Resistive Random Access Memory Devices Research Articles

Enhanced resistive switching performance in TiN/AlOx/Pt RRAM by high-temperature I-V cycling

Set voltage is a key parameter for the application of Resistance Random Access Memory (RRAM). In this paper, based on TiN/AlOx/Pt RRAM synthesized by the magnetron sputtering method, we have studied the influence of I-V cycling at high temperatures on resistive switching performance. The results show that the treatment can significantly reduce the set voltage in resistive switching cycles. Moreover, the treatment can also enhance endurance effectively. Further studies indicated that a higher compliance current in treatment can induce a smaller and more uniform set voltage. We ascribe the improvements in resistive switching performance to the generation and accumulation of oxygen vacancies in the treatment. This research provides new ideas for synthesizing RRAM devices with low power consumption.

Improving the Nonvolatile Memory Characteristics of Sol–Gel-Processed Y2O3 RRAM Devices Using Mono-Ethanolamine Additives

In this study, Y2O3-based resistive random-access memory (RRAM) devices with a mono-ethanolamine (MEA) stabilizer fabricated using the sol–gel process on indium tin oxide/glass substrates were investigated. The effects of MEA content on the structural, optical, chemical, and electrical characteristics were determined. As the MEA content increased, film thickness and crystallite size decreased. In particular, the increase in MEA content slightly decreased the oxygen vacancy concentration. The decreased film thickness decreased the physical distance for conductive filament formation, generating a strong electric field. However, owing to the lowest oxygen vacancy concentration, a large electrical field is required. To ensure data reliability, the endurance cycles across several devices were measured and presented statistically. Additionally, endurance performance improved with the increase in MEA content. Reduced oxygen vacancy concentration can successfully suppress the excess formation of the Ag conductive filament. This simplifies the transition from the high- to the low-resistance state and vice versa, thereby improving the endurance cycles of the RRAM devices.

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.

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.

A flexible and fast digital twin for RRAM systems applied for training resilient neural networks

Resistive Random Access Memory (RRAM) has gained considerable momentum due to its non-volatility and energy efficiency. Material and device scientists have been proposing novel material stacks that can mimic the “ideal memristor” which can deliver performance, energy efficiency, reliability and accuracy. However, designing RRAM-based systems is challenging. Engineering a new material stack, designing a device, and experimenting takes significant time for material and device researchers. Furthermore, the acceptability of the device is ultimately decided at the system level. We see a gap here where there is a need for facilitating material and device researchers with a “push button” modeling framework that allows to evaluate the efficacy of the device at system level during early device design stages. Speed, accuracy, and adaptability are the fundamental requirements of this modelling framework. In this paper, we propose a digital twin (DT)-like modeling framework that automatically creates RRAM device models from device measurement data. Furthermore, the model incorporates the peripheral circuit to ensure accurate energy and performance evaluations. We demonstrate the DT generation and DT usage for multiple RRAM technologies and applications and illustrate the achieved performance of our GPU implementation. We conclude with the application of our modeling approach to measurement data from two distinct fabricated devices, validating its effectiveness in a neural network processing an Electrocardiogram (ECG) dataset and incorporating Fault Aware Training (FAT).

A Violet‐Light‐Responsive ReRAM Based on Zn2SnO4/Ga2O3 Heterojunction as an Artificial Synapse for Visual Sensory and In‐Memory Computing

AbstractDue to the imitation of the neural functionalities of the human brain via optical modulation of resistance states, photoelectric resistive random access memory (ReRAM) devices attract extensive attraction for synaptic electronics and in‐memory computing applications. In this work, a photoelectric synaptic ReRAM (PSR) of the structure of ITO/Zn2SnO4/Ga2O3/ITO/glass with a simple fabrication process is reported to imitate brain plasticity. Electrically induced long‐term potentiation/depression (LTP/D) behavior indicates the fulfillment of the fundamental requirement of artificial neuron devices. Classification of three‐channeled images corrupted with different levels (0.15–0.9) of Gaussian noise is achieved by simulating a convolutional neural network (CNN). The violet light (405 nm) illumination generates excitatory post synaptic current (EPSC), which is influenced by the persistent photoconductivity (PPC) effect after discontinuing the optical excitation. As an artificial neuron device, PSR is able to imitate some basic neural functions such as multi‐levels of photoelectric memory with linearly increasing trend, and learning‐forgetting‐relearning behavior. The same device also shows the emulation of visual persistency of optic nerve and skin‐damage warning. This device executes high‐pass filtering function and demonstrates its potential in the image‐sharpening process. These findings provide an avenue to develop oxide semiconductor‐based multifunctional synaptic devices for advanced in‐memory photoelectric systems.

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.

Quantum Dots for Resistive Switching Memory and Artificial Synapse.

Memristor devices for resistive-switching memory and artificial synapses have emerged as promising solutions for overcoming the technological challenges associated with the von Neumann bottleneck. Recently, due to their unique optoelectronic properties, solution processability, fast switching speeds, and low operating voltages, quantum dots (QDs) have drawn substantial research attention as candidate materials for memristors and artificial synapses. This review covers recent advancements in QD-based resistive random-access memory (RRAM) for resistive memory devices and artificial synapses. Following a brief introduction to QDs, the fundamental principles of the switching mechanism in RRAM are introduced. Then, the RRAM materials, synthesis techniques, and device performance are summarized for a relative comparison of RRAM materials. Finally, we introduce QD-based RRAM and discuss the challenges associated with its implementation in memristors and artificial synapses.

Oxygen-Plasma-Treated Al/TaOX/Al Resistive Memory for Enhanced Synaptic Characteristics.

In this study, we investigate the impact of O2 plasma treatment on the performance of Al/TaOX/Al-based resistive random-access memory (RRAM) devices, focusing on applications in neuromorphic systems. Comparative analysis using scanning electron microscopy and X-ray photoelectron spectroscopy confirmed the differences in chemical composition between O2-plasma-treated and untreated RRAM cells. Direct-current measurements showed that O2-plasma-treated RRAM cells exhibited significant improvements over untreated RRAM cells, including higher on/off ratios, improved uniformity and distribution, longer retention times, and enhanced durability. The conduction mechanism is investigated by current-voltage (I-V) curve fitting. In addition, paired-pulse facilitation (PPF) is observed using partial short-term memory. Furthermore, 3- and 4-bit weight tuning with auto-pulse-tuning algorithms was achieved to improve the controllability of the synapse weight for the neuromorphic system, maintaining retention times exceeding 103 s in the multiple states. Neuromorphic simulation with an MNIST dataset is conducted to evaluate the synaptic device.

Influence of electrodes on the resistive switching characteristics of Al/Gd2Zr2O7/E (E=Al or ITO) RRAM devices

Sol-gel derived amorphous Gd2Zr2O7 (GZO) thin films with Al/GZO/E (E = ITO or Al) structures were prepared to demonstrate the effect of electrode material on the switching behavior of resistive random access memory (RRAM) devices. All devices exhibit bipolar resistive switching (BRS) mode. After the post-metal annealing (PMA) treatment, the AlOx interfacial layer contributes to enhancing oxygen ion storage capacity and limiting the electromigration of aluminum metal. The forming-free Al/GZO/ITO device exhibits a switching cycle of 3027, a Vset/Vreset ratio of −1.83 V/0.56 V, a Ron/Roff ratio of approximately 10, and a retention time of 104 s. And the Al/GZO/Al device features a dual-layer AlOx structure, significantly improving the integrity of filament rupture to reduce leakage current and increase the switching window. Its switching cycle is 1946, with a Vset/Vreset ratio of −3.47 V/0.29 V, a Ron/Roff ratio of approximately 102, and a retention time of 104 s. The oxygen storage capacity of the dual-layer AlOx interfacial layer in the Al/GZO/Al device surpasses that of the Al/GZO/ITO device, allowing for a reduction in the reset voltage and ensuring more complete filament rupture, thereby enhancing the RHRS. Accordingly, GZO thin films can be applied to achieve the desired RS characteristics on different electrodes, making them promising candidates for RRAM applications.

Convolutional neural network for high-performance reservoir computing using dynamic memristors

In the rapidly advancing field of neuromorphic computing, W/ZnO/TiN resistive random-access memory (RRAM) devices have emerged as a next-generation computational building block. Our findings reveal the significant role played by the thickness of the ZnO layer in determining the electrical properties essential for data storage and neuromorphic applications. The short-term memory (STM) capabilities, which are critical for processing temporal information, are closely examined alongside their potential to simulate biological synaptic functions through multilevel conductance states and synaptic behaviors such as paired-pulse facilitation. Integrating these devices into reservoir computing systems enhances pattern recognition and accelerates learning, which demonstrates their utility in sequential data processing. In addition, conductance modulation via pulse width adjustment is a novel strategy to optimize memory device performance. By showcasing the effectiveness of W/ZnO/TiN devices in neuromorphic computing through high-accuracy image recognition tasks, our study highlights their foundational role in advancing neuromorphic computing technologies. The adaptability, learning capabilities, and efficiency of these devices underscore their potential for developing hardware-based neuromorphic systems that are capable of complex data processing.

Vanadium Dioxide by Atomic Layer Deposition: A Promising Material for Next-Generation Memory Devices.

The synthesis of a vanadium dioxide (VO2) film using atomic layer deposition (ALD) with vanadium tetrachloride (VCl4) as a precursor for the realization of programmable memory devices is reported. X-ray diffraction analysis revealed the epitaxial growth of VO2 on c-Al2O3. The phase transition was monitored using resistivity measurements across varying temperatures, demonstrating a decrease of >4 orders of magnitude at the transition temperature, thereby confirming the high quality of the material. From this material, memristive devices are fabricated as resistive random-access memory (RRAM). On the basis of spiking voltage inputs, these RRAM exhibited cycle stability over 512 cycles and state retention stability for >450 s, showing <2% drift. With respect to synaptic-like applications, the RRAM devices were piloted through step patterns to enable multilevel memory states. These ALD-grown VO2-based devices demonstrate potential for use as synaptic connections with multiweight synapses, advancing scalability in neuromorphic applications.

Enhancing reliability in oxide-based memristors using two-dimensional transition metal dichalcogenides

Oxide-based memristor is an attractive candidate for future nonvolatile resistive random access memory (RRAM) devices. However, it suffers from insufficient reliability, owing to the randomness of the conductive filaments, hindering the practical use of the memristor for future RRAM applications. Here, we propose harnessing the two-dimensional (2D) transition metal dichalcogenides (TMDs) on oxide memristor to achieve high device reliability by controlling oxygen vacancy-based filaments near the TMDs/oxide interface. By forming the Pt/WSe2/HfxZr1-xO2 (HZO)/TiN structure, the fabricated memristor exhibits high reliability with good cyclic endurance (over 2,000 cycles), retention (104 s), and low cycle-to-cycle variability. Surface chemical analysis reveals the abundant oxygen vacancies induced by forming WSe2/HZO interface are the source of filamentary switching. By incorporating 2D materials and oxides, the practical application of memristor to future information processing devices can be boosted by the enhanced device reliability.

ReSG: A Data Structure for Verification of Majority-based In-memory Computing on ReRAM Crossbars

Recent advancements in the fabrication of Resistive Random Access Memory (ReRAM) devices have led to the development of large-scale crossbar structures. In-memory computing architectures relying on ReRAM crossbars aim to mitigate the processor-memory bottleneck that exists with current complementary metal-oxide semiconductor technology. With this motivation, several synthesis and mapping approaches focusing on the realizations of Boolean functions in the ReRAM crossbars have been proposed earlier. Thus far, the verification of the designs realized on ReRAM crossbars is done either through manual inspection or using simulation-based approaches. Since manual inspections and simulation-based approaches are limited to smaller designs, they cannot be applied to the verification of complex designs on large-scale ReRAM crossbars. Motivated by this, we propose, for the first time, an automatic equivalence checking flow that determines the equivalence between the original function specification (e.g., Majority-inverter Graph ) and the crossbar micro-operations file formats. We consider two crossbar structures, zero-transistor, one-memristor (0T1R) and one-transistor, one-memristor (1T1R) to implement the micro-operations. While the micro-operations file format exists for 0T1R crossbar structures, no representations for micro-operations to be executed in 1T1R crossbars exist yet. In this work, we introduce the micro-operation file format for 1T1R crossbar structures to efficiently represent the micro-operations as ReRAM crossbar netlists. Afterwards, we introduce two intermediate data structures, ReRAM Sequence Graph for 0T1R crossbars (ReSG-0T1R) and for 1T1R crossbars (ReSG-1T1R) , that are derived from the 0T1R and 1T1R crossbar micro-operations file formats, respectively. These ReSGs are then translated into Boolean Satisfiability (SAT) formula, and then the verification is done by checking the generated SAT formulae against the golden functional specification (represented in Verilog) using Z3 Satisfiability solver. Experimental evaluations confirm the effectiveness of the proposed verification methodology on MCNC and ISCAS benchmarks.

Complementary resistive switching characteristics of solid electrolyte chalcogenide AgxTe nanoparticles for high-density crossbar random access memory

Silver telluride (AgxTe) is a member of the chalcogenide family that comprises materials extensively used as solid electrolytes. Because of its high-ionic conductivity, low-optical bandgap, and excellent thermoelectric properties, AgxTe has been studied in many research fields, including optoelectronics and energy harvesting. Herein, AgxTe is proposed as the active channel for resistive random access memory (RRAM) showing complementary resistive switching (CRS) characteristics. AgxTe-based RRAM devices with an Ag/AgxTe/Au structure are fabricated on a glass substrate. AgxTe nanoparticles are synthesized using the colloidal method, and AgxTe thin films are prepared via spin coating of the synthesized nanoparticles dispersed in deionized water. The fabricated AgxTe-based RRAM device exhibits CRS characteristics without any additional built-in selectors or antiserial arrangement. This is attributed to the formation of the inversion of CF geometry and allows the fabrication of high-density crossbar arrays. The AgxTe RRAM device annealed at 200 °C exhibits a resistance on/off ratio of approximately 102 as well as stable retention (∼104 s) and endurance (∼103 cycles). This investigation proposes a new application of AgxTe, as a solid electrolyte, and a new strategy for the development of high-density crossbar RRAM architectures, for the first time.

Study of resistive properties and neural response of ZrO2/TiO2 heterojunction nanowire array (NWA) RRAM

Nowadays, the researcher has an eye on enhancing the performance of resistive random-access memory (RRAM) and exploring new demands and applications, particularly in the field of artificial intelligence and neural computing. It is crucially important for accurately replicating the observed plasticity within synapses to achieve superior RRAM performance in low-dimensional nanomaterials. In this work, we focus on addressing certainly unsatisfactory electrical properties of RRAM based on titanium oxide nanowire array (TiO2 NWA), for example, short retention time (∼103 s). Theoretically and experimentally, a novel and solution-based RRAM structure, namely ZrO2/TiO2(NWA), has been conducted. With the help of the ZrO2 insertion layer, the RRAM device shows impressive resistive switching characteristics, including 200 current–voltage(I-V) sweeps without degradation, increased cycling endurance (>105 cycles), and a long retention time (∼9 × 104 s). These findings hold significant implications for digital computing systems. Moreover, the successful implementation of the proposed device enables the emulation of fundamental synaptic biological features such as non-linear transmission properties, learning experiences behavior, short-term potentiation (STP) and long-term potentiation (LTP). This research provides evidence of the immense potential of the Ag/ZrO2/TiO2(NWA)/FTO RRAM device in bipolar non-volatile memory (NVM) and biomimetic neuromorphic systems.

Analysis of conductive filament heat transfer in TiO2-based RRAM device

Abstract Resistive random access memory (RRAM) has developed into a new type of non-volatile memory that has attracted much attention for its high density and low power; TiO2 has been studied to make RRAM because of its high conductivity. Based on the COMSOL Multiphysics finite element method and domain decomposition method, an electrically-thermally coupled model of TiO2-based RRAM with oxygen vacancy (Vo) conduction mechanism is constructed, the formation and cutting process of RESET and SET conductive filament (CF) under different voltages is simulated. Moreover, the characteristics of the internal temperature distribution of the CF are explored. The results show that the RESET process is more sensitive to heat changes, the transverse direction thermal value of the CF is more obvious than the longitudinal direction, and the rate of change is faster. Additionally, the electric field induces the migration of the Vo in filament, which affects the enthalpy change of the device’s heat transfer and resistive properties. This is an important reference for a deeper understanding of the switching behavior of RRAM devices and the control mechanisms for thermal studies.

Bipolar resistive switching behavior of PVA/g-C3N4 quantum dots hybrid thin films

Graphite-phase carbon nitride quantum dots (g-C3N4 QDs) have garnered widespread attention and considerable research interest as active media for resistive random-access memory (RRAM) devices owing to their exceptional physical properties. In this study, g-C3N4 QDs were synthesized via ultrasonic-assisted liquid-phase exfoliation. Subsequently, the obtained g-C3N4 QDs with uniform size were embedded into polyvinyl alcohol (PVA) for preparing PVA/g-C3N4 QDs hybrid, and the RRAM devices with Al/g-C3N4 QDs-PVA/ITO/PET structure were fabricated. The obtained memory devices exhibit bipolar resistive switching (BRS) behavior and are primarily influenced by the space charge limited conduction (SCLC) mechanism. The data retention time exceeds 104 s at a read voltage of 0.1 V, accompanied by an impressively low set voltage. In addition, the device exhibits a surprising temperature dependence of the resistive switching performance at different temperatures. The aforementioned properties demonstrate the significant potential of g-C3N4 QDs in RRAM for data storage applications.

Improved resistive switching characteristics observed in amorphous boron nitride-based RRAM device via oxygen doping: A study based on bulk and interface traps analysis

In this paper, we propose an oxygen-doped amorphous boron nitride (O-doped a-BN)-based resistive random-access memory (RRAM) to address the low on/off ratio and stability concerns of conventional a-BN-based RRAM. Initially, comparative analysis with a-BN based RRAM device revealed that the O-doped a-BN based RRAM exhibited 2.5-fold increase in the on/off ratio, enhanced endurance with stable operation over 100 DC cycles, and improved retention stability lasting for 104 s. Then, on the basis of both interface and bulk trap analysis using impedance spectroscopy and the Terman method, the bulk trap density in the O-doped a-BN and a-BN films acts as a key parameter in RS properties, which results in an increase of its on/off ratio and its stable retention without any degradation. These findings show that O-doping in a-BN films can be a technique to improve the on/off ratio and reliability of a-BN-based RRAM devices.

An ab-initio investigation of physical characteristics of GdSc1-xTMxO3(TM=Ti; x=0.25, 0.5, 0.75) for photo influenced (NIR)memory storage and allied devices

In the present study, we have computed the structural, electronic, and optical characteristics of pristine GdScO3 and GdSc1-xTMxO3 (TM = Ti; x = 0.25, 0.5, 0.75) for improved performance of Resistive Random Access Memory (RRAM) devices. All calculations have been performed using the Tran Balha-modified Becke Johnson (TB-mBJ) approximation within the framework of the WEIN2K simulation package. Herein, the effect of Ti-dopant (transition metal, i.e., TM) with varying concentrations has been observed, especially in tuning the energy band gap. The structural analysis of composites reveals structural stability and a significant reduction in bulk modulus with increasing dopant concentration, leading to enhanced electrical conductivity. The band structure analysis reveals that the band gap tends to decrease with increasing concentrations of Ti-dopant.As regards total density of states (TDOS), it has been found that with increasing concentrations of Ti, dopant extra states appear in the conduction band. This is the reason behind the formation of the conducting filaments (CF) within the active layer of RRAM devices. The partial density of states (PDOS) elaborates that for all studied composites, the formation of the conduction band (C.B.) and valence band (V.B.) is a consequence of the hybridization of Sc-3d, Gd-5d, and Ti-4d states, along with the minute contribution of O-2p states. Optical characteristics disclose the photoresponse of all studied composites, wherein GdSc0.25Ti0.75O3 exhibits wide range absorption, henceforth making it a making it a more suitable candidate for photoinfluencing, especially in near infrared (NIR) RRAM devices.