**A Silicon-Compatible Synaptic Transistor Capable of Multiple Synaptic Weights toward Energy-E**ffi**cient Neuromorphic Systems**

#### **Eunseon Yu <sup>1</sup> , Seongjae Cho 2,\* and Byung-Gook Park 3,\***


Received: 15 July 2019; Accepted: 26 September 2019; Published: 30 September 2019

**Abstract:** In order to resolve the issue of tremendous energy consumption in conventional artificial intelligence, hardware-based neuromorphic system is being actively studied. Although various synaptic devices for the system have been proposed, they have shown limits in terms of endurance, reliability, energy efficiency, and Si processing compatibility. In this work, we design a synaptic transistor with short-term and long-term plasticity, high density, high reliability and energy efficiency, and Si processing compatibility. The synaptic characteristics of the device are closely examined and validated through technology computer-aided design (TCAD) device simulation. Consequently, full synaptic functions with high energy efficiency have been realized.

**Keywords:** energy consumption; hardware-based neuromorphic system; synaptic device; Si processing compatibility; TCAD device simulation
