A low-power reconfigurable memristor for artificial neurons and synapses

Abstract

With the advancement of artificial intelligence technology, memristors have aroused the interest of researchers because they can realize a variety of biological functions, good scalability, and high running speed. In this work, the amorphous semiconductor material silicon carbide (SiC) was used as the dielectric to fabricate the memristor with the Ag/SiC/n-Si structure. The device has a power consumption as low as 3.4 pJ, a switching ratio of up to 105, and a lower set voltage of 1.26 V, indicating excellent performance. Importantly, by adjusting the current compliance, the strength of the formed filaments changes, and the threshold characteristic and bipolar resistance switching phenomenon could be simultaneously realized in one device. On this basis, the biological long- and short-term memory process was simulated. Importantly, we have implemented leakage integration and fire models constructed based on structured Ag/SiC/n-Si memristor circuits. This low-power reconfigurable device opens up the possibilities for memristor-based applications combining artificial neurons and synapses.