Reset Voltage Research Articles

Enhancing the Switching Performance of CH3NH3PbI3 Memristors by the Control of Size and Characterization Parameters

AbstractThis paper analyzes the effects of scaling and measurement conditions on the performance of hybrid organic inorganic perovskite (HOIP) devices having bipolar resistive switching characteristics. Electroforming voltage, SET current, and ON/OFF ratios are found to be area dependent. Linear voltage sweep and pulse voltage characterization showed that parameters such as compliance current, voltage scan rate, pulse width, amplitude, and frequency significantly alter the device switching parameters. The CH3NH3PbI3 memristors fabricated has FORMING, SET, and RESET voltages of 1.18, 0.17, and −0.13 V, respectively, along with an ON/OFF ratio of 1.3 × 103. It has been found that, both the RESET voltage and current significantly increase with scan rate, whereas the ON/OFF ratio increases significantly with compliance current. In case of voltage pulse characterization, the ON/OFF ratio can be enhanced by increasing the pulse amplitude and width. Additionally, the experimental data fitting to a SPICE based analytical model establishes that the HOIP memristor current conduction is dominated by tunneling process in the OFF state and is ohmic in the ON state. Based on the results, the authors arrive at a general protocol that can be used to characterize memristors made of HOIPs and other related materials such that they can operate optimally.

Functional bipolar resistive switching in AlN/Ni–Mn–In based magnetoelectric heterostructure

This report explores the influence of temperature on resistive switching characteristics in the AlN/Ni–Mn–In magnetoelectric (ME) heterostructure-based resistive random access memory (ReRAM) device. The fabricated Cu/AlN/Ni–Mn–In/Si device exhibits a sharp transition from a high resistance state (HRS) to low resistance state (LRS) at a SET voltage. The rupture of the filament from its weakest point at a RESET voltage turn the device back to its HRS. The stable bipolar resistive switching behavior is described by the current–voltage (I–V) characteristic. The HRS and LRS are explained by the trap-controlled space charge limited conduction mechanism and a well-known Ohmic conduction mechanism, respectively. The temperature-dependent resistance has been observed to further confirm the conduction mechanism in HRS and LRS. The current conduction in LRS is explained by an analytical model based on copper metallic filament formation via Cu+ migration from the top to the bottom electrode. A significant change in the SET voltage has been observed with the decrease in temperature. This variation in the SET voltage is explained via strain-mediated coupling in interfacially connected AlN/Ni–Mn–In ME heterostructure. The fabricated device displays an appreciable OFF/ON ratio of the order ∼3 × 103 with good endurance and retention of ∼1000 cycles and ∼900 s, respectively. A slight variation (<40%) in SET and RESET voltages has been observed for total endurance cycles. This study demonstrates the importance of ME heterostructure for futuristic tuneable ReRAM applications.

Gradually Modified Conductance in the Self-Compliance Region of an Atomic-Layer-Deposited Pt/TiO2/HfAlOx/TiN RRAM Device

This study presents conductance modulation in a Pt/TiO2/HfAlOx/TiN resistive memory device in the compliance region for neuromorphic system applications. First, the chemical and material characteristics of the atomic-layer-deposited films were verified by X-ray photoelectron spectroscopy depth profiling. The low-resistance state was effectively controlled by the compliance current, and the high-resistance state was adjusted by the reset stop voltage. Stable endurance and retention in bipolar resistive switching were achieved. When a compliance current of 1 mA was imposed, only gradual switching was observed in the reset process. Self-compliance was used after an abrupt set transition to achieve a gradual set process. Finally, 10 cycles of long-term potentiation and depression were obtained in the compliance current region for neuromorphic system applications.

Resistive switching characteristics of epitaxial NiO thin films affected by lattice strains and external forces

We investigated the resistive switching characteristics of NiO films grown epitaxially on two single-crystal Rh and Ni substrates. Two epitaxial NiO films were relatively small compressive strained on the Rh substrate, and confirmed by the x-ray diffraction experiments that the strain was relatively large compressive on the Ni substrate. Comparing the forming, SET, and RESET voltages of NiO resistive switching random access memory capacitors, NiO films grown on the Ni substrates showed relatively higher voltages than Rh substrates. We propose that this compressive strain has an effect on raising the forming, SET, and RESET voltages. Furthermore, we observed that the forming voltage decreases while reducing the compressive strain by applying pressure to the NiO thin film grown on the Ni substrate with an atomic force microscope tip. In addition, we showed that relaxation of compressive strain by external force by first-principles calculations can reduce the oxygen deficiency energy and lower the forming voltage and working voltages, which supports the experimental results well.

Ion beam-assisted solid phase epitaxy of SiGe and its application for analog memristors

Low dimensional defects such as dislocation in single crystal Si are known to serve as a fast diffusion path of metal ions. Recently, many efforts have been made to employ dislocations in single crystal based oxide and silicon as reliable Ag filaments in CBRAM (Conductive Bridge Resistive Memory). In this study, we report the synthesis of the SiGe epitaxy thin films by an ion beam-assisted solid phase epitaxy process and its application for analog CBRAM memristors. The epitaxial SiGe thin films were produced by implanting Ge ions into a LPCVD a-Si film, followed by post annealing. We found that the interface oxide between a-Si and c-Si hinders facile epitaxy growth of a-Si. Thus, the ion implantation parameters were carefully adjusted to effectively remove the interface oxide and produce the epitaxy thin films of high quality. The low dimensional defects, identified to be a stacking fault by TEM observations, were observed to be densely located near the surface region of the SiGe epitaxy thin film. We fabricated the CBRAM devices by sandwiching the epitaxial Si thin films between an active metal electrode of Ag and a heavily doped Si wafer. We investigated the performances of the CBRAM devices and discuss the effect of the low dimensional defects on the switching behaviors of the devices. We found that the Ge implantation enables forming-free CBRAM operation and also provides reduced variations in set and reset voltages. Furthermore, we performed the feasibility study on the use of the epitaxial Si based CBRAM for artificial synapse for neuromorphic computing.

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.

Effects of heavy ion irradiation on Cu/Al2O3/Pt CBRAM devices

Abstract In this work, the effects of heavy ion irradiation on atomic switches with Cu/Al2O3/Pt structure are investigated. The initial device is prone to hard breakdown after forming, while the device after irradiation exhibits good performance such as stable operating voltage, non-volatile switching (a retention characteristic of 105 s at room temperature) and good endurance (2000 switching cycles). Compared with the device after low-dose irradiation, the device under higher-dose irradiation shows more uniform off-state resistances but no relevant changes were observed on distributions of on-state resistances, set and reset voltages.

Low power consumption photoelectric coupling perovskite memristor with adjustable threshold voltage

Organic–inorganic halide perovskites (OHPs) have been proven to possess unique optical and electrical properties, and achieved more extensive application as excellent materials for memristors in recent years. Based on the traditional OHP-based memristors, the intermediate layer of the memristor was prepared using yttrium oxide (Y2O3)/OHP stacking structure in this manuscript. The potential barrier between Y2O3 and perovskite is relatively high (ΔE C = 2.13 eV) which leads to comparatively low current of the memristor, thus the power consumption can be reduced. Besides, by changing the external light conditions, one can realize sharp or slow switch between high resistance state (HRS) and low resistance state (LRS), so as to meet the requirement of multilevel data storage, which indicates its promising application prospect in information storage and biological simulation. In addition, based on characteristics of photoelectric coupling, the Y2O3/OHP memristor can also achieve the advantage of adjustable threshold voltage. The transition of HRS and LRS can be realized by changing the illumination condition at any voltage, which means the set and reset voltage are not fixed, so that the memristor with adjustable threshold voltage can adapt to various working conditions.

Tri-Layer Structure ZnGa2O4-Based Resistive Random Access Memory

This study aimed to improve the performance of RRAM cell with switching layer of ZnGa2O4. We used radio frequency magnetron sputtering system to insert two layers of gallium-related oxide materials, Al0.05Ga0.95O and In0.9Ga0.1O, into the resistance-switching layer. The on/off ratio can be increased from 101 to 102 by inserting Al0.05Ga0.95O layer. Moreover, with the aids of In0.9Ga0.1O layer, reset voltage of the RRAM device can be reduced to −0.7 V. The heterostructure effectively increases the on/off ratio and lowers the working voltage of the device, which not only improves the memory characteristics but also decreases the power consumption. In addition, the heterojunction memory can switch between high- and low-resistance states more than 100 times and keep stable at each state for 10000 s at room temperature.

High switching uniformity in HfOx-based memristors by adding polydopamine-derived Ag nanoparticles on the electrode

In this Letter, a Ti/HfOx/Pt memristor with a modified Ti electrode created by inserting polydopamine (PDA)/Ag nanoparticles (AgNPs) between the Ti electrode and functional layer is reported. This memristor exhibits a significant improvement in the uniformity of device parameters [including set voltage, reset voltage, high resistance state (HRS) resistances, low resistance state (LRS) resistances, endurance, and retention] compared to conventional memristors. The AgNPs embedded in PDA renders a reduced variability in HRS and LRS resistances from 47% to 7%, and 46% to 11%, respectively. By fitting Poole–Frenkel and Ohmic behavior models, the consistency of the conductive mechanism of the devices before and after modification has been proven, which is further enhanced through variable temperature tests and the simulation of electric field distribution. It is believed that AgNPs play a lightning rod role in guiding the growth of conductive paths; thus, by growing AgNPs in situ on PDA film on the Ti electrode, it reduces the parameter variability.

Improved Device Distribution in High-Performance SiNx Resistive Random Access Memory via Arsenic Ion Implantation.

Large device variation is a fundamental challenge for resistive random access memory (RRAM) array circuit. Improved device-to-device distributions of set and reset voltages in a SiNx RRAM device is realized via arsenic ion (As+) implantation. Besides, the As+-implanted SiNx RRAM device exhibits much tighter cycle-to-cycle distribution than the nonimplanted device. The As+-implanted SiNx device further exhibits excellent performance, which shows high stability and a large 1.73 × 103 resistance window at 85 °C retention for 104 s, and a large 103 resistance window after 105 cycles of the pulsed endurance test. The current–voltage characteristics of high- and low-resistance states were both analyzed as space-charge-limited conduction mechanism. From the simulated defect distribution in the SiNx layer, a microscopic model was established, and the formation and rupture of defect-conductive paths were proposed for the resistance switching behavior. Therefore, the reason for such high device performance can be attributed to the sufficient defects created by As+ implantation that leads to low forming and operation power.

Light‐Assisted Resistive Switching Memory Device with Reduced SET/RESET Voltage Using Sol–Gel TiO2 on Al‐Doped ZnO Electrode

Herein, light‐assisted resistive switching (RS) characteristic of low‐cost sol–gel TiO2 film‐based metal–insulator–metal (MIM) configuration using Al‐doped ZnO (AZO) as the bottom electrode is demonstrated. Unprecedentedly, instead of the costly transparent conducting electrode such as tin‐doped indium oxide, AZO electrode is exploited in this study due to its dual role as a transparent and an additional oxygen vacancy (VO)‐rich electrode. The Al/TiO2/AZO device shows electroforming free bipolar RS characteristics, which can be explained by the formation (rupture) of conducting filaments composed of VO. The memory window is increased three times under the blue light illumination compared to dark conditions. Interestingly, the SET and RESET voltages are decreased from 5.2 to 4.5 V and −3.9 to −3.3 V, respectively, under the blue light illumination with respect to the dark condition. The enhancement in the RS effect under the blue light illumination is explained in terms of the photoresponsive properties of TiO2. The MIM device exhibits good switching repeatability with stable retention characteristics, making them attractive for next‐generation nonvolatile resistive random access memory devices.

Improved Synaptic Device Properties of HfAlOx Dielectric on Highly Doped Silicon Substrate by Partial Reset Process

This work demonstrates the synaptic properties of the alloy-type resistive random-access memory (RRAM). We fabricated the HfAlOx-based RRAM for a synaptic device in a neuromorphic system. The deposition of the HfAlOx film on the silicon substrate was verified by X-ray photoelectron spectroscopy (XPS) analysis. It was found that both abrupt and gradual resistive switching could be implemented, depending on the reset stop voltage. In the reset process, the current gradually decreased at weak voltage, and at strong voltage, it tended to decrease rapidly by Joule heating. The type of switching determined by the first reset process was subsequently demonstrated to be stable switching by successive set and reset processes. A gradual switching type has a much smaller on/off window than abrupt switching. In addition, retention maintained stability up to 2000 s in both switching cases. Next, the multiple current states were tested in the gradual switching case by identical pulses. Finally, we demonstrated the potentiation and depression of the Cu/HfAlOx/Si device as a synapse in an artificial neural network and confirmed that gradual resistive switching was suitable for artificial synapses, using neuromorphic system simulation.

Forming-free and multilevel resistive switching properties of hydrothermally synthesized hexagonal molybdenum oxide microrods

In recent years, resistive switching memory devices are attracted much attention for high-density non-volatile memory applications owing to their cell scalability, multilevel operations, and 3D capability in crossbar memory arrays. In this work, we report the forming-free and multilevel resistive switching properties of hydrothermally synthesized hexagonal molybdenum oxide (h-MoO3) microrods. The formation of h-MoO3 microrods was confirmed by using the X-ray diffraction technique and scanning electron microscopy. Different chemical properties of h-MoO3 microrods were determined by energy-dispersive X-ray, photoluminescence, Raman, and X-ray photoelectron spectroscopic techniques. The memory device was fabricated in a Ti/MoO3/FTO structure and its bipolar resistive switching properties were investigated. The memory device shows voltage-dependent tunable I-V properties and shows electroforming-free operation. Moreover, we have calculated the different memristive properties and showed that the device possesses double-valued charge-magnetic flux characteristics, suggesting the dominance of memristive properties in the Ti/MoO3/FTO device. We further explored the multilevel resistive switching property of the device by varying the RESET voltage. The Ti/MoO3/FTO memristive device can able to show four distinct resistive states during endurance and retention tests. The statistical analysis suggested that the device has less variation during the cycle-to-cycle operation. The device conduction mechanism was obtained by fitting different charge transport models, and a possible resistive switching mechanism is presented based on the observed multilevel resistive switching effect of the Ti/MoO3/FTO memristive device.

Effect of Light and Heat on Polymer‐Based Resistive Random Access Memory

Highly repeatable, photosensitive nonvolatile resistive random access memory (ReRAM) made of a Si/SiO2/Cu/PRPC/Ta stack with a photoresponsive polymer composite (PRPC) as the active medium is presented. The device shows errorless bipolar resistive switching with more than 100 cycles repeatability and stable SET and RESET voltages. It changes its resistive states in response to white light and recovers completely after removal of the light source. It also changes its state in response to heat and recovers randomly after the removal of the heat source. The phenomenon is explained by valance charge transfer along with a space‐charge‐limited conduction (SCLC) mechanism. The initial state of the device is low resistance state (LRS) because of electric‐field‐induced formation of valance charge transfer states. It switches to a high resistance state (HRS) due to electric‐field‐induced dissociation of the charge transfer states.

Stability-Enhanced Resistive Random-Access Memory via Stacked In x Ga1-x O by the RF Sputtering Method.

The stability of a resistive random-access memory (RRAM) device over long-term use has been widely acknowledged as a pertinent concern. For investigating the stability of RRAM devices, a stacked InxGa1–xO structure is designed as its switching layer in this study. Each stacked structure in the switching layer, formed via sputtering, consists of varying contents of gallium, which is a suppressor of oxygen vacancies; thus, the oxygen vacancies are well controlled in each layer. When a stacked structure with layers of different contents is formed, the original gradients of concentration of oxygen vacancies and mobility influence the set and reset processes. With the stacked structure, an average set voltage of 0.76 V, an average reset voltage of −0.66 V, a coefficient of variation of set voltage of 0.34, and a coefficient of variation of reset voltage of 0.18 are obtained. Additionally, under DC sweeps, the stacked RRAM demonstrates a high operating life of more than 4000 cycles. In conclusion, the performance and stability of the RRAM are enhanced herein by adjusting the concentration of oxygen vacancies via different compositions of elements.

Thickness scaling effects of self-assembled NiO nanodots on resistive switching characteristics

High-density resistive random access memory devices benefit from the reduction in the size of memory cells to a nanoscale. As the RRAM cells become smaller and denser, more stable operation is required. In this study, resistive switching characteristics of self-assembled NiO nanodots on Nb-doped SrTiO3 substrates were examined by using conducting atomic force microscopy. For the NiO nanodot thickness of 8, 6, and 4 nm, the forming voltages were 5.43, 4.63, and 4.12 V, respectively, indicating that the forming voltage decreased as the thickness of NiO nanodots decreased. The SET and RESET voltages also decreased (2.40 and 1.21 V for 8 nm, 2.11 and 0.96 V for 6 nm, 1.86 and 0.82 V for 4 nm, respectively). In addition, as the thickness of the NiO nanodots decreased, the distribution of forming voltages stabilized. We propose that the reduction of the forming voltage distribution is related to the volume of the conductive filaments that were formed in the nanodots. The fabrication of NiO nanodots and the detailed investigation of resistive switching characteristics that depend on the size of the nanodots provide valuable insights for future NiO nanodot resistive random access memory devices.

Self-assembling crystalline peptide microrod for neuromorphic function implementation

Self-assembling crystalline peptide microrod for neuromorphic function implementation

Analysis of the transient Joule heating effect in a conductive-bridge random-access memory (CBRAM) using a single-phase-lag (SPL) model

The main objective of this work is to study the transient Joule heating effect in a conductive-bridge random-access memory (CBRAM) using the single-phase-lag heat conduction model to describe the effects of the metallic conductive filament (CF) radius and the reset voltage on the thermal and electric field. The results reveal that the CF geometry plays an important role in the transient Joule heating. The heat wave of fast transient conduction is stronger in the narrow region of the CF during the reset process for a high applied voltage and a small top radius of the CF. It is demonstrated that the presented model can predict the nanoscale heat transfer in the transient state and during the reset process in the CBRAM. Finally, numerical computations are carried out using the finite-element method to solve the nonlinear heat conduction equations.

A New Perspective Towards the Understanding of the Frequency-Dependent Behavior of Memristive Devices

As theoretically predicted by Prof. Chua, the input signal frequency has a major impact on the electrical behavior of memristors. According with one of the so-called fingerprints of such devices, the resistive window, i.e. the difference between the low and high resistance states, shrinks as the frequency increases. Physically, this effect stems from the incapability of ions/vacancies to follow the external electrical stimulus. In terms of the electrical behavior, the collapse of the resistive window can be ascribed to the shift of the set and reset voltages toward higher values. In addition, for a fixed frequency, the resistive window increases with the signal amplitude. In this letter, we show that both phenomena, decrease and increase of the resistive window, can be consistently explained after considering the snapback effect and a balance model equation for the memory state of the device.