Improvement of polarization switching in ferroelectric transistor by interface trap reduction for brain-inspired artificial synapses

Abstract

Numerous devices have been studied to accomplish a brain-inspired neuromorphic computing system; however, their characteristics require improvement to enhance operation accuracy of neuromorphic systems. Here, we propose a ferroelectric field-effect transistor based on Hf0.5Zr0.5O2 for a high-performance artificial synaptic device by reducing interface trap density. Using polarization in the Hf0.5Zr0.5O2 ferroelectric layer, threshold voltage is precisely controlled to achieve synaptic characteris-tics. However, synaptic characteristics are degraded because interface traps cause threshold voltage shift in the direction opposite to the threshold voltage shift by polarization. Therefore, oxygen plasma treatment was performed to minimize degradation by interface traps. Thus, outstanding synaptic characteristics including the linearity of the weight update, the max/min weight ratio, and the number of weights were observed. Furthermore, high repeatability and long-term plasticity was observed at low operating power. Therefore, our study demonstrated a promising method for implementing a high -accuracy, low-power neuromorphic system with progressed artificial synaptic devices.(c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).