Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering

Abstract

Neuromorphic computing offers parallel data processing and low energy consumption and can be useful to replace conventional von Neumann computing. Memristors are two-terminal devices with varying conductance that can be used as synaptic arrays in hardware-based neuromorphic devices. In this research, we extensively investigate the analog symmetric multi-level switching characteristics of zinc tin oxide (ZTO)-based memristor devices for neuromorphic systems. A ZTO semiconductor layer is introduced between a complementary metal-oxide-semiconductor (CMOS) compatible Ni top electrode and a highly doped poly-Si bottom electrode. A variety of bio-realistic synaptic features are demonstrated, including long-term potentiation (LTP), long-term depression (LTD), and spike timing-dependent plasticity (STDP). The Ni/ZTO/Si device in which the adjustment of the number of states in conductance is realized by applying different pulse schemes is highly suitable for hardware-based neuromorphic applications. We evaluate the pattern recognition accuracy by implementing a system-level neural network simulation with ZTO-based memristor synapses. The density of states (DOS) and charge density plots reveal that oxygen vacancies in ZTO assist in generating resistive switching in the Ni/ZTO/Si device. The proposed ZTObased memristor composed of metal-insulator-semiconductor (MIS) structure is expected to contribute to future neuromorphic applications through further studies.

Density functional theory insight into metal ions and vacancies for improved performance in storage devices

“…The review of Chakraborty et al was focused on low energy aspect of NVM and their application in energy efficient memory and computing devices 15 . Our research group has reported earlier various characteristics of low power RRAM devices in different RS materials 14,16,17 . Due to low power consumption, RRAM is considered as a dominating substituent of static random‐access memory 10 .…”

Towards Sustainable Crossbar Artificial Synapses with Zinc-Tin Oxide

“…This material has shown synaptic operations which can be applied for both computing paradigms of deep neural networks (DNNs) and spiking neural networks (SNNs). However, due to indium and gallium both being critical raw materials, the use of zinc-tin oxide (ZTO) has started to be considered as a reliable substitute [15][16][17][18]. There are few reports on ZTO memristive devices with synaptic capabilities [19,20], and even fewer using exclusively ZTO as their switching medium [21,22], with all sharing a common bottom electrode configuration.…”

“…However, this implies the application of the voltage to the Schottky contact. In order to use a more universal terminology, the above-mentioned switching mode is referred to as "forward set", since the set operation happens in the diode's forward directions [17].…”

Threshold-Variation-Tolerant Coupling-Gate α-IGZO Synaptic Transistor for More Reliably Controllable Hardware Neuromorphic System

“…However, power consumption per chip getting higher, joule heating becoming more serious with chip complexity, and system speed bottleneck due to serial data processing have much room to resolve [2]- [5]. In order to overcome these limits and increase the parallel computing capability more importantly valued in the massive data processing, new computing architecture has been sought and neuromorphic system is on the leading edge in recent days [6]- [9]. The neuromorphic system realizes various neural networks defined by mathematical and software approaches through hardware.…”