Conductive Filament Evolution Research Articles

Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging

The resistive switching effect in memristors typically stems from the formation and rupture of localized conductive filament paths, and HfO2 has been accepted as one of the most promising resistive switching materials. However, the dynamic changes in the resistive switching process, including the composition and structure of conductive filaments, and especially the evolution of conductive filament surroundings, remain controversial in HfO2-based memristors. Here, the conductive filament system in the amorphous HfO2-based memristors with various top electrodes is revealed to be with a quasi-core-shell structure consisting of metallic hexagonal-Hf6O and its crystalline surroundings (monoclinic or tetragonal HfOx). The phase of the HfOx shell varies with the oxygen reservation capability of the top electrode. According to extensive high-resolution transmission electron microscopy observations and ab initio calculations, the phase transition of the conductive filament shell between monoclinic and tetragonal HfO2 is proposed to depend on the comprehensive effects of Joule heat from the conductive filament current and the concentration of oxygen vacancies. The quasi-core-shell conductive filament system with an intrinsic barrier, which prohibits conductive filament oxidation, ensures the extreme scalability of resistive switching memristors. This study renovates the understanding of the conductive filament evolution in HfO2-based memristors and provides potential inspirations to improve oxide memristors for nonvolatile storage-class memory applications.

Two- and three-terminal HfO2-based multilevel resistive memories for neuromorphic analog synaptic elements

Synaptic elements based on memory devices play an important role in boosting neuromorphic system performance. Here, we show two types of fab-friendly HfO2 material-based resistive memories categorized by configuration and an operating principle for a suitable analog synaptic device aimed at inference and training of neural networks. Since the inference task is mainly related to the number of states from a recognition accuracy perspective, we first demonstrate multilevel cell (MLC) properties of compact two-terminal resistive random-access memory (RRAM). The resistance state can be finely subdivided into an MLC by precisely controlling the evolution of conductive filament constructed by the local movement of oxygen vacancies. Specifically, we investigate how the thickness of the HfO2-switching layer is related to an MLC, which is understood by performing physics-based modeling in MATLAB from a microscopic view. Meanwhile, synaptic devices driven by an interfacial switching mechanism instead of local filamentary dynamics are preferred for training accelerated neuromorphic systems, where the analogous transition of each state ensures high accuracy. Thus, we introduce three-terminal electrochemical random-access memory that facilitates mobile ions across the entire HfO2 switching area uniformly, resulting in highly controllable and gradually tuned current proportional to the amount of migrated ions.

Multi‐Level Control of Conductive Filament Evolution and Enhanced Resistance Controllability of the Cu‐Cone Structure Embedded Conductive Bridge Random Access Memory

AbstractMemristor is considered as one of the key components of neuromorphic hardware aiming to overcome the limitations of classical von Neumann computers, but the continuous control of the device conduction remains a challenge. Random and stochastic dynamics of weak conducting filaments (CF) hinder the precise control of the resistance states, particularly in the conductive bridge random access memory (CBRAM). The problem of random and stochastic resistive switching of the Cu‐based CBRAM is largely mitigated by inserting the Cu‐cone as a cation source into the memory cell (Cu‐cone device). The electric field concentrated on the Cu‐cone induces stronger CF with a limited number near the tip region, making the device feature distinctive from the planar Cu CBRAM. The Cu‐cone device exhibits enhanced resistance controllability attributed to the well‐controlled CF, improved switching reliability improvement, and multiple intermediate resistance states. Such features are used to explore its usefulness as an artificial synapse, where fluent potentiation and depression can be achieved using voltage pulses. Further research is still required to emulate the artificial synapses fully, but the feasibility is presented in this work by exploiting the similarities between the Cu cations in the CBRAM device and the Ca2+ dynamics in a biological synapse.

Conductive filament evolution dynamics revealed by cryogenic (1.5 K) multilevel switching of CMOS-compatible Al2O3/TiO2 resistive memories

Non-volatile resistive switching devices are considered as prime candidates for next-generation memory applications operating at room temperature and above, such as resistive random-access memories or brain-inspired in-memory computing. However, their operability in cryogenic conditions remains to be mastered to adopt these devices as building blocks enabling large-scale quantum technologies via quantum–classical electronics co-integration. This study demonstrates multilevel switching at 1.5 K of Al2O3/TiO2-x resistive memory devices fabricated with complementary metal-oxide-semiconducto-compatible processes and materials. The I–V characteristics exhibit a negative differential resistance (NDR) effect due to a Joule-heating-induced metal-insulator transition of the Ti4O7 conductive filament. Carrier transport analysis of all multilevel switching I–V curves show that while the insulating regime follows the space charge limited current (SCLC) model for all resistance states, the conduction in the metallic regime is dominated by SCLC and trap-assisted tunneling for low- and high-resistance states respectively. A non-monotonic conductance evolution is observed in the insulating regime, as opposed to the continuous and gradual conductance increase and decrease obtained in the metallic regime during the multilevel SET and RESET operations. Cryogenic transport analysis coupled to an analytical model accounting for the metal-insulator-transition-induced NDR effects and the resistance states of the device provide new insights on the conductive filament evolution dynamics and resistive switching mechanisms. Our findings suggest that the non-monotonic conductance evolution in the insulating regime is due to the combined effects of longitudinal and radial variations of the Ti4O7 conductive filament during the switching. This behavior results from the interplay between temperature- and field-dependent geometrical and physical characteristics of the filament.

Resistive switching in HfO2 based valence change memories, a comprehensive 3D kinetic Monte Carlo approach

A simulation study has been performed to analyze resistive switching (RS) phenomena in valence change memories (VCM) based on a HfO2 dielectric. The kernel of the simulation tool consists of a 3D kinetic Monte Carlo (kMC) algorithm implemented self-consistently with the 3D Poisson and heat equations. These VCM devices show filamentary conduction, their RS operation is based on the destruction and regeneration of an ohmic conductive filament (CF) composed of oxygen vacancies. The physics underlying the RS operation is described by means of processes linked to generation of oxygen vacancies, oxygen ion migration and recombination between vacancies and oxygen ions that can be accurately described by using the electric field and temperature distributions in the dielectric. The studied devices consist of TiN/Ti/HfO2/W stacks where the Ti capping layer plays the role of oxygen ion getter material. The simulation tool is useful for obtaining information of internal physical variables, explaining RS dynamics and the CFs evolution from the microscopic viewpoint in terms of their size and shape under different electrical input signals; particularly, the pulsed operation regime has been studied in depth. Furthermore, interesting phenomena, such as partial SETs within overall RESET processes can be accurately reproduced.

Controlled Construction of Atomic Point Contact with 16 Quantized Conductance States in Oxide Resistive Switching Memory

A resistive switching device with controlled formation and evolution of conductive filament possesses great capability of being miniaturized to atomic scale for the construction of high-density mem...

Amorphous‐Si‐Based Resistive Switching Memories with Highly Reduced Electroforming Voltage and Enlarged Memory Window

Amorphous Si (a‐Si) based memory devices that offer significant improvement in switching performance are fabricated by inserting a gold nanoparticles (Au NPs) monolayer between the amorphous Si and inert bottom electrodes. It is demonstrated that the Au NPs‐interlayer amorphous Si memory devices deliver great improvements in lowering the electroforming voltage as well as enhancing the ON/OFF ratio, as compared to a pure amorphous Si memory structure. The switching mechanism is due to the modified electric field distribution with the insertion of Au NPs, which can directly affect the dynamic transport of ions and lead to the change of filament growth. Transmission electron microscopy (TEM) is used to directly capture the filaments growth process in these two types of memory devices to verify the evolution of conductive filament (CF). In addition, it is also demonstrated that the Au NPs‐interlay amorphous Si memory fabricated on a flexible substrate can maintain low electroforming voltage and high ON/OFF ratio. This fabrication approach offers a versatile structural platform for next‐generation memory applications with enhancement of the switching properties.

Conductive filament evolution in HfO2 resistive RAM device during constant voltage stress

The resistance evolution under constant voltage stress of the low resistive state and the high resistive state of HfO2 based RRAM cells is studied from an experimental and theoretical point of view. A filamentary model based on ions hopping and oxygen vacancies generation phenomena is used to interpret the behavior of the cells. The gap between the tip of the filament and the metal electrode is the parameter governing the device resistance. The current experiments are simulated in terms of the time evolution of the gap length during the electrical stress. The impact of the stress voltage amplitude and the parameter variability on the degradation dynamics is emphasized.

Evolution of conductive filament and its impact on reliability issues in oxide-electrolyte based resistive random access memory.

The electrochemical metallization cell, also referred to as conductive bridge random access memory, is considered to be a promising candidate or complementary component to the traditional charge based memory. As such, it is receiving additional focus to accelerate the commercialization process. To create a successful mass product, reliability issues must first be rigorously solved. In-depth understanding of the failure behavior of the ECM is essential for performance optimization. Here, we reveal the degradation of high resistance state behaves as the majority cases of the endurance failure of the HfO2 electrolyte based ECM cell. High resolution transmission electron microscopy was used to characterize the change in filament nature after repetitive switching cycles. The result showed that Cu accumulation inside the filament played a dominant role in switching failure, which was further supported by measuring the retention of cycle dependent high resistance state and low resistance state. The clarified physical picture of filament evolution provides a basic understanding of the mechanisms of endurance and retention failure, and the relationship between them. Based on these results, applicable approaches for performance optimization can be implicatively developed, ranging from material tailoring to structure engineering and algorithm design.

A SPICE Model of Resistive Random Access Memory for Large-Scale Memory Array Simulation

A SPICE model of oxide-based resistive random access memory (RRAM) for dc and transient behaviors is developed based on the conductive filament evolution model and is implemented in large-scale array simulation. The simulations of one transistor-one resistor RRAM array up to 16 kb with wire resistance (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wire</sub> ) and capacitance (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wire</sub> ) indicate that: 1) resistance-capacitance delay during RESET and leakage current during SET have significant impact on write operations; 2) with array size enlarging, the power dissipation increases during RESET but decreases during SET; and 3) the increased R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wire</sub> and C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wire</sub> lead to the degradation of high resistance state and the fluctuation of low resistance state, respectively.

A Physics-Based Compact Model of Metal-Oxide-Based RRAM DC and AC Operations

A physics-based compact model of metal-oxide-based resistive-switching random access memory (RRAM) cell under dc and ac operation modes is presented. In this model, the conductive filament evolution corresponding to the resistive switching process is modeled by considering the transport behaviors of oxygen vacancies and oxygen ions together with the temperature effect. Both the metallic-like and electron hopping conduction transports are considered to model the conduction of RRAM. The model can reproduce both the typical I-V characteristics of RRAM in high-/low-resistance state (LRS) and the nonlinear characteristics in LRS. Moreover, to accurately model ac operation mode, the effects of parasitic capacitance and resistance are included in our model. The developed compact model is verified and calibrated by measured data in different HfOx-based RRAM devices under dc and ac operation modes. The excellent agreement between the model predictions and experimental results shows a promising prospect of the future implementation of this compact model in large-scale circuit simulation to optimize the design of RRAM.

Optimization of Conductive Filament of Oxide-Based Resistive-Switching Random Access Memory for Low Operation Current by Stochastic Simulation

Large switching current is a great challenge for scaling down of the oxide-based resistive random access memory devices to realize high density and low power memory array. In this paper, large operation current caused by the current overshoot effect during forming process is investigated using a stochastic simulator based on the percolation theory. The electrical characteristic of forming process is simulated and compared with the experimental data. Our simulation demonstrates that the current overshoot effect results in a stronger conductive filament during forming process, which will cause a larger operation current in subsequent switching cycle. Furthermore, our simulation results reveal that low sweeping rate, high ambient temperature, high doping concentration and high pre-exist oxygen vacancies (VO) concentration are beneficial to the control of conductive filament evolution and the suppression of the current overshoot effect, which is critical for low reset current and low operation power resistive-switching random access memory (RRAM).