Advances of RRAM Devices: Resistive Switching Mechanisms, Materials and Bionic Synaptic Application

Demonstration of Threshold Switching and Bipolar Resistive Switching in Ag/SnOx/TiN Memory Device

In this work, we observed the duality of threshold switching and non-volatile memory switching of Ag/SnOx/TiN memory devices by controlling the compliance current (CC) or pulse amplitude. The insulator thickness and chemical analysis of the device stack were confirmed by transmission electron microscope (TEM) images of the Ag/SnOx/TiN stack and X-ray photoelectron spectroscopy (XPS) of the SnOx film. The threshold switching was achieved at low CC (50 μA), showing volatile resistive switching. Optimal CC (5 mA) for bipolar resistive switching conditions with a gradual transition was also found. An unstable low-resistance state (LRS) and negative-set behavior were observed at CCs of 1 mA and 30 mA, respectively. We also demonstrated the pulse operation for volatile switching, set, reset processes, and negative-set behaviors by controlling pulse amplitude and polarity. Finally, the potentiation and depression characteristics were mimicked by multiple pulses, and MNIST pattern recognition was calculated using a neural network, including the conductance update for a hardware-based neuromorphic system.

Digital and analog functionality in monolayer AlOx-based memristors with various oxidizer sources

Memristors with the outstanding advantages are beneficial for neuromorphic computing and next-generation storage. Realizing various resistive switching behaviors in monolayer memristors is essential for understanding the device physics and fabricating fully memristive devices. In this paper, a simple and feasible method was proposed to achieve the digital and analog resistive switching in Cu/AlOx/Ag memristors by using ozone and water precursors in atomic layer deposition. According to the characterization results of surface topography, Raman spectrum and electrical measurement, the transition between the abrupt and gradual resistive switching was ascribed to the migration and diffusion of active electrode metal ions in the sparser, rougher and more amorphous AlOx dielectric films. The key features of biological synapses including long-term potentiation/depression, paired-pulse facilitation and learning-experience behaviors were emulated in the analog monolayer memristors. This study makes an important step towards the development of the sophisticated, multi-functional, and large-scale integrated neuromorphic devices and systems.

Improved Device Distribution in High-Performance SiNx Resistive Random Access Memory via Arsenic Ion Implantation

Large device variation is a fundamental challenge for resistive random access memory (RRAM) array circuit. Improved device-to-device distributions of set and reset voltages in a SiN_x RRAM device is realized via arsenic ion (As⁺) implantation. Besides, the As⁺-implanted SiN_x RRAM device exhibits much tighter cycle-to-cycle distribution than the nonimplanted device. The As⁺-implanted SiN_x device further exhibits excellent performance, which shows high stability and a large 1.73 × 10³ resistance window at 85 °C retention for 10⁴ s, and a large 10³ resistance window after 10⁵ cycles of the pulsed endurance test. The current–voltage characteristics of high- and low-resistance states were both analyzed as space-charge-limited conduction mechanism. From the simulated defect distribution in the SiN_x layer, a microscopic model was established, and the formation and rupture of defect-conductive paths were proposed for the resistance switching behavior. Therefore, the reason for such high device performance can be attributed to the sufficient defects created by As⁺ implantation that leads to low forming and operation power.

Improved Synaptic Device Properties of HfAlOx Dielectric on Highly Doped Silicon Substrate by Partial Reset Process

This work demonstrates the synaptic properties of the alloy-type resistive random-access memory (RRAM). We fabricated the HfAlOx-based RRAM for a synaptic device in a neuromorphic system. The deposition of the HfAlOx film on the silicon substrate was verified by X-ray photoelectron spectroscopy (XPS) analysis. It was found that both abrupt and gradual resistive switching could be implemented, depending on the reset stop voltage. In the reset process, the current gradually decreased at weak voltage, and at strong voltage, it tended to decrease rapidly by Joule heating. The type of switching determined by the first reset process was subsequently demonstrated to be stable switching by successive set and reset processes. A gradual switching type has a much smaller on/off window than abrupt switching. In addition, retention maintained stability up to 2000 s in both switching cases. Next, the multiple current states were tested in the gradual switching case by identical pulses. Finally, we demonstrated the potentiation and depression of the Cu/HfAlOx/Si device as a synapse in an artificial neural network and confirmed that gradual resistive switching was suitable for artificial synapses, using neuromorphic system simulation.

Electrical Properties and Biological Synaptic Simulation of Ag/MXene/SiO2/Pt RRAM Devices

Utilizing electronic devices to emulate biological synapses for the construction of artificial neural networks has provided a feasible research approach for the future development of artificial intelligence systems. Until now, different kinds of electronic devices have been proposed in the realization of biological synapse functions. However, the device stability and the power consumption are major challenges for future industrialization applications. Herein, an electronic synapse of MXene/SiO2 structure-based resistive random-access memory (RRAM) devices has been designed and fabricated by taking advantage of the desirable properties of SiO2 and 2D MXene material. The proposed RRAM devices, Ag/MXene/SiO2/Pt, exhibit the resistance switching characteristics where both the volatile and nonvolatile behaviors coexist in a single device. These intriguing features of the Ag/MXene/SiO2/Pt devices make them more applicable for emulating biological synaptic plasticity. Additionally, the conductive mechanisms of the Ag/MXene/SiO2/Pt RRAM devices have been discussed on the basis of our experimental results.

Self-Rectifying Resistive Switching and Short-Term Memory Characteristics in Pt/HfO2/TaOx/TiN Artificial Synaptic Device

Here, we propose a Pt/HfO₂/TaO_x/TiN artificial synaptic device that is an excellent candidate for artificial synapses. First, XPS analysis is conducted to provide the dielectric (HfO₂/TaO_x/TiN) information deposited by DC sputtering and atomic layer deposition (ALD). The self-rectifying resistive switching characteristics are achieved by the asymmetric device stack, which is an advantage of the current suppression in the crossbar array structure. The results show that the programmed data are lost over time and that the decay rate, which is verified from the retention test, can be adjusted by controlling the compliance current (CC). Based on these properties, we emulate bio-synaptic characteristics, such as short-term plasticity (STP), long-term plasticity (LTP), and paired-pulse facilitation (PPF), in the self-rectifying I–V characteristics of the Pt/HfO₂/TaO_x/TiN bilayer memristor device. The PPF characteristics are mimicked by replacing the bio-stimulation with the interval time of paired pulse inputs. The typical potentiation and depression are also implemented by optimizing the set and reset pulse. Finally, we demonstrate the natural depression by varying the interval time between pulse inputs.

Synaptic Characteristics from Homogeneous Resistive Switching in Pt/Al2O3/TiN Stack

In this work, we propose three types of resistive switching behaviors by controlling operation conditions. We confirmed well-known filamentary switching in Al₂O₃-based resistive switching memory using the conventional device working operation with a forming process. Here, filamentary switching can be classified into two types depending on the compliance current. On top of that, the homogeneous switching is obtained by using a negative differential resistance effect before the forming or setting process in a negative bias. The variations of the low-resistance and high-resistance states in the homogeneous switching are comparable to the filamentary switching cases. However, the drift characteristics of the low-resistance and high-resistance states in the homogeneous switching are unstable with time. Therefore, the short-term plasticity effects, such as the current decay in repeated pulses and paired pulses facilitation, are demonstrated when using the resistance drift characteristics. Finally, the conductance can be increased and decreased by 50 consecutive potentiation pulses and 50 consecutive depression pulses, respectively. The linear conductance update in homogeneous switching is achieved compared to the filamentary switching, which ensures the high pattern-recognition accuracy.

Short-Term Memory Dynamics of TiN/Ti/TiO2/SiOx/Si Resistive Random Access Memory

In this study, we investigated the synaptic functions of TiN/Ti/TiO₂/SiO_x/Si resistive random access memory for a neuromorphic computing system that can act as a substitute for the von-Neumann computing architecture. To process the data efficiently, it is necessary to coordinate the information that needs to be processed with short-term memory. In neural networks, short-term memory can play the role of retaining the response on temporary spikes for information filtering. In this study, the proposed complementary metal-oxide-semiconductor (CMOS)-compatible synaptic device mimics the potentiation and depression with varying pulse conditions similar to biological synapses in the nervous system. Short-term memory dynamics are demonstrated through pulse modulation at a set pulse voltage of −3.5 V and pulse width of 10 ms and paired-pulsed facilitation. Moreover, spike-timing-dependent plasticity with the change in synaptic weight is performed by the time difference between the pre- and postsynaptic neurons. The SiO_x layer as a tunnel barrier on a Si substrate provides highly nonlinear current-voltage (I–V) characteristics in a low-resistance state, which is suitable for high-density synapse arrays. The results herein presented confirm the viability of implementing a CMOS-compatible neuromorphic chip.

Emulation of Biological Synapse Characteristics from Cu/AlN/TiN Conductive Bridge Random Access Memory

Here, we present the synaptic characteristics of AlN-based conductive bridge random access memory (CBRAM) as a synaptic device for neuromorphic systems. Both non-volatile and volatile memory are observed by simply controlling the strength of the Cu filament inside the AlN film. For non-volatile switching induced by high compliance current (CC), good retention with a strong Cu metallic filament is verified. Low-resistance state (LRS) and high-resistance state (HRS) conduction follow metallic Ohmic and trap-assisted tunneling (TAT), respectively, which are supported by I-V fitting and temperature dependence. The transition from long-term plasticity (LTP) to short-term plasticity (STP) is demonstrated by increasing the pulse interval time for synaptic device application. Also, paired-pulse facilitation (PPF) in the nervous system is mimicked by sending two identical pulses to the CBRAM device to induce STP. Finally, potentiation and depression are achieved by gradually increasing the set and reset voltage in pulse transient mode.