. Both memories with Ag/CsSnBr3/Pt and Pt/CsSnBr3/Pt structures exhibit reproducible bipolar RS characteristics, including the large on/off ratios and low reset currents. The RS characteristics are attributed to the formation/rupture of nano‐cone‐shaped conductive paths under external voltage bias. In addition, compared with Pt/CsSnBr3/Pt device, the Ag/CsSnBr3/Pt device manifests lower operation set/reset voltages, revealing the formation of higher density or stronger conductive paths. This work might pave the way for the lead‐free all‐inorganic perovskite‐based RS memory devices in high performance emerging commercial applications.

The Resistive Switching Characteristics and Electrical Conduction Mechanisms of Memory Devices Based on Nanocomposite

The resistive switching memory device based on nanocomposites has become a potential candidate in the data storage field. Understanding resistive switching characteristics and electrical conduction mechanisms may support the appropriate way to fabricate and control the operation of a device. In this study, a capacitor-like structure using PVA-ZnO as an insulator layer was fabricated by a solution method. The crystalline structure, morphology, and absorption spectrum of ZnO nanoparticles were revealed respectively. The resistive switching effect was observed with the ON/OFF ratio of 0.5´102, high endurance, excellent retention and the electrical transport mechanisms were followed by the SCLC and Ohmic’s law in the low resistance state and Flower- Nordheim tunneling in the high resistance state. The resistive switching mechanism was contributed by the oxygen vacancies in ZnO nanoparticles and the oxygen ions in the bottom electrode.

Halide Perovskites for Memristive Data Storage and Artificial Synapses.

Halide perovskites have been noted for their exotic properties such as fast ion migration, tunable composition, facile synthetic routes, and flexibility in addition to large light absorption coefficients, long carrier diffusion lengths, and high defect tolerance. These properties have made halide perovskites promising materials for memristors. Applications in the field of resistive switching memory devices and artificial synapses for neuromorphic computing are especially noteworthy. This Perspective covers state-of-the-art perovskite-based memristive devices. Moreover, the fundamental mechanisms and characteristics of perovskite-based memristors are elucidated. Interesting opportunities to improve the performance of perovskite-based memristors for commercialization are provided, including improving film uniformity and air stability, controlling the stoichiometry, finding new all-inorganic and lead-free halide perovskites, and making perovskites into single crystals or quantum dots. We expect our Perspective to be the foundation of realizing next-generation halide perovskite-based memristors.

Oxide Passivation of Halide Perovskite Resistive Memory Device: A Strategy for Overcoming Endurance Problem.

Owing to a low operation voltage, high on/off ratio, and tunable band gap, halide perovskites (HPs) are being conceived as an alternative to oxide or chalcogenide materials in resistive-switching (RS) memory devices. However, the HP-based RS memory devices face problems such as short endurance, low retention, and device stability. Herein, the oxide-passivated HP devices were fabricated by hybridizing the oxide sol-gel and halide adduct methods. The silicon oxide (SiO2)-passivation enhanced the device properties with an endurance of 6000 cycles and retention of 1.8 × 104 s. The study of activation energy using ionic conductivity and time-of-flight secondary-ion mass spectroscopy demonstrated that the migration path of the Ag ions is well-controlled by the SiO2 passivation layer. Various oxides were used as passivation materials. Especially, the zirconium oxide-passivated devices exhibit excellent properties with an endurance of 57 000 cycles and retention of 7.8 × 104 s. The high cohesive energy of oxides effectively increased the formation voltage by retarding the Ag-ion migration, leading to the improved endurance properties of the devices. This paper proposes a strategy for significantly improving the low endurance property of HP-based RS memory devices using the oxide passivation technology.

Solution-Processed Photoinduced Multilevel Resistive Switching Devices Based on Lead-Free All-Inorganic Perovskite

The letter reports lead free all-inorganic perovskite based resistive switching (RS) memory devices. The cesium tin bromide (CsSnBr <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ) perovskite films were prepared by the solution deposition technique. The memory devices exhibit bipolar resistive RS characteristic and light assisted multilevel storage capability. The proposed devices show a maximum ON/OFF ratio of ~ 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup> , data retention of ~ 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> s, and endurance of 400 cycles. We explain the resistive switching effect on lights of the formation and rupture of a conducting path under an electric field. This work may provide an opportunity to develop transparent, flexible, and multibit storage capacity photonic resistive memory devices based on all-inorganic perovskites for successful logic application.

Quasi-2D Halide Perovskite Memory Device Formed by Acid-Base Binary Ligand Solution Composed of Oleylamine and Oleic Acid.

Organometal halide perovskite materials are receiving significant attention for the fabrication of resistive-switching memory devices based on their high stability, low power consumption, rapid switching, and high ON/OFF ratios. In this study, we synthesized 3D FAPbBr3 and quasi-2D (RNH3)2(FA)1Pb2Br7 films using an acid-base binary ligand solution composed of oleylamine (OlAm) and oleic acid in toluene. The quasi-2D (RNH3)2(FA)1Pb2Br7 films were synthesized by controlling the protonated OlAm (RNH3+) solution concentration to replace FA+ cations with large organic RNH3+ cations from 3D FAPbBr3 perovskites. The quasi-2D (RNH3)2(FA)1Pb2Br7 devices exhibited nonvolatile write-once read-many (WORM) memory characteristics, whereas the 3D FAPbBr3 only exhibited hysteresis behavior. Analysis of the 3D FAPbBr3 device indicated operation in the trap-limited space-charge-limited current region. In contrast, quasi-2D (RNH3)2(FA)1Pb2Br7 devices provide low trap density that is completely filled by injected charge carriers and then subsequently form conductive filaments (CFs) to operate as WORM devices. Nanoscale morphology analysis and an associated current mapping study based on conductive atomic force microscopy measurements revealed that perovskite grain boundaries serve as major channels for high current, which may be correlated with the conductive low-resistive-switching behavior and formation of CFs in WORM devices.

Rapid microwave annealing of CH3NH3PbI3 with controllable crystallization for enhancing the resistive-switching performance

High switching fluctuation induced by the random formation and rupture of conductive filaments (CFs) is a critical issue for the development of organic-inorganic perovskite-based resistive switching (RS) memory devices. In this study, a rapid microwave-annealing method is developed to reduce grain boundaries (GBs) of CH3NH3PbI3 (MAPbI3) film and improve the switching reliability of the Au/MAPbI3/FTO device. The crystal grain size of MAPbI3 is increased and the corresponding GBs number is reduced with microwave irradiation time ranging from 40 to 120 s. In the optimized case, the dispersion of the RS parameters of the Au/MAPbI3/FTO cell is greatly reduced. Specifically, the fluctuations of the high/low resistance states and SET/RESET voltages dropped from 70.4%/69.5% and 40.5%/40.3% to 20.1%/26.7% and 16.0%/11.9%, respectively. The device can be operated with reduced compliance current. These results demonstrate that reducing the number of GBs is a feasible strategy to reduce the randomness of the CFs, and thus achieve more stable RS performance in MAPbI3-based memory devices.

Organic Memory and Memristors: From Mechanisms, Materials to Devices

AbstractFacing the exponential growth of data digital communications and the advent of artificial intelligence, there is an urgent need for information technologies with huge storage capacity and efficient computing processing. However, the traditional von Neumann architecture and silicon‐based storage and computing technology will reach their limits and cannot meet the storage requirements of ultrasmall size, ultrahigh density, and memory computing. Considering these issues, organic material resistance switching memory and memristor devices have become promising candidates for high‐density storage, logic computing, and neuromorphic computing because of their advantages of fast speed, high energy efficiency, nonvolatile storage, and low cost. In this article, the working mechanism, material design strategy, and device performance of organic memory and memristors are reviewed.

Modeling electrical conduction in resistive-switching memory through machine learning

Traditional physical-based models have generally been used to model the resistive-switching behavior of resistive-switching memory (RSM). Recently, vacancy-based conduction-filament (CF) growth models have been used to model device characteristics of a wide range of RSM devices. However, few have focused on learning the other-device-parameter values (e.g., low-resistance state, high-resistance state, set voltage, and reset voltage) to compute the compliance-current (CC) value that controls the size of CF, which can influence the behavior of RSM devices. Additionally, traditional CF growth models are typically physical-based models, which can show accuracy limitations. Machine learning holds the promise of modeling vacancy-based CF growth by learning other-device-parameter values to compute the CC value with excellent accuracy via examples, bypassing the need to solve traditional physical-based equations. Here, we sidestep the accuracy issues by directly learning the relationship between other-device-parameter values to compute the CC values via a data-driven approach with high accuracy for test devices and various device types using machine learning. We perform the first modeling with machine-learned device parameters on aluminum-nitride-based RSM devices and are able to compute the CC values for nitrogen-vacancy-based CF growth using only a few RSM device parameters. This model may now allow the computation of accurate RSM device parameters for realistic device modeling.