With the rapid advancement of emerging information technologies—such as artificial intelligence (AI), big data, and cloud computing—the limitations posed by the "power wall" and "memory wall" in traditional von Neumann computing architectures have become increasingly pronounced. Neuromorphic computing, an innovative computational paradigm that mimics the operational mechanisms of human brain neurons, is widely regarded as a pivotal solution to overcoming these bottlenecks. Among various technologies, ferroelectric tunnel junctions (FTJs) have emerged as a standout candidate for next-generation neuromorphic memory devices due to their compact size, non-destructive readout capabilities, multi-level conductance modulation, and ultra-low power consumption. Notably, ferroelectric HfO₂ with a fluorite structure offers distinct advantages over traditional perovskite-type ferroelectric materials: it is not only compatible with silicon-based CMOS processes but also retains stable performance even as device dimensions are significantly reduced.