Ferroelectricity-Defects Synergistic Artificial Synapses for High Recognition Accuracy Neuromorphic Computing

Abstract

The ability of ferroelectric memristors to modulate conductance and offer multilevel storage has garnered significant attention in the realm of artificial synapses. On one hand, the resistance change of ferroelectric memristors mainly depends on the polarization reversal. On the other hand, the defects such as oxygen vacancies, which are inevitable presence during high-temperature processes, can undergo diffusion drift with the polarization reversal, thereby change the interface potential barrier. Thus, it is both desirable and necessary to investigate the synergistic effect of ferroelectricity and defects. Here, we prepare BaTiO 3 ferroelectric memristor by pulse laser deposition and achieve resistance switching through the synergistic effect of ferroelectricity and oxygen vacancies. The memristor shows excellent switching characteristics with a large switching ratio (10 4 ) and good stability (10 3 s). It effectively emulates the features of artificial synapses and accomplishes decimal logical neural computing. In the neuromorphic system crafted with the memristor, the recognition accuracy of the 28 × 28 pixel image reaches 94.9%. These findings strongly support the research of ferroelectric memristors in neuromorphic devices.