Conductive Bridge Random Access Memory Research Articles

Controlling diffusion dynamics with electrode engineering for stable and reliable resistive switching in AlN/Ag-based CBRAM

Due to high scalability, quick operating speed, wide dynamic on–off resistance range, and analog current switching, cation migration-based conductive bridge random access memory (CBRAM) has received much attention for a wide range of applications including data storage, logic gates, and neuromorphic circuits. However, Inadequate controllability of metal-ion injection and the creation of numerous filaments are the major issues for the switching stability. In this work, we investigated Ag/Ta/Ag stacked electrode structure to improve cycle-to-cycle and device-to-device switching uniformity by controlling the Ag-ion diffusion into the host material. The device shows stable dc endurance for 100 switching cycles without much degradation. The data retention behavior for 104 s is observed in the stacked electrode device at room temperature as well as an elevated temperature of 80 °C. The proposed device emulates biological synaptic functionality by demonstrating long-term potentiation(LTP) and depression (LTD) behavior for 10 epochs.

Two-Dimensional (2D) Materials-Inserted Conductive Bridge Random Access Memory: Controllable Injection of Cations in Vertical Stacking Alignment of MoSe2 Layers Prepared by Plasma-Assisted Chemical Vapor Reaction

Two-Dimensional (2D) Materials-Inserted Conductive Bridge Random Access Memory: Controllable Injection of Cations in Vertical Stacking Alignment of MoSe₂ Layers Prepared by Plasma-Assisted Chemical Vapor Reaction

Pulse-stream impact on recognition accuracy of reservoir computing from SiO2-based low power memory devices

Reservoir computing (RC)-based neuromorphic applications exhibit extremely low power consumption, thus challenging the use of deep neural networks in terms of both consumption requirements and integration density. Under this perspective, this work focuses on the basic principles of RC systems. The ability of self-selective conductive-bridging random access memory devices to operate in two modes, namely, volatile and non-volatile, by regulating the applied voltage is first presented. We then investigate the relaxation time of these devices as a function of the applied amplitude and pulse duration, a critical step in determining the desired non-linearity by the reservoir. Moreover, we present an in-depth study of the impact of selecting the appropriate pulse-stream and its final effects on the total power consumption and recognition accuracy in a handwritten digit recognition application from the National Institute of Standards and Technology dataset. Finally, we conclude at the optimal pulse-stream of 3-bit, through the minimization of two cost criteria, with the total power remaining at 287 µW and simultaneously achieving 82.58% recognition accuracy upon the test set.

Ultralow Operating Voltage Nb2O5-Based Multilevel Resistive Memory with Direct Observation of Cu Conductive Filament

Amorphous Nb2O5 is proposed as the resistive switching layer for conductive bridge random access memory. The Nb2O5 device is fabricated with the top Cu and bottom Au electrodes, which is fabricated at a fully room temperature process, exhibiting excellent resistive switching performance with an on/off ratio of up to 105 and ultralow operating voltage. The multilevel resistive switching characteristic can be rationally demonstrated by changing the compliance current in the Nb2O5 device. Each level of the resistance state is uniform with distinguishable read windows. The reset voltage reduces significantly as the compliance current decreases, which is merely 0.002 V when the compliance current is 10–5 A. An approach of the broken-down device is elaborately developed to firmly identify the migration of Cu and the existence of a Cu conductive filament and to explain the ultralow operating voltage. Amorphous Nb2O5 devices exhibit excellent resistive switching performance, proving it is a promising material for memory applications.

Recent Progress of the Cation Based Conductive Bridge Random Access Memory

Demand for new computing systems equipped with ultra-high-density memory storage and new computer architecture is rapidly increasing with the tremendous increment of the amount of data produced and/or reproduced. In particular, the requirement for technology development is growing as conventional storage devices face the physical limitations for scaling down and the data bottleneck that the Von Neumann architecture increases. Among the recent emerging memory devices, the conductive bridge random access memory (CBRAM) has superior switching properties and excellent scalability to be adopted as the next-generation storage device and as the hardware implementation of the neuromorphic computing system. In this review, the previous papers on the resistive switching mechanism of CBRAM and the precedent CBRAM devices exploiting various materials proposed by many research groups are introduced. The principle of CBRAM is discussed including the operation mechanism, switching materials, and the challenges that need to be solved. A wide selection of materials including metal oxides, Chalcogenides, and other non-oxides have been examined as the electrolyte layer of the CBRAM. Various switching materials, device engineering, and material innovation approaches were introduced, and the research results for solving the problems of CBRAM were reviewed in depth.

Insights on the variability of Cu filament formation in the SiO2 electrolyte of quantized-conductance conductive bridge random access memory devices

Conductive bridge random access memory devices such as Cu/SiO2/W are promising candidates for applications in neuromorphic computing due to their fast, low-voltage switching, multiple-conductance states, scalability, low off-current, and full compatibility with advanced Si CMOS technologies. The conductance states, which can be quantized, originate from the formation of a Cu filament in the SiO2 electrolyte due to cation-migration-based electrochemical processes. A major challenge related to the filamentary nature is the strong variability of the voltage required to switch the device to its conducting state. Here, based on a statistical analysis of more than hundred fifty Cu/SiO2/W devices, we point to the key role of the activation energy distribution for copper ion diffusion in the amorphous SiO2. The cycle-to-cycle variability is modeled well when considering the theoretical energy landscape for Cu diffusion paths to grow the filament. Perspectives of this work point to developing strategies to narrow the distribution of activation energies in amorphous SiO2.

Resistive Switching Characteristic of Cu Electrode-Based RRAM Device

The conductive bridge random access memory (CBRAM) device has been widely studied as a promising candidate for next-generation nonvolatile memory applications, where Cu as an electrode plays an important role in the resistive switching (RS) process. However, most studies only use Cu as one electrode, either the top electrode (TE) or the bottom electrode (BE); it is rarely reported that Cu is used as both TE and BE at the same time. In this study, we fabricated CBRAM devices by using Cu as both the TE and BE, and studied the RS characteristic of these devices. With Al2O3 as the switching layer (5~15 nm), the devices showed good bipolar RS characteristics. The endurance of the device could be as high as 106 cycles and the retention time could be as long as 104 s. The Al2O3 thickness influences the bipolar RS characteristic of the devices including the initial resistance, the forming process, endurance, and retention performance. The Cu electrode-based RRAM devices also present negative bias-suppressed complementary resistive switching (CRS) characteristics, which makes it effective to prevent the sneak path current or crosstalk problem in high-density memory array circuits.

Electric-Field-Induced Metal Filament Formation in Cobalt-Based CBRAM Observed by TEM

Conductive-bridging random access memory (CBRAM) using a cobalt (Co) electrode has recently featured a CMOS-compatible process, excellent data retention, and a sub-μA operating current level, which are difficult to achieve by conventional CBRAM. However, the resistive switching (RS) mechanism of Co CBRAM has not been extensively explored compared to that of the conventional CBRAM cells using Ag, Cu, or Ni as active metal electrodes. Because only implicit inferences based on electrical measurements have been made, the formation of Co filaments is not yet clearly understood. This study presents evidence of Co filament formation in Co/10 nm SiOx/TiN resistive random access memory (RRAM) using direct transmission electron microscopy (TEM) observations. Co protrusions larger than 5 nm are observed, and their exact atomic composition is investigated by spectroscopy. We explain the RS operation of Co/SiOx/TiN cells based on the Co electromigration-mediated filament development process through Co electrode deformation, protrusion, and subsequent Co conductive bridge formation. An asymmetric RS operation and negative temperature correlation of the resistance are found in low resistance state (LRS) cells, which further supports the Co-involved RS operation in Co/SiOx/TiN devices.

Multiscale Modeling of Metal-Oxide-Metal Conductive Bridging Random-Access Memory Cells: From Ab Initio to Finite-Element Calculations

Continuum modeling is a popular, computationally efficient technique that can shed light on the resistance-switching properties of conductive bridging random-access memory (CBRAM) cells. Traditional models typically rely on many fitting parameters, but this approach uses material parameters extracted either from either ab initio or machine-learned empirical calculations. As proof of concept, the authors apply the computational framework to an SiO${}_{2}$-based CBRAM cell, and reveal the relevance of Joule heating in nanoscale devices. With the proposed multiscale methodology it is possible to explore the potential of not-yet-fabricated memory cells, and to optimize their design reliably.

Vacuum gap atomic switch with improved controllability of quantized conduction states and low transition energy

To maximize the multilevel data storage capability for high-density memory applications, precise control of quantized conduction with ultralow transition energy is required. We report the quantized conduction in Ag/Ag2S/vacuum conductive-bridge random access memory under various pulse conditions to regulate atomic motion at room temperature. Using stochastic analysis, we unveil a pulse condition for supplying the optimal energy that allows precise atom detachment and has a high dissolution probability. In addition, we calculate the transition energy required to change each quantized state for an Al2O3 electrolyte and vacuum gap. We determine a large transition energy of Ag in Al2O3 (8–1 mJ), hindering the precise control of quantized conduction, whereas the transition energy of Ag in vacuum is relatively low (397–95 nJ), enabling proper atomic motion.

Reconfigurable Logic Operation Scheme Based on Gate-Tunable CBRAM

The traditional von Neumann architecture features large transfer latency and power dissipation. In-memory computing has been widely investigated in an effort to negotiate this hurdle. Herein, gate-tunable conductive bridge random access memory (GCBRAM) is proposed to construct in-memory computing. GCBRAM has a flexible modulation dimension, which can reduce the sensitivity of the selection of compensation resistors. A reconfigurable logic circuit based on GCBRAM has been developed, and the quantity of compensation resistors has been reduced. A full adder based on a GCBRAM circuit has been demonstrated, and the number of compensation resistors has been minimized compared with previous results using basic logic gates. To the best of our knowledge, full adder based on GCBRAM (six GCBRAM, seven steps) is the most compact form developed to date. This work represents the realization of a new form of in-memory logic with lower hardware costs, which can facilitate the development of in-memory computing.

Introduction of defects in hexagonal boron nitride for vacancy-based 2D memristors.

Two-dimensional (2D) materials have become potential resistive switching (RS) layers to prepare emerging non-volatile memristors. The atomically thin thickness and the highly controllable defect density contribute to the construction of ultimately scaled memory cells with stable switching behaviors. Although the conductive bridge random-access memory based on 2D hexagonal boron nitride has been widely studied, the realization of RS completely relying on vacancies in 2D materials has performance superiority. Here, we synthesize carbon-doped h-BN (C-h-BN) with a certain number of defects by controlling the weight percentage of carbon powder in the source. These defects can form a vacancy-based conductive filament under an applied electric field. The memristor displays bipolar non-volatile memory with a low SET voltage of 0.85 V and shows a long retention time of up to 104 s at 120 °C. The response times of the SET and RESET process are less than 80 ns and 240 ns, respectively. The current mapping by conductive atomic force microscopy demonstrates the electric-field-induced current tunneling from defective sites of the C-h-BN flake, revealing the defect-based RS in the C-h-BN memristor. Moreover, C-h-BN with excellent flexibility can be applied to wearable devices, maintaining stable RS performance in a variety of bending environments and after multiple bending cycles. The vacancy-based 2D memristor provides a new strategy for developing ultra-scaled memory units with high controllability.

Self-compliance and high-performance GeTe-based CBRAM with Cu electrode

Conductive bridging random access memory (CBRAM) has been considered as a promising candidate for next-generation non-volatile memory. However, there are always problems of high-power consumption in CBRAM. In this study, a GeTe-based resistive random access memory (RRAM) with an active Cu electrode is fabricated, which reveals significant behavior of low forming voltage (<|-2|V). At the same time, the device exhibits the property of self-compliance, which is essential for protection of the device and reduction of the leakage current. Furthermore, the resistance switching (RS) mechanism of the device is proved to be filament-type, which helps explain the self-compliance phenomenon in detail. These properties provide an effective solution to the achievement of low-power consumption in CBRAM, and show a potential for the scalability of the device and high-density integration in the cross-bar array.

Insights into few-atom conductive bridging random access memory cells with a combined force-field/ab initio scheme

We present a simulation framework to simulate the switching behavior of Ag/a-SiO2 conductive bridging random access memories (CBRAM). Whereas the dynamics of the switching process is investigated with classical molecular dynamics simulations using a force-field, the electrical properties are determined through ab initio calculations. With a structural analysis of the oxide, we shed light on the switching mechanism, which relies on preferred channels containing wide SiO2 rings through which Ag+ ions migrate. Also, we demonstrate that moving only few atoms in such channels can change the resistance state by several orders of magnitude.

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.

(Digital Presentation) Power Efficient Transistors with Low Subthreshold Swing Using Abrupt Switching Devices

With the rapid development of transparent integrated circuits, transistors with extremely low subthreshold swing (SS) is becoming a necessary requirement. Here, we fabricated three transparent device structures that show abrupt electrical switching and make their series connection to the source terminal of the conventional field effect transistors (FET) to lower the SS value. Firstly, we demonstrate an environment friendly, disposable, and transparent conductive bridge random access memory (CBRAM) device composed of a cellulose nanocrystals active layer. Our CBRAM consists of a silver (Ag) electrochemically active top electrode and a cellulose nanocrystals-based switching layer on the FTO coated glass substrate. Devices with CBRAM can enable FET with an ultra-steep slope that is SS < 0.24 mV/dec and has a significantly high on/off ratio (~105) by switching the Ag metallic filament between on and off. Niobium oxide (NbO2) based threshold switching devices and zinc oxide (ZnO) based flexible Schottky diodes that show electrical breakdown were also stacked with FET, which gave SS values < 0.74 mV/dec and < 5.20 mV/dec, respectively. Comparatively, a nano-watt transistor called filament transistor (FET + CBRAM stack) can significantly improve the SS slope value with the lowest leakage current (~nA) and a record low turn on-voltage (~0.2 V) with a set power of only ~197 nW compared to the other series stack, which thereby attracts the attention of low power operations. Keywords: filament transistor, threshold switching, Schottky diode, subthreshold swing, on/off ratio Figure 1

Dual Threshold and Memory Switching Induced By Conducting Filament Morphology in Ag/WSe2 Based ECM Cell

In recent years, two-dimensional (2D) materials-based RRAMs have gained high importance because of their thermal and mechanical stability, and better potentiation-depression controllability. 2D materials based conductive bridge random access memory (CBRAM) has been considered as promising approach for neuromorphic and image processing technology [1]. Despite much progress in CMOS technology, the growth and deposition technology of 2D materials for semiconductor integrated circuit are much complex and is generally available at wafer scale [2]. In addition, high growth temperature for high quality of 2D materials complicates direct wafer growth and makes transfer process desirable. At the device level, challenges are linked to controlled and uniform growth of 2D material for high density electronic structure.Recently, discreet 2D based memristor have been used in crossbar structure as synapse for neuromorphic computing. However, the plasma-assisted chemical vapor reaction (PACVR) based memristor for neuromorphic application are rarely demonstrated. Here, we report the co-integration of plasma-assisted chemical vapor reaction (PACVR) with silicon CMOS technology to provide brain-inspired computing device. PACVR offers compatibility with temperature limited 3D integration process and also provides much better thickness control over a large area. Furthermore, it an easy platform for direct and controlled synthesis of TMDs compared to conventional CVD approach. The PACVR grown WSe2 layer (~2 nm) on silicon substrate is realized, which exhibits both threshold and bipolar switching. The threshold and bipolar switching emulate integrate-fire neuron function and is obtained by modulating the compliance current in the device. The dynamics of the switching is closely related to the diffusive dynamics of the active metal (Ag or Cu) which can be controlled by device current. As a result, the WSe2/Si memristor shows synaptic behavior for neuromorphic system with learning accuracy of 96%.

Versatile GeS-based CBRAM with compliance-current-controlled threshold and bipolar resistive switching for electronic synapses

Chalcogenide materials have promising physical and electrical characteristics for use in advanced memory and electronic synaptic devices. However, limited research has been conducted on chalcogenide materials for highly advanced and scalable memory devices. In this study, we investigate compliance current (CC)-controlled resistive switching (RS) in a monochalcogenide GeS-based conductive bridge random access memory (CBRAM) device for use in advanced memory and electronic synapses. A CBRAM device with a structure stacking sequence of Ag/GeS/Pt/Ti/SiO2 is fabricated by depositing a 13 nm GeS layer using a sputtering process. The GeS-based CBRAM device exhibits the reversible CC-controlled transition between threshold resistive switching (T-RS) and bipolar resistive switching (B-RS). Under a high CC (1 mA and above), the device exhibits B-RS behavior with excellent retention and highly reproducible endurance characteristics, illustrated by a very high ION/IOFF ratio of almost ∼2 × 108. Under a low CC (100 µA and below), the device exhibits T-RS, with the automatic transition from a low resistance state (LRS) to a high resistance state (HRS) when sweeping the voltage in the reverse direction. Under all CC conditions, the device has a very low HRS current of around ∼1 × 10−12 A. A model based on the formation and rupture of conductive filaments (CFs) is proposed to explain the coexistence of T-RS and B-RS in GeS-based CBRAM devices. In particular, the change in the size and geometry of the CFs in accordance with the applied CC is speculated to be the main reason for the coexistence of T-RS and B-RS. The retention characteristics of the device in both T-RS and B-RS mode are investigated for possible application to case-sensitive hardware-based data security and the disposal of trusted and untrusted information. The ability of the CBRAM device in T-RS mode to perform important biological synaptic functions for potential use in brain-inspired neuromorphic systems is also investigated.

Water-soluble polyethylene-oxide polymer based memristive devices

In this research work, Conductive bridge Random Access memory devices (CBRAMs) featuring a water-solution processed Polyethylene Oxide (PEO) layer used as solid polymer electrolyte were fabricated. The devices showed promising results with forming-free capabilities, switching voltages within the range from −1.5 V to 2.0 V, high OFF/ON resistance ratio ~ 105 and > 300 cycles each at 10 & 100 μA compliance current (CC). Cycling at various CC also confirmed that the conductive filament was more stable at higher compliance current with a higher probability to achieve non-volatile switching. This article also reports the conduction mechanism in the high and low resistance states for PEO based devices. Finally, due to their high OFF/ON current ratio, it is suggested that these devices could also serve as BEOL (Back-End-Of-Line) selector devices while operating in their volatile mode.

Conductive Bridge Random Access Memory (CBRAM): Challenges and Opportunities for Memory and Neuromorphic Computing Applications.

Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based storage devices and computing systems are approaching their scaling and technical limits, extensive research on emerging technologies is becoming more and more important. Among other emerging technologies, CBRAM offers excellent opportunities for future memory and neuromorphic computing applications. The principles of the CBRAM are explored in depth in this review, including the materials and issues associated with various materials, as well as the basic switching mechanisms. Furthermore, the opportunities that CBRAMs provide for memory and brain-inspired neuromorphic computing applications, as well as the challenges that CBRAMs confront in those applications, are thoroughly discussed. The emulation of biological synapses and neurons using CBRAM devices fabricated with various switching materials and device engineering and material innovation approaches are examined in depth.