Depolarization Field Controllable HfZrOx-Based Ferroelectric Capacitors for Physical Reservoir Computing System

Abstract

Reservoir computing as one of the artificial neural networks can process input signals in various ways, thereby showing strength in modeling data that changes over time. The reservoir is utilized in various fields because it is particularly energy efficient in learning and can exhibit powerful performance with relatively few trainings cost. This study emphasizes the significant advantages of the hafnium zirconium oxide (HZO) film in reservoir applications by controlling the depolarization field. The decay time of HZO-based ferroelectric memory devices is investigated, focusing on the impact of both ferroelectric layer thickness and interlayer (IL) thickness on physical reservoir computing system. Devices with HZO film thicknesses of 10, 15, and 20 nm were fabricated and characterized. Among these, the 15 nm HZO film demonstrated optimal thickness, exhibiting excellent ferroelectric properties, including enhanced orthorhombic phase (o-phase) formation and reliable short-term memory characteristics. When the optimized device for decay time is integrated into a reservoir computing system, it achieved a remarkable average accuracy of 93.42% in image recognition tasks, emphasizing its capability for high-precision computations.