TiW/SiOX:Al/TiW memristor with negative differential resistance effect for neuromorphic computing

Abstract

Memristors, acting as artificial synapses, are proposed to be a promising candidate for neuromorphic computing applications. In this work, the CMOS process-compatible TiW/SiOX:Al/TiW memristor with negative differential resistance (NDR) effect is explored for this application. Nonpolar switching with a 340 on/off ratio, data retention beyond 106 s, and endurance of 106 cycles are realized. The device shows excellent analog behavior with nonlinearities of 1.69 and 0.65 of long-term potentiation and depression, respectively, under identical pulse stimuli. The synaptic features such as long-term potentiation (LTP), long-term depression (LTD), spike-timing-dependent plasticity (STDP), and paired-pulse facilitation (PPF) are mimicked. Moreover, on the basis of the symmetry and linearity of the conductance of TiW/SiOX:Al/TiW memristor, the neural network simulation for supervised learning presents successful pattern recognition, with an accuracy of 93.11% achieved after 20 iterations. It is proposed that the nonpolar NDR switching originates from the discontinuous Al metal nanoparticles that form deeply localized states in the energy band and result in the trap/de-trap of electronic carriers. Overall, this memristor with the NDR effect presents a unique way to simulate artificial synapse behavior for neuromorphic computing.