Resistive Switching Random Access Memory Devices Research Articles

Comparative analysis of low-frequency noise based resistive switching phenomenon for filamentary and interfacial RRAM devices

We investigate the low-frequency noise (LFN) characteristics of resistive switching random access memory (RRAM) devices with metal–insulator–metal structures of TiN/Ti/TiO2/TiN (filamentary) and TiN/Ti/TiO2/HfO2/TiN (interfacial). By comparing filamentary and interfacial RRAM devices, we stipulate guidelines for noise sources according to the resistance states or resistive switching mechanisms of RRAM device. In filamentary RRAM devices, the dominant noise source in the low resistance state is the localized oxygen vacancies, whereas the noise characteristics in the high resistance state represent a bulk effect. In interfacial RRAM devices, the noise characteristics in both resistance states represent the bulk effect. The physical mechanism of the multilevel cell operation is inferred by the I–V characteristics in both Icc and Vreset control modes. Specifically, the changes in the structure of the conductive filament inside the switching layer can be confirmed through LFN measurement.

Low-Frequency Noise-Based Mechanism Analysis of Endurance Degradation in Al/αTiOx/Al Resistive Random Access Memory Devices.

In this work, we analyze a resistive switching random access memory (RRAM) device with the metal-insulator-metal structure of Al/αTiOx/Al. The transport mechanism of our RRAM device is trap-controlled space-charge limited conduction, which does not change during the endurance test. As the number of resistive switching (RS) cycles increases, the current in the low-resistance state (LRS) does not change significantly. In contrast, degradation in the high-resistance state (HRS) is noticeably evident. According to the RS cycle, the current shift fits well with the stretched-exponential equation. The normalized noise power spectral density (Si/I2) measured in the HRS is an order of magnitude higher than that in the LRS owing to the difference in the degree of trap occupancy, which is responsible for the transition of resistance states. During the consecutive RS, the Si/I2 in the HRS rapidly decreases for approximately 100 cycles and then saturates. In contrast, in the LRS, the Si/I2 does not change significantly. Here we propose a model associated with the endurance degradation of the experimental device, and the model is verified with a 1/f noise measurement.

Programming Strategy Optimization of RRAM Fabricated by 28 nm Standard CMOS Process

The switching characteristics of HfOx-based resistive switching random access memory (RRAM) fabricated on front-end of 28 nm standard CMOS process are investigated. The integration of RRAM in the front-end of the CMOS process would minimize the influence of parasitic parameters caused by interconnection line and interlayer oxide on the one transistor one RRAM (1T1R) cells. By adopting pulse program-verify measurement for cycling test, we observe two nonideal phenomena in the commercialized RRAM devices for the first time: 1) low resistance state (LRS) current periodically decays exponentially accompanied by incremental SET pulse number and then increases abruptly when the cycle reaches a certain level and 2) high resistance state (HRS) current fluctuated dramatically during RESET operation. The current fluctuation is mainly due to the generation of new oxygen vacancies (Vos) near the bottom electrode and gap region by electrons trapping/detrapping. By adopting efficient pulse amplitude modulation, the optimized programming strategy has greatly reduced the switching instability and improved the endurance of the devices. Mechanisms of the instability and the optimization strategy are explained by a modified trap-assisted tunneling (TAT) model based on the generation and redistribution of Vos during cycling operations.

An ab initio investigation of the structural, mechanical, electronic, optical, and thermoelectric characteristics of novel double perovskite halides Cs2CaSnX6 (X = Cl, Br, I) for optically influenced RRAM devices.

Hybrid lead halide perovskites have been considered as promising candidates for a large variety of optoelectronic applications. By exploring novel combinations of lead-free double perovskite halides, it is possible to find a suitable replacement for poisonous lead halide perovskites, enhancing electronic and optical response for their application as optically-influenced resistive switching random access memory (RRAM). In this work, the structural, mechanical, elastic, electronic, optical, and thermoelectric characteristics of lead-free double halide perovskites were investigated by Vienna ab initio simulation package (VASP) to explore their role in RRAM. From the analysis of mechanical constraints, it is clear that all three composites of Cs2CaSnX6 (X = Cl, Br, I) are mechanically stable and ductile in nature. The electronic bandgap with and without spin-orbit coupling (SOC), and total and sub-total density of states (TDOS, sub-TDOS) have been calculated using the Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA) potentials. The observed direct band gaps of 3.58 eV, 3.09 eV, and 2.60 eV for Cs2CaSnCl6, Cs2CaSnBr6, and Cs2CaSnI6, respectively, reveal the suitability of these specified composites as resistive switching material for RRAM devices. Additionally, the optical characteristics, such as complex refractive index, absorption coefficient, and reflectivity of the compounds under consideration have been calculated under the action of incident photons of 0 to 14 eV energy. The thermoelectric properties of Cs2CaSnX6 (X = Cl, Br, I) double perovskite halide were computed and analyzed with the help of the BoltzTraP Code.

Uniform, fast, and reliable CMOS compatible resistive switching memory

Resistive switching random access memory (RRAM) is considered as one of the potential candidates for next-generation memory. However, obtaining an RRAM device with comprehensively excellent performance, such as high retention and endurance, low variations, as well as CMOS compatibility, etc., is still an open question. In this work, we introduce an insert TaO x layer into HfO x -based RRAM to optimize the device performance. Attributing to robust filament formed in the TaO x layer by a forming operation, the local-field and thermal enhanced effect and interface modulation has been implemented simultaneously. Consequently, the RRAM device features large windows (> 103), fast switching speed (~ 10 ns), steady retention (> 72 h), high endurance (> 108 cycles), and excellent uniformity of both cycle-to-cycle and device-to-device. These results indicate that inserting the TaO x layer can significantly improve HfO x -based device performance, providing a constructive approach for the practical application of RRAM.

CMOS-compatible wafer-scale Si subulate array for superb switching uniformity of RRAM with localized nanofilaments

Resistive switching random access memory (RRAM) is one of the most promising candidates with high-density three-dimensional integration characteristics for next-generation nonvolatile memory technology. However, the poor uniformity issue caused by the stochastic property of the conductive filament (CF) impedes the large-scale manufacture of RRAM chips. Subulate array has been introduced into the RRAM to minimize the CF randomness, but the methods are cumbersome, expensive, or resolution-limited for large-scale preparation. In this work, Si subulate array (SSA) substrates with different curvature radii prepared by a wafer-scale and nanoscale-controllable method are introduced for RRAM fabrication. The SSA structure, which induces a quasi-single CF or a few CFs formed in the tip region (TR) of the device as evidenced by the high-resolution transmission electron microscopy and energy dispersive spectroscopy characterization, dramatically improves the cycle-to-cycle and device-to-device uniformity. Decreasing the curvature radius of the TR significantly improves the device performance, including switching voltages, high/low resistance states, and retention characteristics. The improved uniformity can be attributed to the enhanced local electric field in the TR. The proposed SSA provides a low-cost, uniform, CMOS-compatible, and nanoscale-controllable optimization strategy for the large-scale integration of highly uniform RRAM devices.

Combining Accuracy and Plasticity in Convolutional Neural Networks Based on Resistive Memory Arrays for Autonomous Learning

Nowadays, artificial neural networks (ANNs) can outperform the human brain’s ability in specific tasks. However, ANNs cannot replicate the efficient and low-power learning, adaptation, and consolidation typical of biological organisms. Here, we present a hardware design based on arrays of SiO x resistive switching random-access memory (RRAM), which allows combining the accuracy of convolutional neural networks with the flexibility of bio-inspired neuronal plasticity. In order to enable the combination of the stable and the plastic attributes of the network, we exploit the spike-frequency adaptation of the neurons relying on the multilevel programming of the RRAM devices. This procedure enhances the efficiency and accuracy of the network for MNIST, noisy MNIST (N-MNIST), Fashion-MNIST, and CIFAR-10 datasets, with inference accuracies of about 99%–89%, respectively. We also demonstrate that the hardware is capable of asynchronous self-adaptation of its operative frequency according to the fire rate of the spiking neuron, thus optimizing the whole behavior of the network. We finally show that the system enables fast and accurate filter retraining to overcome catastrophic forgetting, showing high efficiency in terms of operations per second and robustness against device non-idealities. This work paves the way for the theoretical modeling and hardware realization of resilient autonomous systems in dynamic environments.

Switching Dynamics of Ag-Based Filamentary Volatile Resistive Switching Devices—Part I: Experimental Characterization

Volatile resistive switching random access memory (RRAM) devices are drawing attention in both storage and computing applications due to their high ON-/ OFF-ratio, fast switching speed, low leakage, and scalability. However, these devices are relatively new and the physical switching mechanisms are still under investigation. A thorough understanding and modeling of the physical dynamics underlying filament formation and self-dissolution are of utmost importance in view of future integration of volatile devices in neuromorphic systems and in memory arrays. To assess the physical mechanisms and develop appropriate models, though, the electrical properties of the device have to be characterized. In this article, we present an extensive study of Ag/SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> -based volatile RRAM devices. Important parameters, such as switching time, switching voltage, and retention time are investigated as a function of the stimulation conditions. A physical explanation is provided and the applicability of the device in neuromorphic systems is discussed.

Electroforming-Free Bipolar Resistive Switching Memory Based on Magnesium Fluoride.

Electroforming-free resistive switching random access memory (RRAM) devices employing magnesium fluoride (MgFx) as the resistive switching layer are reported. The electroforming-free MgFx based RRAM devices exhibit bipolar SET/RESET operational characteristics with an on/off ratio higher than 102 and good data retention of >104 s. The resistive switching mechanism in the Ti/MgFx/Pt devices combines two processes as well as trap-controlled space charge limited conduction (SCLC), which is governed by pre-existing defects of fluoride vacancies in the bulk MgFx layer. In addition, filamentary switching mode at the interface between the MgFx and Ti layers is assisted by O–H group-related defects on the surface of the active layer.

Brain-inspired computing via memory device physics

In our brain, information is exchanged among neurons in the form of spikes where both the space (which neuron fires) and time (when the neuron fires) contain relevant information. Every neuron is connected to other neurons by synapses, which are continuously created, updated, and stimulated to enable information processing and learning. Realizing the brain-like neuron/synapse network in silicon would enable artificial autonomous agents capable of learning, adaptation, and interaction with the environment. Toward this aim, the conventional microelectronic technology, which is based on complementary metal–oxide–semiconductor transistors and the von Neumann computing architecture, does not provide the desired energy efficiency and scaling potential. A generation of emerging memory devices, including resistive switching random access memory (RRAM) also known as the memristor, can offer a wealth of physics-enabled processing capabilities, including multiplication, integration, potentiation, depression, and time-decaying stimulation, which are suitable to recreate some of the fundamental phenomena of the human brain in silico. This work provides an overview about the status and the most recent updates on brain-inspired neuromorphic computing devices. After introducing the RRAM device technologies, we discuss the main computing functionalities of the human brain, including neuron integration and fire, dendritic filtering, and short- and long-term synaptic plasticity. For each of these processing functions, we discuss their proposed implementation in terms of materials, device structure, and brain-like characteristics. The rich device physics, the nano-scale integration, the tolerance to stochastic variations, and the ability to process information in situ make the emerging memory devices a promising technology for future brain-like hardware intelligence.

Total ionizing dose effects of 60Co-γ ray radiation on the resistive switching and its bending performance of Al-in-O/InOx-based flexible RRAM device

Flexible resistive switching random access memory (RRAM) device is one of the promising candidates for non-volatile memory used in space because of its features such as simple structure, high speed, low power consumption, durability and lightweight with reduction in thickness. Al-In-O/InOx self-mixing layer can be applied for flexible RRAM due to its low annealing temperature (i.e. temperatures<180 °C), forming-free resistive switching characteristics and low SET and RESET voltage. Herein, effects of the total ionizing dose of 60Co-γ ray radiation on the resistive switching, the bending performance of the prepared flexible RRAM devices based on the Al-In-O/InOx films were studied. The results indicated that the resistance decreases with the bias in high resistance state (HRS) and the SET voltages of the device decrease very slightly after irradiation, while the low resistance state (LRS), RESET voltage, and retention parameters are almost immune to radiation. Moreover, after irradiation, the decrease of resistance with the bias in HRS becomes more exacerbated when bended. Mechanism of bending on the RS is studied by the first-principles calculation, and the mechanism underlying the irradiation effect is studied from the viewpoint of the origin of RS.

Progress of lead-free perovskite and its resistance switching performance

With the rapid development of the information age, the demand for information storage capacity and miniaturization of memory units has been being increased. However, the commonly used silicon-based flash memory has nearly approached to its physical limit. The resistive switching random access memory (ReRAM) has become one of the promising candidates for the next-generation non-volatile memory due to its simple structure, fast operation speed, excellent flexibility, and long endurance. Recently, we witnessed that the lead halide perovskites, as hot star materials, have been widely used in optoelectronic fields owning to their advantages of low cost, excellent photoelectric properties, and solution process ability. Moreover, the lead halide perovskite has been successfully used as the active layer in ReRAM device because of its tunable bandgap, long charge carrier diffusion length, fast ion migration, and high charge carrier mobility. Whereas the toxicity of lead in halide perovskite is a very horrible problem in lead halide perovskite-based ReRAM devices. The lead-free halide perovskite is considered to be the most promising material for perovskite-based ReRAM devices because it does not contain lead element. Most recently, a large number of scientists from different groups have begun to study lead-free perovskite-based ReRAM devices. For example, tin, bismuth, antimony, and copper-based halide perovskite materials have been utilized in ReRAM devices and exhibited excellent resistance switching (RS) performances. Here in this paper, the recent development of lead-free perovskite and its RS performance are reviewed, including lead-free halide perovskite materials, RS performances, and RS mechanisms of lead-free perovskite-based ReRAM. Finally, the key problems and development prospects of lead-free perovskite-based ReRAM are also presented, which provides a fundamental step towards developing the RS performance based on lead-free halide perovskites.

Investigation of the Thermal Recovery From Reset Breakdown of a SiN x -Based RRAM

In this article, we report a method for recovering a resistive-switching random access memory (RRAM) from the reset breakdown and enhancing the endurance characteristics. A SiNx-based RRAM device has been fabricated and its switching characteristics are analyzed with a particular interest in reset breakdown. It has been found that the SiNx RRAM in permanent reset breakdown can be revived to high-resistance state (HRS) by thermal recovery, a low-temperature annealing method. The memory window could be widened even with enhanced reset stability and conductance distribution. Temperature-dependent conductance change has been measured in order to figure out the substantial component of conductive filament and the mechanism of thermal recovery. The experimental evidences show that the reset breakdown process is the result of unwanted Si dangling bond (Si-DB) formation. By thermal recovery, Ni filament could be ruptured without applying a high electric field which induces negative set.

Rapid thermal annealing on the atomic layer-deposited zirconia thin film to enhance resistive switching characteristics

The resistive switching random access memory (RRAM) device has received a great interest for the next-generation non-volatile memory application, and resistive switching (RS) characteristics are mainly affected by conductive oxygen vacancies ([V··]) within switching material. Various effective approaches with materials, doping, and thermal treatments have been attempted to achieve the stable RS behaviors. Particularly, thermal annealing is considered as an efficient knob to control [V··] compared to other approaches. However, research on thermal treatment still lacks results and further research efforts are still needed to improve the RS characteristics of the devices. In this work we investigated the RS characteristics of Ti/ZrOx/Pt-structured RRAM device in comparison without and with postrapid thermal annealing (RTA) temperature range under oxygen ambient. The as-fabricated device with atomic layer-deposited ZrOx switching layer exhibited conducting characteristics, which is related to a relatively high amount of [V··] within switching medium. It indicates that moderate amount of [V··] apparently determines the appropriate RS behaviors. With this regard, we modulated the [V··] in ZrOx thin films by employing RTA in the ranges of 500 °C to 800 °C at the oxygen ambient for 60 s. Unlike device without RTA, we observed the stable RS characteristics from device with RTA and device annealed at 700 °C exhibits the excellent bipolar RS characteristics such as higher Ron/Roff, smaller cycle-to-cycle switching variation, better endurance, and longer retention among RTA conditions, indicating moderate amount of [V··] formed within ZrOx thin film layer. Moreover, increasing ALD ZrOx thickness shows the further improvement in the RS characteristics and RTA on the thicker ZrOx device still improves the RS behaviors. This research indicates that modulating [V··] by fast thermal annealing on the ALD zirconia material can provide the proper RS characteristics of the non-volatile memory applications.

Hardware implementation of RRAM based binarized neural networks

Resistive switching random access memory (RRAM) has been explored to accelerate the computation of neural networks. RRAM with linear conductance modulation is usually required for the efficient weight updating during the online training according to the back-propagation algorithm. However, most RRAM devices usually show the nonlinear characteristic. Here, to overcome the dilemma, we designed a novel weight updating principle for binarized neural networks, which enables the nonlinear RRAM to realize the weight updating in efficiency during online training. Moreover, a vector-matrix multiplication is designed to parallel calculate the dot-products of the forward and backward propagation. 1 kb nonlinear RRAM array is fabricated to demonstrate the feasibility of the analog accumulation and the parallel vector-matrix multiplication. The results achieved in this work offer new solutions for future energy efficient neural networks.

The observation of resistive switching characteristics using transparent and biocompatible Cu2+-doped salmon DNA composite thin film

For the potential switching bio-memory device application using DNA composite thin film, we fabricated and characterized the transparent and biocompatible resistive switching random access memory (RRAM) device within the structure stacking of Pt/Cu2+ doped salmon DNA/FTO, where Cu2+ doping into salmon DNA was solution-processed. The device shows good bipolar switching characteristics with SET and RESET processes at negative and positive sweeps, respectively, with switching memory window greater than 103 ratios. The device was observed to be in low resistance state as its pristine state and an initial RESET state was necessary to achieve programmable SET and RESET cycles. Based on the electrical characteristics of the Cu2+-doped salmon DNA-based RRAM device we propose a switching mechanism with the formation and rupture of conductive filaments due to the migration of Cu2+ during the electrical stress. Our understanding could contribute to the engineering of biomaterial memory switching medium for the environmentally benign, biocompatible and biodegradable memory storage devices.

Temperature-dependence of resistive switching behaviors and tunneling mechanism of (111) epitaxial NiO films on metal seed layer

Since 2000, resistive switching random access memory (ReRAM) based on binary metal oxide has become one of potential candidates for next generation of nonvolatile memory due to its simple structure, high writing/read speed (~5 ns), good endurance (~109 cycles), long retention time (~10 years) and low energy consumption (~ dozens of pJ). NiO has been extensively studied as one of promising materials applied for commercial ReRAMs. However, it exhibits diverse resistive switching (RS) behaviors that heavily dependent on fabrication technologies, methods and conditions. Up to now, RS performances and mechanisms of polycrystalline NiO films have been extensively investigated, while there are few discussions on RS performances of epitaxial NiO films, especially on metal seed layer. On the other hand, with the expanding scope of human activities, researches on stabilities of ReRAM devices under extreme environmental conditions are necessary. In this paper, temperature-dependence of RS behaviors and tunneling mechanism of epitaxial NiO(111) films on Pt seed layers have been discussed. A set of highly textured NiO(111) films on Pt seed layers were prepared by means of Radio Frequency magnetron sputtering. Their microstructural characteristics and temperature-dependence of RS performance were investigated. Microstructural investigation demonstrated the “cube-to-cube” lattice relationship of NiO(111)/Pt(001) interfaces. Under the applied electric field, the drift of oxygen ions in NiO film and the redox of Ag ions near upper electrodes result in the formation/rupture of oxygen-vacancy conductive filaments at a set/reset voltage lower than ± 1 V. Moreover, current-voltage ( I - V ) curves of Ag/NiO(111)/Pt memory cells exhibit stable bipolar switching behaviors in the temperature range from RT to 80°C. Moreover, their Arrhenius form (ln I vs. 1000/ T ) and Schottky tunneling (ln( I / T 2) vs. 1000/ T ) plots are the best linear fitting relationship. It reveals that the leakage current of Ag/NiO(111)/Pt memory cell on high resistance state can be explained by the Schottky tunneling mechanism.

Synaptic behaviors of HfO2 ReRAM by pulse frequency modulation

A resistive switching random-access memory (ReRAM) device with TiN/HfO2/SiO2/p+-Si stack is analyzed for synaptic behavior. Fabricated RRAM device stack consists of heavily doped p-type silicon bottom electrode (BE), HfO2 as a switching layer, SiO2 as a tunneling barrier layer and TiN as a top electrode (TE). The RRAM cell successfully shows I-V curves including SET and RESET operations in DC sweep mode. By inserting a SiO2 tunneling barrier layer, gradual switching characteristics are obtained by pulse operation. By optimizing the pulse scheme applied to the device, biological synaptic plasticity of long-term potentiation and depression is demonstrated. Finally, spike rate-dependent plasticity (SRDP) learning rule is realized by applying pulses with different frequencies to both terminals of the ReRAM device.

A System-Level Simulator for RRAM-Based Neuromorphic Computing Chips

Advances in non-volatile resistive switching random access memory (RRAM) have made it a promising memory technology with potential applications in low-power and embedded in-memory computing devices owing to a number of advantages such as low-energy consumption, low area cost and good scaling. There have been proposals to employ RRAM in architecting chips for neuromorphic computing and artificial neural networks where matrix-vector multiplication can be computed in the analog domain in a single timestep. However, it is challenging to employ RRAM devices in neuromorphic chips owing to the non-ideal behavior of RRAM. In this article, we propose a cycle-accurate and scalable system-level simulator that can be used to study the effects of using RRAM devices in neuromorphic computing chips. The simulator models a spatial neuromorphic chip architecture containing many neural cores with RRAM crossbars connected via a Network-on-Chip (NoC). We focus on system-level simulation and demonstrate the effectiveness of our simulator in understanding how non-linear RRAM effects such as stuck-at-faults (SAFs), write variability, and random telegraph noise (RTN) can impact an application’s behavior. By using our simulator, we show that RTN and write variability can have adverse effects on an application. Nevertheless, we show that these effects can be mitigated through proper design choices and the implementation of a write-verify scheme.

Ni/GeOx/p+ Si resistive-switching random-access memory with full Si processing compatibility and its characterization and modeling

In this study, a fully Si-compatible resistive-switching random-access memory (ReRAM) employing GeOx as the switching layer is fabricated, analyzed, and characterized. I–V curves and endurance characteristics have been obtained from the measurement of fabricated GeOx ReRAM devices. From the measurement results, the size dependence of the operation voltages is investigated. Here, we have carefully prepared the methods for GeOx switching layer and its interfaces. Physical vapor deposition (PVD) by an evaporator and subsequent thermal oxidation are the key processes for the switching layer. Additional annealing was performed and its effects on device performances have been closely investigated. It was revealed from the measurement results that the forming voltage of the GeOx ReRAM cell was lower than set voltage. This merit of forming-freeness gets rid of the necessity of preparing an additional voltage scheme and relatively complicated peripheral circuit for generating the forming voltage which is the highest value among the operation voltages in most cases. The low-resistance state (LRS) and high-resistance state (HRS) current ratio is larger than 103 and the number of endurance cycles reaches 400 even under the harsh condition of DC sweep mode. At the end of this study, a DC compact model for the fabricated ReRAM cell is schemed intuitively by simple elements including variable resistors, capacitors, and switches. The components in the conceived model are allowed to have highly accurate values by figuring out the predominant conduction mechanism and comparing with the measurement results in the recursive manner. The systematic study embracing process architecture, device fabrication and characterization, and circuit modeling would be highly beneficial in the array and system level architecture design.