Resistive Switching Operation Research Articles

Different PCA approaches for vector functional time series with applications to resistive switching processes

This paper is motivated by modeling the cycle-to-cycle variability associated with the resistive switching operation behind memristors. Although the data generated by this stochastic process are by nature current–voltage curves associated with the creation (set process) and destruction (reset process) of a conductive filament, the statistical analysis is usually based on analyzing only the scalar time series related to the reset and set voltages/currents in consecutive cycles. As the data are by nature curves, functional principal component analysis is a suitable candidate to explain the main modes of variability associated with these processes. Taking into account this data-driven motivation, in this paper we propose two new forecasting approaches based on studying the sequential cross-dependence between and within a multivariate functional time series in terms of vector autoregressive modeling of the most explicative functional principal component scores. The main difference between the two methods lies in whether a univariate or multivariate PCA is performed so that we have a different set of principal component scores for each functional time series or the same one for all of them. Finally, the sample performance of the proposed methodologies is illustrated by an application on a bivariate functional time series of reset/set curves.

A High-Entropy-Oxides-Based Memristor: Outstanding Resistive Switching Performance and Mechanisms in Atomic Structural Evolution.

The application of high-entropy oxide (HEO) has attracted significant attention in recent years owing to their unique structural characteristics, such as excellent electrochemical properties and long-term cycling stability. However, the application of resistive random-access memory (RRAM) has not been extensively studied, and the switching mechanism of HEO-based RRAM has yet to be thoroughly investigated. In this study, HEO (Cr, Mn, Fe, Co, Ni)3 O4 with a spinel structure is epitaxially grown on a Nb:STO conductive substrate, and Pt metal is deposited as the top electrode. After the resistive-switching operation, some regions of the spinel structure are transformed into a rock-salt structure and analyzed using advanced transmission electron microscopy and scanning transmission electron microscopy. From the results of X-ray photoelectron spectroscopy and electron energy loss spectroscopy, only specific elements would change their valence state, which results in excellent resistive-switching properties with a high on/off ratio on the order of 105 , outstanding endurance (>4550 cycles), long retention time (>104 s), and high stability, which suggests that HEO is a promising RRAM material.

Electromechanical Switching of a C60 Chain in a Nanogap

Electromechanical switching in fullerene C60 nanochains, introduced in the device as a C60 pyrrolidine tris-acid (CPTA) film, was realized in nanogap electrodes with ∼20 nm separation. Unlike microscale C60 channels, a conductive C60 chain spontaneously formed in the nanogap without electron beam irradiation. The initial current flow was likely due to electron hopping through the CPTA molecules. A higher voltage generated a nonlinear current and caused a rapid current step to drastically generate a large current flow. A further high current generated a sudden current reduction recognized as the negative differential resistance, suggesting a resistance state change from a low state to a high state. At the high-resistance state, a step-like current increase changed the nanochain conduction to the low-resistance state. The high- to low-resistance state switching was reproducible, and a sequential input voltage executed a binary resistance switching operation at room temperature. From the switching voltage and current values, the switching energy for the C60 chain in the nanogap was estimated to be approximately several milliwatts, most probably caused by the polymerization and depolymerization of the conductive C60 chain.

Picosecond Time‐Scale Resistive Switching Monitored in Real‐Time

AbstractThe resistance state of filamentary memristors can be tuned by relocating only a few atoms at interatomic distances in the active region of a conducting filament. Thereby the technology holds promise not only in its ultimate downscaling potential and energy efficiency but also in unprecedented speed. Yet, the breakthrough in high‐frequency applications still requires the clarification of the dominant mechanisms and inherent limitations of ultra‐fast resistive switching. Here bipolar, multilevel resistive switchings are investigated in tantalum pentoxide based memristors with picosecond time resolution. Cyclic resistive switching operation due to 20 ps long voltage pulses of alternating polarity are experimentally demonstrated. The analysis of the real‐time response of the memristor reveals that the set switching can take place at the picosecond time‐scale where it is only compromised by the bandwidth limitations of the experimental setup. In contrast, the completion of the reset transitions significantly exceeds the duration of the ultra‐short voltage bias, demonstrating the dominant role of thermal diffusion and underlining the importance of dedicated thermal engineering for future high‐frequency memristor circuit applications.

Thermal Characterization of Conductive Filaments in Unipolar Resistive Memories.

A methodology to estimate the device temperature in resistive random access memories (RRAMs) is presented. Unipolar devices, which are known to be highly influenced by thermal effects in their resistive switching operation, are employed to develop the technique. A 3D RRAM simulator is used to fit experimental data and obtain the maximum and average temperatures of the conductive filaments (CFs) that are responsible for the switching behavior. It is found that the experimental CFs temperature corresponds to the maximum simulated temperatures obtained at the narrowest sections of the CFs. These temperature values can be used to improve compact models for circuit simulation purposes.

High-temperature operation of gallium oxide memristors up to 600 K

Memristors have attracted much attention for application in neuromorphic devices and brain-inspired computing hardware. Their performance at high temperatures is required to be sufficiently reliable in neuromorphic computing, potential application to power electronics, and the aerospace industry. This work focuses on reduced gallium oxide (GaOx) as a wide bandgap memristive material that is reported to exhibit highly reliable resistive switching operation. We prepared amorphous GaOx films to fabricate Pt/GaOx/indium tin oxide memristors using pulsed laser deposition. Stable resistive switching phenomena were observed in current–voltage properties measured between 300 and 600 K. The conduction mechanism analysis revealed that the resistive switching is caused by the transition between ohmic and space charge limiting current conductions. We elucidated the importance of appropriate control of the density of oxygen vacancies to obtain a high on/off resistance ratio and distinct resistive switching at high temperatures. These results indicate that GaOx is a promising memristor material that can be stably operated even at the record-high temperature of 600 K.

Interface engineering of amorphous gallium oxide crossbar array memristors for neuromorphic computing

This paper reports on the fabrication and characterization of crossbar array memristors using amorphous gallium oxide (a-GaO x ) for implementing high-speed and wide-dynamic range artificial synaptic functions. The a-GaO x memristors were fabricated by pulsed laser deposition in an argon atmosphere using a platinum bottom electrode and an indium tin oxide (ITO) top electrode. We revealed that the interface engineering at a-GaO x /ITO is the key to demonstrating exemplary resistive switching operation. Stable counter figure-8 hysteresis loops were obtained by voltage application, leading to the successful demonstration of non-volatile retention over 104 s and the multi-level conductance modulation. Furthermore, spike-timing-dependent plasticity (STDP) was artificially implemented by applying pre- and post-spike voltages to the device. Consequently, significant weight-change rates were achieved in the asymmetric STDP imitation, which can be attributed to the reliable resistive switching properties of the device with an extensive dynamic range. These results indicate that the a-GaO x crossbar array memristor is a promising hardware platform for neuromorphic computing applications.

An atomistic modeling framework for valence change memory cells

We present a framework dedicated to modeling the resistive switching operation of Valence Change Memory (VCM) cells. The method combines an atomistic description of the device structure, a Kinetic Monte Carlo (KMC) model for the creation and diffusion of oxygen vacancies in the central oxide under an external field, and an ab initio quantum transport method to calculate electrical current and conductance. As such, it reproduces a realistically stochastic device operation and its impact on the resulting conductance. We demonstrate this framework by simulating a switching cycle for a TiN/HfO2/TiN VCM cell, and see a clear current hysteresis between high/low resistance states, with a conductance ratio of one order of magnitude. Additionally, we observe that the changes in conductance originate from the creation and recombination of vacancies near the active electrode, effectively modulating a tunneling gap for the current. This framework can be used to further investigate the mechanisms behind resistive switching at an atomistic scale and optimize VCM material stacks and geometries.

Investigation of Barrier Layer Effect on Switching Uniformity and Synaptic Plasticity of AlN Based Conductive Bridge Random Access Memory

In this work, we investigated the effect of the tungsten nitride (WNx) diffusion barrier layer on the resistive switching operation of the aluminum nitride (AlN) based conductive bridge random access memory. The WNx barrier layer limits the diffusion of Cu ions in the AlN switching layer, hence controlling the formation of metallic conductive filament in the host layer. The device operated at a very low operating voltage with a Vset of 0.6 V and a Vreset of 0.4 V. The spatial and temporal switching variability were reduced significantly by inserting a barrier layer. The worst-case coefficient of variations (σ/µ) for HRS and LRS are 33% and 18%, respectively, when barrier layer devices are deployed, compared to 167% and 33% when the barrier layer is not present. With a barrier layer, the device exhibits data retention behavior for more than 104 s at 120 °C, whereas without a barrier layer, the device fails after 103 s. The device demonstrated synaptic behavior with long-term potentiation/depression (LTP/LTD) for 30 epochs by stimulating with a train of identical optimized pulses of 1 µs duration.

Linearly potentiated synaptic weight modulation at nanoscale in a highly stable two-terminal memristor

The fabrication of nanoscale electronic synapses is an essential step towards the development of neuromorphic devices having a high integration density. Excellent learning abilities of such electronic synapses are crucial for the emulation of human brain potentialities. In order to achieve the same, linearly potentiated synaptic weight modulation (having negligible variability at nanoscale) is a primary and essential requirement. Here, we investigate solid-state memristor-based nanoscale synaptic emulators that exhibit linearly potentiated synaptic weight entries irrespective of amplitude, width, and frequency of the input voltage pulses. The memristive synapses under consideration replicate all the essential synaptic functions including potentiation and depression, spike-rate dependent plasticity, paired-pulse facilitation, and both excitatory-inhibitory responses and therefore, fulfil the requirements to build neuromorphic devices which can emulate brain-like functionalities. The incorporation of metallic ions in an amorphous oxide thin film leads to both distinctly linear weight adjustability and highly stable resistive switching operation which depend on the amplitude of the driving bias voltage. This study will help to understand and optimize the linearity in performances of oxide memristor-based synapses for neuromorphic applications.

Relationship between resistive switching and Mott transition in atomic layer deposition prepared La2Ti2O7-x thin film

This study prepared Mott-metal state thin film La2Ti2O7-x on TiN substrate using atomic layer deposition, and confirmed W/La2Ti2O7-x/TiN clockwise forming-less resistive switching. The resistive switching mechanism was voltage-driven and oxygen vacancy doping-controlled Mott transition. Positive voltage induces the formation of oxygen vacancy in La2Ti2O7-x and change it from Mott-metal to Mott-insulator state, with the process reversible under negative voltage. We show that N doping can reduce the Ti3+ ratio in La2Ti2O7-x film, producing a weakly correlated system compared with La2Ti2O7-x film without N-doping. Nitrogen doping also increased resistive switching operation voltage and reduced La2Ti2O7-x film on/off ratio. Thus, La2Ti2O7-x, was a promising candidate for the fabrication of resistive switching device based on Mott transition.

Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective

We have analyzed variability in resistive memories (Resistive Random Access Memories, RRAMs) making use of advanced numerical techniques to process experimental measurements and simulations based on the kinetic Monte Carlo technique. The devices employed in the study were fabricated using the TiN/Ti/HfO2/W stack. The switching parameters were obtained making use of new developed extraction methods. The appropriateness of the advanced parameter extraction methodologies has been checked by comparison to kinetic Monte Carlo simulations; in particular, the reset and set events have been studied and detected. The data obtained were employed to shed light on the resistive switching operation and the cycle-to-cycle variability. It has been shown that variability depends on the numerical technique employed to obtain the set and reset voltages, therefore, this issue must be taken into consideration in RS characterization and modeling studies. The proposed techniques are complementary and depending on the technology and the curves shape the features of a particular method could make it to be the most appropriate.

Multi-Level Resistive Switching of Pt/HfO2/TaN Memory Device

This work characterizes resistive switching and neuromorphic simulation of Pt/HfO2/TaN stack as an artificial synaptic device. A stable bipolar resistive switching operation is performed by repetitive DC sweep cycles. Furthermore, endurance (DC 100 cycles) and retention (5000 s) are demonstrated for reliable resistive operation. Low-resistance and high-resistance states follow the Ohmic conduction and Poole–Frenkel emission, respectively, which is verified through the fitting process. For practical operation, the set and reset processes are performed through pulses. Further, potentiation and depression are demonstrated for neuromorphic application. Finally, neuromorphic system simulation is performed through a neural network for pattern recognition accuracy of the Fashion Modified National Institute of Standards and Technology dataset.

Retention enhancement through capacitance-dependent voltage division analysis in 3D stackable TaOx/HfO2-based selectorless memristor

Sneak path current generated by adjacent cells in three-dimensional (3D) memristor arrays must be curbed while securing the multi-bit storage capability of each cell to aid in the cost-effective increase in array size. For this purpose, a 3D stackable TaOx/HfO2-based selectorless memristor has been proposed and optimized via capacitance-dependent voltage division analysis. The proposed device utilizes the formation or rupture of conductive filaments for self-rectifying resistive switching operation, in contrast to nonfilamentary devices that often exploit the change in the charge state of the electron trap. This approach enables the reduction of the trapped charge leakage through the interface between the resistive switching and metal layers effectively, giving rise to excellent retention properties (>5 × 105 s). Furthermore, the proposed device exhibits a sufficiently high on/off ratio (~1.35 × 103), rectification ratio (~2.3 × 103), endurance (1.5 × 102 cycles), and low resistance variation (standard deviation <0.022). Moreover, multilevel operations are facilitated, making the proposed device suitable for high-density, nonvolatile memory applications.

On the Thermal Models for Resistive Random Access Memory Circuit Simulation.

Resistive Random Access Memories (RRAMs) are based on resistive switching (RS) operation and exhibit a set of technological features that make them ideal candidates for applications related to non-volatile memories, neuromorphic computing and hardware cryptography. For the full industrial development of these devices different simulation tools and compact models are needed in order to allow computer-aided design, both at the device and circuit levels. Most of the different RRAM models presented so far in the literature deal with temperature effects since the physical mechanisms behind RS are thermally activated; therefore, an exhaustive description of these effects is essential. As far as we know, no revision papers on thermal models have been published yet; and that is why we deal with this issue here. Using the heat equation as the starting point, we describe the details of its numerical solution for a conventional RRAM structure and, later on, present models of different complexity to integrate thermal effects in complete compact models that account for the kinetics of the chemical reactions behind resistive switching and the current calculation. In particular, we have accounted for different conductive filament geometries, operation regimes, filament lateral heat losses, the use of several temperatures to characterize each conductive filament, among other issues. A 3D numerical solution of the heat equation within a complete RRAM simulator was also taken into account. A general memristor model is also formulated accounting for temperature as one of the state variables to describe electron device operation. In addition, to widen the view from different perspectives, we deal with a thermal model contextualized within the quantum point contact formalism. In this manner, the temperature can be accounted for the description of quantum effects in the RRAM charge transport mechanisms. Finally, the thermometry of conducting filaments and the corresponding models considering different dielectric materials are tackled in depth.

Effect of Ag doping on bipolar switching operation in molybdenum trioxide (MoO3) nanostructures for non-volatile memory

As an emerging technology, nanoscale non-volatile memory technology can be used for in-memory computing and neuromorphic computing. However, the deeper understanding of the charge transport and resistive switching mechanism in memristor devices are still needed to improve the device properties for practical application. Herein, we first synthesized the MoO3 nanorods and studied the structural properties by XRD, SEM and TEM. The elemental compositions were confirmed through EDX and XPS analysis. The resistive switching operation of Au/ MoO3/p-Si ReRAM device was examined and its conductive mechanism was analyzed by space-charge limited conduction theory. The changes of high resistive state to low resistive state and vice-versa in ReRAM device is owing to the movement of oxygen vacancies in MoO3 structure. For comparison, silver atoms were intercalated into MoO3 Nanostructures and device performance was also analyzed. The improved switching behavior of Ag doped Au/ MoO3/p-Si device is due to Ag doping effect in the formation of conducting paths in the MoO3 active material. The obtained results indicate the contribution of Ag atoms in conduction filament enhance the bipolar resistive switching performance.

Effects of electric and magnetic fields on the resistive switching operation of iPCM

Interfacial phase change memory devices based on chalcogenide superlattices show a remarkable performance improvement over traditional phase change memory devices. Here, we report on the effects of the resistive switching of Ge–Te/Sb–Te superlattices in the presence of an external magnetic field at elevated temperature. In addition to the unique thermal dependence of the switching behavior, a new resistance level was found. This resistance level, once initiated, could be then obtained without a magnetic field. The observed phenomena are associated with the structural reconfiguration of domains at the superlattice interfaces and grain boundaries. It has been proposed that these effects may be caused by the localization of spin-polarized electrons generated by a combination of electric and magnetic fields in the ferroelectric phase of the superlattice.

Initial states and analog switching behaviors of two major tantalum oxide resistive memories

A systematic study was performed to understand the two major operation modes, valence change memory (VCM) and electrochemical memory (ECM), of tantalum oxide resistive memory, which were categorized by the type of conductive filament. The tantalum oxide insulator layer was predictably fabricated to modify the pristine oxygen-vacancy concentration in the insulator layer, where tantalum and copper top electrodes were used to achieve VCM and ECM modes. The distinguishable characteristics of the initial state and analog resistive switching operation revealed the prerequisites for switching capabilities and demonstrated the effects of oxygen vacancies in the two switching modes.

Low power high speed 3-bit multilevel resistive switching in TiO2 thin film using oxidisable electrode

Multilevel cell (MLC) capability of a memory device is an attractive alternative to realise high integration density of memory arrays. In addition, power efficient memory cell along with MLC capability has huge potential in neuromorphic computing and data storage applications. In this study low power, high speed and 3-bit multilevel bipolar resistance switching operation is reported in TiO2 thin films where copper is used as counter electrode. On account of using an oxidisable electrode, low programming voltages (∼+0.2 V, −0.1 V) along with low reset current (∼10 µA) are observed, thereby ensuing low power (∼µW) memory operation. Additionally, observation of fast switching (∼250 ns) translated to ultra-low energy (∼pJ) consumption. By varying compliance current (IC) from 25 µA to 1.6 mA during the set process, eight distinct non-volatile resistance states are reliably obtained, which showed statistically significant and non-overlapping resistance distribution. The multilevel resistive switching in Cu/TiO2/Pt device is explained by considering filamentary the widening phenomenon in the electrochemical metallization memory cell. Numerical calculations revealed that increase in the diameter of the metallic conducting filament from ∼3 nm to 70 nm with increasing IC is accountable for multiple low resistance states. The results of this study are promising towards realisation of emerging memory devices with low operating power, fast switching operation and high spatial density.

A Memristor with Low Switching Current and Voltage for 1S1R Integration and Array Operation

AbstractMemristor devices could realize their full scaling (2D) and stacking (3D) potential if vertically integrated with a two‐terminal selector in a one selector one memristor (1S1R) crossbar array. However, for a 1S1R‐integrated device to function properly, memristor and selector should be compatible in terms of their material composition and electrical properties. A platinum (Pt)/yttria‐stabilized zirconia (YSZ)/zirconium (Zr) memristor with low forming voltage (&lt;1.5 V), low first reset current (150 µA), fast switching speed (2 ns), low voltage (&lt;1 V) and current (50 µA) resistive switching operation, and multi‐conductance state capabilities is reported. A low activation energy of oxygen vacancy diffusion (Ea,diffusion = 0.7 eV) measured in the YSZ switching layer enables the proposed memristor to have the observed low‐energy operation, which renders it better compatible with a selector device than the more commonly used binary oxides. For a proof‐of‐principle demonstration, the device is vertically integrated with a tunneling selector and successfully performs memristor‐electroforming operations with the selector in a self‐compliant 1S1R integrated device. 1S1R cells into a small array (2 × 2) are further investigated and electroforming and resistive switching operations at the array level are demonstrated.