Impact of Ta/Ti electrodes on linearities of TaOx-based resistive random-access memories for neuromorphic computing

In this work, by incorporating different electrodes (Ta/Ti) onto TaO(x)dielectric layer, we studied both the conductance reading and conductance updating (long term potentiation and depression) linearities in the two RRAM devices. Owing to the composition modulation (CM) mechanism, the Ta-electrode device shows better conductance reading and updating linearities. The RRAM device linearities directly influence the performance of the neural network when the devices are used as synapses. System evaluation of a two-layer neural network considering the conductance reading and updating linearity factors further confirm that both the training and inference accuracies of Ta electrode device are better than those of the Ti electrode one. We believe that this work could serve as a powerful reference for engineering synaptic devices with good linearity for neuromorphic computing applications.