Hafnia ferroelectric transistor for wearable device platform

Abstract

The use of wearable devices and various types of data are rapidly increasing due to the era of the Internet of Things (IoT) has evolved. In order to efficiently process the data, neuromorphic computing, which enables parallel computing and an adaptive learning process is one of the promising alternative compared to the existing von Neumann-structured computing. In particular, the hafnia-based ferroelectric thin film exhibits excellent ferroelectricity at a thin thickness (~10 nm), and has excellent CMOS process compatibility, so studies on the application of neuromorphic chips are actively being conducted. However, the hafnia material has a characteristic that ferroelectricity is formed only under a certain temperature (~600 ℃) and pressure, and the tetragonal phase and the monoclinic phase are formed and ferroelectricity is lost under different conditions. For this reason, research on application methods to wearable devices requiring a low-temperature process is insufficient. In this paper, to overcome the high temperature annealing condition, we proposed a method of securing ferroelectricity under low temperature annealing (~250 ℃) by applying various annealing method to the hafnia-based thin film ($Hf_{0.5}Zr_{0.5}O_{2}$). Furthermore, the hafnia thin film applied with a low temperature process annealing and a hafnia based ferroelectric thin film transistor were fabricated on a flexible substrate to evaluate synaptic device characteristics and calculated the expected accuracy when operating as a neuromorphic chip. Through this, the scalability and applicability of the hafnia-based ferroelectric thin film in the wearable device platform were verified.