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To implement a SNN using a hardware system, an integrate and fire (I&F) neuron is commonly adopted as a spiking neuron owing to its simplicity. An I&F neuron integrates the input synaptic current and the membrane potential is charged, as shown in Figure 1a. When the membrane potential reaches the threshold voltage of the neuron, the neuron generates spikes to the next synapse layer and resets the membrane potential. Unfortunately, it is becoming burdensome to use conventional CMOS-based neurons in massive neuromorphic hardware due to their large areas and high power consumption. [6] In this regard, volatile thershold switching (TS) devices [7][8][9][10][11] and nonvolatile memory such as resistive random access memory (RRAM) , [12] phase change random access memory (PRAM), [13] ferromagnetic material, [14] and floating body transistor [15] based I&F neurons have been reported to overcome the limitations of conventional CMOS-based neurons. In nonvolatile memory device based I&F neurons wherein the memory device is used for integrating the input synaptic current, an additional circuit is required to return memory device to its initial state in the reset process of the neuron. However, in a TS-based I&F neuron, due to the volatile voltage hysteric switch characteristic of the TS device, a self-reset process is performed without a reset circuit. Thus, it enables the realization of a compact and low power consumption neuron. Although many TS-based I&F neurons have been studied, only the operations of I&F neuron and their biological plausibility have been reported. However, it is necessary to study and understand the correlation between the switching parameter of a TS device and the neuron characteristics for practical application of TS-based I&F neurons in various SNN-based hardware.Therefore, in this work, we investigated the effect of the switching parameters of the TS devices on the characteristics of TS-based I&F neurons through electrical measurements and computational simulation of three different types of neurons using a NbO 2 -based insulator-to-metal transition device (IMT), [16] a B-Te-based ovonic threshold switching (OTS) device, [17] and a Ag/HfO 2 -based atomic-switching TS device. [18] In addition, we confirmed the feasibility of TS-based neuron by simulating SNN, which converted from analog-based ANN prelearned by backpropagation.This study demonstrates an integrate and fire (I&F) neuron using threshold switching (TS) devices to implement spike-based neuromorphic system. An I&F neuron can be realized using the hysteric voltage switch characteristics of a TS device. To investigate the effects of various TS devices on neuron behavior, neurons are compared using three different types of TS device: NbO 2 -based insulator-to-metal transition (IMT) device, B-Te-based ovonic threshold switching device, and Ag/HfO 2 -based atomic-switching TS device. The results show that the off-state resistance and switching time of the TS devices determine the leaky/nonleaky characteristics and types of activation function ...

Multilevel cell (MLC) storage technology is attractive in achieving ultrahigh density memory with low cost. In this letter, we have demonstrated 3-bit per cell storage characteristics in a TaO x -based RRAM. By analyzing the key requirements for MLC operation mainly the switching uniformity and stability of resistance levels, an engineered stack based on thermodynamics in top electrode/(vacancy reservoir/defect control layer)/switching layer/bottom electrode structure was designed. In the optimized stack with ∼10-nm Ta layer incorporated at W/TaO x interface, seven low resistance state levels with same high resistance state were obtained by controlling the switching current down from 30 µA enabling low power 3-bit storage in contrast to the control device which shows 2-bit MLC with resistance saturation. The improved switching and MLC behavior is attributed to the minimized stochastic nature of set/reset operations due to filament confinement by favorable electric field generation and formation of thin but highly conductive filament which is confirmed electrically. Index Terms-Multi-level cell, RRAM, TaO x , vacancy reservoir, defect engineering, dense filament.

In this research, we investigate electrically driven threshold switching (TS) characteristics in electrochemical metallization cells by adopting the field-induced nucleation theory. For this aim, Ag/HfO2 and Ag/TiO2 based TS devices are prepared and examined. First, we carry out the field driven turn-on process to form Ag filaments created as a consequence of sequential nucleation of Ag ions from the bottom electrode. During the filament formation process, it is observed that the prepared devices show switching time exponential in voltage and temperature with different nucleation barrier energies (W0), which confirms the field-induced nucleation theory. Furthermore, we find that the device with higher W0 shows faster dissolution speed. This implies that the slow turn-off speed of the TS device can be improved by finding a material system with a higher W0 value.