Multi-state nonvolatile capacitances in HfO2-based ferroelectric capacitor for neuromorphic computing
Shuyu Wu, Xumeng Zhang, Rongrong Cao, Keji Zhou, J. Lu, Chao Li, Yang Yang, Dashan Shang, Yingfen Wei, Hao Jiang, Qi Liu
Abstract
In the last decade, HfO2-based ferroelectric capacitors (FeCaps) have undergone significant advancements, particularly within the realm of nonvolatile ferroelectric random access memories (FeRAMs). Nonetheless, the READ operation in FeRAMs is inherently destructive, rendering it unsuitable for neuromorphic computing. In this study, we have engineered tunable nonvolatile capacitances within FeCaps, featuring nondestructive readout functionality. Robust capacitance states can be read at a zero d.c. bias (Vbias) with different a.c. signals, not only preventing the alteration of their stored state but also benefiting to the low power consumption. Moreover, the capacitance memory window (CMW) at Vbias of zero can be effectively modulated through electrode engineering, leading to a larger CMW when there is a greater disparity in work functions between the electrodes. Furthermore, we provide a comprehensive investigation into synaptic behavior of TiN/Hf0.5Zr0.5O2/Pt FeCaps, demonstrating their excellent cycle-to-cycle uniformity, retention, and endurance characteristics, which confirm their high reliability in maintaining nonvolatile capacitance states. These findings underscore the significant potential of FeCaps in advancing low-power neuromorphic computing.