Cross-Point Ferroelectric Hf_0.5Zr_0.5O₂ Capacitors for Remanent Polarization-Driven In-Memory Computing

Ferroelectric Hf_0.5Zr_0.5O₂ (HZO) capacitors have been extensively explored for in-memory computing (IMC) applications due to their nonvolatility and back-end-of-line (BEOL) compatible process. Several IMC approaches using resistance and capacitance states in ferroelectric HZO have been proposed for vector-matrix multiplication (VMM), but previous approaches suffer from limited accuracy and reliability. In this work, we propose a promising approach centered on the remanent polarization (P_r) switching of binary ferroelectric HZO capacitor synapses. We experimentally demonstrate a simple pattern recognition task showing that the voltage readout of P_r switching provides excellent accuracy due to its high on/off ratio and consequent reliability. We also performed large-scale simulations on a complex inference task, achieving high accuracy and immunity to device variations. We therefore believe that our proposed paradigm is promising for near-term neuromorphic IMC.