Hafnium-based ferroelectric devices for neuromorphic computing: From materials physics to systems

Technological progress is advancing at a rapid pace, and the rate of chip performance improvements and transistor density increases is gradually diverging from Moore's Law predictions. Simultaneously, the "memory wall" and "power wall" challenges inherent in the von Neumann architecture have become increasingly prominent. Today, neuromorphic computing—inspired by the human brain—is emerging as one of the most promising computational paradigms. To realize efficient brain-like hardware, a high-performance, scalable, non-volatile memory device is essential. Among these, ferroelectric field-effect transistors (FeFETs) based on hafnium oxide (HfO₂) stand out as the most representative. It effectively mimics biological synaptic plasticity while offering high compatibility with CMOS processes, excellent scalability, fast low-power switching characteristics, and inherent controllable three-terminal field-effect properties.

The paper systematically reviews the research progress of HfO₂-based ferroelectric devices in the field of neuromorphic computing. Starting from the ferroelectric physical properties of HfO₂, it first discusses engineering regulation of the ferroelectric phase through methods such as doping and strain, and elaborates on the associated material-level challenges. Building upon this foundation, this review discusses representative HfO₂-based ferroelectric device architectures, including FeFETs, ferroelectric tunnel junctions (FTJs), ferroelectric diodes (Fe-diodes), and advanced fin field-effect transistor (FinFET)/nanowire ferroelectric transistors. The primary focus is on their applications in simulating biological synapses and neurons, along with the impact on performance optimization. The study also extends from devices to system-level integration, addressing issues such as the non-idealities in crossbar arrays, power consumption in peripheral circuits, and challenges in hardware-software co-design. Finally, this research comprehensively summarizes the significant challenges currently facing science and technology from multiple perspectives and proposes several promising solutions. Through comprehensive research, this paper identifies contemporary development directions: integrated applications of two-dimensional ferroelectric materials, exploration of novel computational paradigms, and convergence of sensing, storage, and computation. It aims to provide a comprehensive reference framework for future research in this field.