Understanding fatigue and recovery mechanisms in Hf0.5Zr0.5O₂ capacitors for designing high endurance ferroelectric memory and neuromorphic hardware

This is the authors' abstract. We don't add key points for this paper.

Novel non-volatile memory devices are under intense investigation to revolutionize information processing for ultra-energy-efficient implementation of artificial intelligence and machine learning tasks. Ferroelectric memory devices with ultra-low power and fast operation, non-volatile data retention and reliable switching to multiple polarization states promise one such option for memory and synaptic weight elements in neuromorphic hardware. For quick adaptation by industry, complementary metal oxide semiconductor process compatibility is a key criterion that led to huge attention to hafnia-based FE materials. Designing a high endurance hafnia-based FE is crucially important for online training applications in neuromorphic hardware. In this work, we report on the physical origins of fatigue and recovery mechanisms in back-end-of-line compatible ferroelectric Hf0.5Zr0.5O₂ thin film capacitors for designing high-endurance memory devices. We show that Hf0.5Zr0.5O₂ devices are capable of recovery from the fatigue state with less than 5 V pulse sweeps. Such recovery has been conducted multiple times reaching 88%-93% of 2Pr upon each retrieval. This result indicates that with specifically engineered material stacking and annealing protocols, it is possible to reach endurance exceeding 10⁹ cycles at room temperature, leading to ultralow power ferroelectric non-volatile memory components or synaptic weight elements compatible with online training tasks for neuromorphic computing.