Electrochemical Metallization Cells Research Articles

Ultra-Low-Power Hybrid Synaptic Memristor via Simultaneous-Controlled Mechanism of Cations and Anions for Hyper-Scale Synaptic Cores

Recently, memristive devices such as phase change random access memory (PCRAM), resistive random access memory (ReRAM), and ferroelectric random access memory (FeRAM) have been actively researched to implement hyper-scale synaptic cores of various ANNs, i.e., deep neural networks (DNNs), spiking neural networks (SNNs), convolutional neural networks (CNNs), and binarized neural networks (BNNs). In particular, ReRAM is currently being highlighted as an artificial synaptic device because of its multilevel capability (> 11 bits)1, high switching speed (< 100 ps)2, high endurance (> 1012 cycles)3, high scalability, and complementary metal-oxide-semiconductor (CMOS) compatibility4. ReRAM is generally divided into two types: valence change memory (VCM) cells having oxygen vacancy filaments and electrochemical metallization (ECM) cells having conductive metal filaments. VCM cells have great retention but exhibit high switching current (~ 100 μA). In contrast, ECM cells exhibit relatively lower switching current (~10 uA) than VCM cells but have poor retention due to diffusion phenomena at high external temperatures5. Due to their high switching current and poor reliability, VCM and ECM cells have limitations in their application as synaptic devices in next-generation neuromorphic systems for energy consumption similar to that of the human brain (~20 W). In this study, for the first time, we developed a Ru-based ultra-low-power (< 1μA) hybrid synaptic memristor having a simultaneous-controlled mechanism of Ru cations and oxygen anions in a resistive switching layer. To elucidate the simultaneous-controlled mechanism of Ru cations and oxygen anions, we fabricated the VCM, ECM, and Ru-based hybrid memristor and performed x-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis depending on the resistance states (i.e., pristine, set, and reset). In addition, the mobility of mobile species in VCM, ECM, and Ru-based hybrid memristors was calculated indirectly via electrical properties (switching speed, operating voltage) and ToF-SIMS depth profiles, revealing the mechanism by which Ru-based hybrid memristor has low switching currents (< 1μA). Finally, the power consumption of active synaptic cores in the training and inference process of the designed DNN was evaluated for VCM, ECM, and Ru-based hybrid memristor. The simultaneous-controlled mechanism of Ru cations and oxygen anions of the Ru-based hybrid memristor and its application to DNN will be presented in detail. Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00260527) and Institute of Information & communications Technology Planning & Evaluation (IITP) under the artificial intelligence semiconductor support program to nurture the best talents (IITP-(2023)-RS-2023-00253914) grant funded by the Korea government(MSIT)". References Rao, M. et al. Thousands of conductance levels in memristors integrated on CMOS. Nature 615, 823–829 (2023).Yu, S., Wu, Y., Jeyasingh, R., Kuzum, D. & Wong, H. S. P. An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation. IEEE Trans. Electron Devices 58, 2729–2737 (2011).Lee, H. Y. et al. Evidence and solution of over-RESET problem for HfOX based resistive memory with sub-ns switching speed and high endurance. Tech. Dig. - Int. Electron Devices Meet. IEDM 7–10 (2010) doi:10.1109/IEDM.2010.5703395.Wong, H. S. P. et al. Metal-oxide RRAM. Proc. IEEE 100, 1951–1970 (2012).Yoon, J. H. et al. A Low-Current and Analog Memristor with Ru as Mobile Species. Adv. Mater. 32, 1–9 (2020). Figure 1

Probabilistic model of resistance jumps in memristive devices.

Resistance switching memory cells such as electrochemical metallization cells and valence change mechanism cells have the potential to revolutionize information processing and storage. However, the creation of deterministic resistance switching devices is a challenging problem that is still open. At present, the modeling of resistance switching cells is dominantly based on deterministic models that fail to capture the cycle-to-cycle variability intrinsic to these devices. Herewith we introduce a state probability distribution function and associated integrodifferential equationto describe the switching process consisting of a set of stochastic jumps. Numerical and analytical solutions of the equationhave been found in two model cases. This work expands the toolbox of models available for resistance switching cells and related devices and enables a rigorous description of intrinsic physical behavior not available in other models.

Simulating the filament morphology in electrochemical metallization cells

Electrochemical metallization (ECM) cells are based on the principle of voltage controlled formation or dissolution of a nanometer-thin metallic conductive filament (CF) between two electrodes separated by an insulating material, e.g. an oxide. The lifetime of the CF depends on factors such as materials and biasing. Depending on the lifetime of the CF—from microseconds to years—ECM cells show promising properties for use in neuromorphic circuits, for in-memory computing, or as selectors and memory cells in storage applications. For enabling those technologies with ECM cells, the lifetime of the CF has to be controlled. As various authors connect the lifetime with the morphology of the CF, the key parameters for CF formation have to be identified. In this work, we present a 2D axisymmetric physical continuum model that describes the kinetics of volatile and non-volatile ECM cells, as well as the morphology of the CF. It is shown that the morphology depends on both the amplitude of the applied voltage signal and CF-growth induced mechanical stress within the oxide layer. The model is validated with previously published kinetic measurements of non-volatile Ag/SiO2/Pt and volatile Ag/HfO2/Pt cells and the simulated CF morphologies are consistent with previous experimental CF observations.

Computational Study on Filament Growth Dynamics in Microstructure-Controlled Storage Media of Resistive Switching Memories.

The filament growth processes, crucial to the performance of nanodevices like resistive switching memories, have been widely investigated to realize the device optimization. With the combination of kinetic Monte Carlo (KMC) simulations and the restrictive percolation model, three different growth modes in electrochemical metallization (ECM) cells were dynamically reproduced, and an important parameter, the relative nucleation distance, was theoretically defined to measure different growth modes quantitatively; hence their transition can be well described. In our KMC simulations, the inhomogeneity of storage medium is realized through introducing evolutionary void versus non-void sites within it to mimic the real nucleation during filament growth. Finally, the renormalization group method was used in the percolation model to analytically illustrate void-concentration-dependent growth mode transition, fitting KMC simulation results quite well. Our study found that the nanostructure of the medium can dominate the filament growth dynamics, as the simulation images as well as the analytical results are consistent with experiments results. Our study spotlights a vital and intrinsic factor, void concentration (relative to defects, grains, or nanopores) of a storage medium, in inducing filament growth mode transition within ECM cells. This theoretically proves a mechanism to tune performance of ECM systems that controlling microstructures of the storage media can dominate the filament growth dynamics, indicating an accessible strategy, nanostructure processing, for device optimization of ECM memristors.

Annealing induced cation diffusion in TaOx-based memristor and its compatibility for back-end-of-line post-processing

The effect of annealing on the switching characteristics of memristor devices cannot be overlooked because the thermal process can exhibit both positive and negative effects on the performance of the devices. We investigated the switching behavior of TaOx-based memristors (electrochemical metallization cell type, ECM) that were Ar-ambient annealed under two conditions, with and without the active electrode. We found a high concentration of metal species in the TaOx films, even in the device where the TaOx was annealed without the active top electrode. This indicates that the properties of the annealed films encourage the diffusion of metal species in the oxide. We suggest that the increase in non-lattice oxygen (by 4.1%, indicating a higher concentration of Vo defects) after the annealing process plays a role in this phenomenon. In addition, the concentration of metal species that exist prior to the switching activation as well as the structure of the conducting bridge determines the switching stability of the devices. The device that annealed before top electrode deposition shows the worst stability; conversely, the device that annealed after top electrode deposition has the best coefficient of variation of the LRS and HRS which is 4.69% and 78.8%, respectively. Electrical and materials analyses were conducted to understand this phenomenon. This study provides insight into the compatibility of ECM in CMOS post-processing.

(Digital Presentation) Electrochemical Metallization Cell Based Memristive Neuron Chip Fabricated with 28nm CMOS Process for Real-Time Unsupervised Learning and Pattern Recognition

Spiking neurons communicate with other neurons using sparse and binary signals in a human brain, so they can achieve real-time processing of the information with ultra-low power consumption[1,2]. Thereby, spiking neurons are essential elements for building an energy-efficient biomimetic spatiotemporal system. Recently, to emulate the behavior of biological neuron, many researches for memristive device-based neurons with peripheral circuits (i.e., sense-amplifier or reset circuit)[3] and complementary metal-oxide-semiconductor (CMOS) neurons with capacitors have been reported[4]. Most of the reported memristive device-based neurons required a high operation voltage (>1.2 V) for emulating integrate function of a biological neuron. In addition, complementary metal-oxide-semiconductor-based neurons could not achieve high neuronal density due to using a capacitor in emulating integrate function.In this study, therefore, we propose an electrochemical metallization cell based memristive neuron chip fabricated with 28-nm CMOS process having a low operation voltage (<0.7 V) for emulating integrate function. In addition, since the proposed electrochemical metallization cell based memristive neuron chip does not require a capacitor for emulating integrate function, it can realize a high neuronal density. The memristive neuron chip exhibited a typical integrate-and-fire function; particularly, the frequency of generating a spiking output signal exponentially increased with the input voltage amplitude. Moreover, a spiking neural network was designed using the memristive neuron chip and the software program consisting of a crossbar synaptic memristor array, simplified spike-timing-dependent-plasticity learning rule, and current-to-voltage converters. Using the co-designed spiking neural network with software and hardware, real-time unsupervised learning was realized. Finally, using the trained spiking neural network, a real-time classification for the MNIST hand-written image taken by a live webcam was successfully performed in an inference process. Acknowledgement This research was supported by National R&D Program through the National Research Foundation of Korea(NRF) funded by Ministry of Science and ICT(2021M3F3A2A01037733). Reference Mead, C. Neuromorphic Electronic Systems. Encycl. Comput. Neurosci. 78, 1979–1979 (2015).Douglas, R. Neuromorphic Analogue VLSI. Annu. Rev. Neurosci. 18, 255–281 (1995).Tuma, T., Pantazi, A., Le Gallo, M., Sebastian, A. & Eleftheriou, E. Stochastic phase-change neurons. Nat. Nanotechnol. 11, 693–699 (2016).Aamir, S. A., Müller, P., Hartel, A., Schemmel, J. & Meier, K. A highly tunable 65-nm CMOS LIF neuron for a large scale neuromorphic system. Eur. Solid-State Circuits Conf. 2016-Octob, 71–74 (2016). Figure 1

Anodic oxidation effects at the copper/silicon oxide interface

We report on anodic oxidation effects in memristively switching Cu/SiO2/Pt and Cu/CuOx/SiO2/Pt Electrochemical Metallization Cells. In-depth x-ray photoelectron spectroscopy reveals the formation of a Cu-ion reservoir composed of Cu(OH)2 underneath the anode during oxidation. By using cyclic voltammetry partial redox reactions are observed both in SiO2- and CuOx/SiO2-based devices. From our analysis we conclude that the CuOx layer acts as a reservoir for Cu-ions, similar to the low work-function electrode in valance change mechanism devices, which acts a reservoir for oxygen vacancies. Integration of a CuOx layer may thus allow to tailor the resistive switching performance of cation based memristors.

Impact of Zr top electrode on tantalum oxide-based electrochemical metallization resistive switching memory: towards synaptic functionalities.

Electrochemical metallization memory (ECM) devices have been made by sub-stoichiometric deposition of a tantalum oxide switching film (Ta2O5−x) using sputtering. We investigated the influence of zirconium as the active top electrode material in the lithographically fabricated ECM devices. A simple capacitor like (Pt/Zr/Ta2O5−x/Pt) structure represented the resistive switching memory. A cyclic voltammetry measurement demonstrated the electrochemical process of the memory device. The I–V characteristics of ECMs show stable bipolar resistive switching properties with reliable endurance and retention. The resistive switching mechanism results from the formation and rupture of a conductive filament characteristic of ECM. Our results suggest that Zr can be considered a potential active electrode in the ECMs for the next generation of nonvolatile nanoelectronics. We successfully showed that the ECM device can work under AC pulses to emulate the essential characteristics of an artificial synapse by further improvements.

Self-assembling crystalline peptide microrod for neuromorphic function implementation

Self-assembling crystalline peptide microrod for neuromorphic function implementation

Electric Field-Induced Metal-Insulator Phase Separation in Lithium Titanates: Tuning Symmetry By Lithiation

Specialized hardware for neural networks requires materials with tunable symmetry, retention and speed at low power consumption. The vast majority of memristor are based on two types of ions: either oxygen vacancy migration, in the so-called Valence Change Memories (VCM), or a metal cation, usually Ag+ and Cu2+, in the so-called Electrochemical Metallization Cells (ECM). Despite their excellent performance, their widespread implementation in today’s integrated circuits is delayed due to the need to address cycle-to-cycle and device-to-device variabilities while circumventing electroforming and asymmetry, which are inherent issues associated to the filamentary nature of the switching mechanism. Recently, Li-ion is emerging as an alternative, given the higher diffusivity of Li+ when compared to oxygen, and the ability of Li-oxides solid state conductors to accumulate and deplete lithium at the interfaces and bulk. We have recently proposed lithium titanates, originally developed as Li-ion battery anode materials, as promising candidates for memristive-based neuromorphic computing hardware[1]. In this presentation, we will discuss the non-volatile, non-filamentary bipolar resistive switching characteristics of lithium titanates compounds, Li4+3xTi5O12, as a function of the lithiation degree. We have employed a recently proposed strategy to overcome lithium loss during thin film deposition and finely control the final lithiation degree of the films[2] to create stoichiometrically lithiated Li4Ti5O12 spinel phase and a highly lithiated Li7Ti5O12 rock- salt phase memristive devices. By using ex- and in-operando spectroscopy to monitor the Lithium filling and emptying of structural positions during electrochemical measurements, we investigate the controlled formation of a metallic phase (Li7Ti5O12) percolating through an insulating medium (Li4Ti5O12) with no volume changes under voltage bias, thereby controlling the spatially averaged conductivity of the film device. We present a theoretical model to explain the observed hysteretic switching behavior based on electrochemical nonequilibrium thermodynamics, in which the metal-insulator transition results from electrically driven phase separation of Li4Ti5O12 and Li7Ti5O12. Permittivity enhancement drives lithium ions to regions of high electric field intensity, which become metallic filaments above a critical applied bias, and the ions relax back to their low-conductivity initial state at lower voltages. One of the most striking outcomes is that the metal-insulator transition of llithium titanate can be uniquely modulated for neuromorphic computing purposes, such as control of the neural pulse train symmetry in conductance and the resistance on-to-off ratio, simply by adjusting the lithium stoichiometry and phase pattern of the films. We report ability of highly lithiated phase of Li7Ti5O12 for Deep Neural Network applications, given the large retentions and symmetry, and opportunity for the low lithiated phase of Li4Ti5O12 towards Spiking Neural Network applications, due to the shorter retention and large resistance changes. Our findings pave the way for lithium oxides to enable thin-film memristive devices with adjustable symmetry and retention.

An Experimental Proof that Resistance‐Switching Memory Cells are not Memristors

AbstractIt has been suggested that all resistive‐switching memory cells are memristors. The latter are hypothetical, ideal devices whose resistance, as originally formulated, depends only on the net charge that traverses them. Recently, an unambiguous test has been proposed to determine whether a given physical system is indeed a memristor or not. Here, such a test is experimentally applied to both in‐house fabricated Cu‐SiO2 and commercially available electrochemical metallization cells. The results unambiguously show that electrochemical metallization memory cells are not memristors. Since the particular resistance‐switching memories employed in the study share similar features with many other memory cells, the findings refute the claim that all resistance‐switching memories are memristors. They also cast doubts on the existence of ideal memristors as actual physical devices that can be fabricated experimentally. The results then lead to formulate two memristor impossibility conjectures regarding the impossibility of building a model of physical resistance‐switching memories based on the memristor model.

Conductive filament shape in HfO2 electrochemical metallization cells under a range of forming voltages

The development of neuromorphic computing architectures based on two terminal filamentary resistance switching devices is limited in part by the high degree of variability in resistance states and switching voltages. Because of the large role filament shape plays in directing thermal and electric fields around the filament (and thus switching parameters), unambiguous knowledge of filament morphology resulting from direct characterization of filament shape is essential to solve critical ongoing challenges of device switching variability. Here, we have utilized a conductive atomic force microscopy scalpel technique to simultaneously scribe through a polycrystalline dielectric layer in formed Cu/HfO2/p+Si electrochemical metallization cell devices. Filament tomograms reveal that when conductive filaments are formed at typical bias conditions (4 V, 100 μA), a variety of filament shapes result, which deviate from the inverse conical shape predicted by the phenomenological electrochemical model. Furthermore, the observation of an increasing spectrum of damage which scales with forming voltage (associated with compliance current overshoot), and which is uncorrelated with electric field or oxide microstructure, supports the role of thermal pulses in expanding filaments, leading to irreversible dielectric breakdown structures at the extreme. Overall, these findings suggest that the original conductive filament shape can be highly varied as a result of thermally driven expansion from joule heating during the forming step, which is not explicitly accounted for in the widely accepted electrochemical model.

(Invited) Electron Beam Induced Current Microscopy of Interfacial Barrier Effects in Al2O3/TiOx Resistive Switches

Resistive switching devices (ReRAM) represent a broad class of two-terminal continuously tunable resistors including memristors, phase change memory (PCM), valence change memory (VCM), and electrochemical metallization cells (ECM). Though these devices, especially PCM, are increasingly being commercialized by industry for use in next generation memories, they are also all actively studied for use as synaptic weights in next generation hardware-accelerated neuromorphic networks. We have previously investigated Electron Beam Induced Current Microscopy as a means of reliably characterizing resistive switches. In that investigation, we observed surprising electronic effects, such as internal secondary electron emission, in addition to more traditional electron-hole pair separation, and we broke those up into constituent currents based on their origin through Monte-Carlo modeling of the electron beam-matter interaction. Now, armed with a new understanding of the physics of EBIC imaging, we study the impact of manufacturing variations on resistive switches by continuously tuning the thickness of an Al2O3 interfacial barrier. Shifts in the apparent ratios of internal secondary electron emission from the top electrode to the bottom electrode and vice versa appear to indicate a continuous tuning of the apparent filament diameter as both a function of the injected current and the interfacial barrier thickness. This yields an apparent reduction in the current density, the primary effect of which is a reduction in the device damage from forming and a suppression of parasitic leakage currents imaged in devices without interfacial barriers. Figure 1

Switching an Analogue to Digital Computing Property Based on Memristance By Lithiation – Opportunities on Lithium Titanates

Electrochemical devices allowing to modulate their resistive state through ionic motion upon electric bias are known as memristors. Currently, memristors are positioned as a major candidate to overcome the bottlenecks in current electronic-based transistors in terms of downscaling capabilities and energy consumption. The vast majority of memristor are based on two types of ions: either oxygen vacancy migration, in the so called Valence Change Memories (VCM), or a metal cation, usually Ag+ and Cu2+, in the so called Electrochemical Metallization Cells (ECM). Despite the excellent performance of both systems, a widespread implementation of oxygen-based memristors in today’s integrated circuits is delayed due to the need to address cycle-to-cycle and device-to-device variabilities while circumventing electroforming, which are inherent issues associated to the filamentary nature of the switching mechanism. Recently, Li-ion is emerging as an alternative, given the higher diffusivity of Li+ when compared to oxygen, and the ability of Li-oxides solid state conductors to accumulate and deplete lithium at the interfaces and bulk. The scarce literature regarding Li-based memristors focuses mainly in a traditional high-voltage cathode material, LixCoO2 2, in a rather slow lithium conductor as LiLaTiO3 3 and in a magnetic spinel LiFe5O8 4. Performance-wise, Li-based oxides have shown promising applications in neuromorphic computing thanks to a close-to-analog switching response. However, it is still remains unclear the defect chemistry leading to the switching behavior of Li-based materials and the impact of lithiation degree on their performance. Among the potential Li-based oxides showing resistive switching effects, Lithium titanates compounds present intrinsic properties that could be beneficial to implement a Li- based memristor: a) the existence of a metal-insulator transition upon lithium intercalation, concomitant with a phase transition and valence change in the Ti cation, b) the spinel to rock-salt phase transition occurs with a neglectable volume change and c) there is a large difference in electronic conductivity and diffusivity between the two phases. In this work, we exemplify the resistive switching capabilities of these systems for different lithium stoichiometries. To exemplify this, we will report for the first time the non-volatile, non-filamentary bipolar resistive switching characteristics of lithium titanates compounds, Li4+3xTi5O12, as a function of the lithiation degree. We have employed a recently proposed strategy to overcome lithium loss during thin film deposition and finely control the final lithiation degree of the films5 to create a stoichiometrically lithiated Li4Ti5O12 spinel phase and a highly lithiated Li7Ti5O12 rock- salt phase memristive devices. Changing the Li-content from a stoichiometrically lithiated spinel phase to a highly lithiated rock-salt phase results in the capability to tune the performance in a wide range in terms of accessible resistance window (from ratios of 102 to 106 at low voltage operation, respectively), symmetry (from highly asymmetric to symmetric behavior, respectively) and retention (from few minutes up to 105 s at room temperature, respectively), among others. In other words, controlling the lithiation degree might offer a suitable path to reduce stochasticity from which current filamentary memristive devices inherently suffer, mainly due to the difficulties to control the amount of vacancies generated, and paves the way to further control of ionic migration for novel nanoelectronic devices.

Ge2Sb2Te5 nanobelts by femtosecond laser direct writing for resistive switching devices

Abstract One-dimensional Ge2Sb2Te5 (GST) nanobelts crystallized by femtosecond laser writing are used as the electrolyte material in electrochemical metallization cells. The width and roughness of the nanobelts are found to be strongly dependent on the laser fluence. The electrical transport properties of the crystalline GST nanobelts are comprehensively studied. First, the face-centered cubic (fcc) phase dominated crystalline GST nanobelt is demonstrated by the temperature dependence of resistivity results. Second, the decrease of conductance activation energy from 0.41 eV to 0.056 eV reveals a dramatic reduction of the trap potential of GST from amorphous to fcc phase. Finally, the resistive switching based on the electrochemical metallization is obtained in the one-dimension GST nanobelt with the ON/OFF ratio up to ∼7000, which is hundreds of times higher than that in typical crystalline GST films.

Ultra compact electrochemical metallization cells offering reproducible atomic scale memristive switching

Here we show electrochemical metallization cells with compact dimensions, excellent electrical performance, and reproducible characteristics. An advanced technology platform has been developed to obtain Ag/SiO2/Pt devices with ultra-scaled footprints (15 × 15 nm2), inter-electrode distances down to 1 nm, and a transition from the OFF to ON resistance state relying on the relocation of only few atoms. This technology permits a well-controlled metallic filament formation in a highly confined field at the apex of an atomic scale tip. As a consequence of this miniaturization process, we achieve set voltages around 100 mV, ultra-fast switching times of 7.5 ns, and write energies of 18 fJ. Furthermore, we demonstrate very good cell-to-cell uniformity and a resistance extinction ratio as high as 6 · 105. Combined ab-initio quantum transport simulations and experiments suggest that the manufactured structures exhibit reduced self-heating effects due to their lower dimensions, making them very promising candidates as next-generation (non-)volatile memory components.

Electrochemical metallization cell with anion supplying active electrode

Electrochemical metallization (ECM) memories are among the various emerging non-volatile memory technologies, contending to replace DRAM and Flash and enabling novel neuromorphic computing applications. Typically, the operation of ECM cell is based on the electrochemical redox reactions of the cation supplying active electrode (e.g., Ag, Cu). Although extensively investigated, the possibility of utilizing new materials for the active electrode remains largely undiscussed. In this paper, an ECM cell with a Te active electrode is fabricated. It is found that the SET operation of the device occurs under negative voltage on the active electrode, which is opposite to that of the device with Ag electrode, indicating that the Te electrode supplies Te2− anions by electrochemical reduction. The influence of the electrolyte material on the switching properties is also found to be more significant for devices with Te electrodes. For Pt/GeS/Te and Pt/Ge2Sb2Te5/Te cells, repeatable unipolar and bipolar resistive switching are observed, respectively, which can be attributed to the rupture of the filament by Joule heating for the former and by ECM for the latter in the RESET process. The semiconducting properties of Te, the reversed operating polarity and the electrolyte dependent switching characteristics open up unprecedented prospects for ECM cells.

Electrochemical metallization cell with solid phase tunable Ge2Sb2Te5 electrolyte

Electrochemical metallization (ECM) cell kinetics are strongly determined by the electrolyte and can hardly be altered after the cell has been fabricated. Solid-state property tunable electrolytes in response to external stimuli are therefore desirable to introduce additional operational degree of freedom to the ECM cells, enabling novel applications such as multistate memory and reconfigurable computation. In this work, we use Ge2Sb2Te5(GST) as the electrolyte material whose solid state is switched from the amorphous(a) to the crystalline(c) phase thermally. Electrical heating too is readily achievable. The resistive switching characteristics of the cells with different GST phases are examined. The magnitude of the high resistance, the SET voltage and the on/off ratio are found to be considerably affected by the solid phase of GST, whereas the magnitude of the low resistance is least affected. Moreover, a transition from volatile to nonvolatile SET switching is only observed for c-GST based cell under prolonged voltage sweep, but not for a-GST based cell. This work provides a springboard for more studies on the manipulation of the ECM cell kinetics by tunable electrolyte and the resulting unprecedented device functionalities.

High speed chalcogenide glass electrochemical metallization cells with various active metals

We fabricated electrochemical metallization cells using a GaLaSO solid electrolyte, an InSnO inactive electrode and active electrodes consisting of various metals (Cu, Ag, Fe, Cu, Mo, Al). Devices with Ag and Cu active metals showed consistent and repeatable resistive switching behaviour, and had a retention of 3 and >43 days, respectively; both had switching speeds of <5 ns. Devices with Cr and Fe active metals displayed incomplete or intermittent resistive switching, and devices with Mo and Al active electrodes displayed no resistive switching ability. Deeper penetration of the active metal into the GaLaSO layer resulted in greater resistive switching ability of the cell. The off-state resistivity was greater for more reactive active metals which may be due to a thicker intermediate layer.

Unidirectional threshold switching in Ag/Si-based electrochemical metallization cells for high-density bipolar RRAM applications

We herein present a novel unidirectional threshold selector for cross-point bipolar RRAM array. The proposed Ag/amorphous Si based threshold selector showed excellent threshold characteristics in positive field, such as high selectivity (~ 105), steep slope (< 5 mV/decade) and low off-state current (< 300 pA). Meanwhile, the selector exhibited rectifying characteristics in the high resistance state as well and the rectification ratio was as high as 103 at ± 1.5 V. Nevertheless, due to the high reverse current about 9 mA at − 3 V, this unidirectional threshold selector can be used as a selection element for bipolar-type RRAM. By integrating a bipolar RRAM device with the selector, experiments showed that the undesired sneak was significantly suppressed, indicating its potentiality for high-density integrated nonvolatile memory applications.