Sodium-Doped Titania Self-Rectifying Memristors for Crossbar Array Neuromorphic Architectures

Adv Mater. 2022 Feb;34(6):e2106913. doi: 10.1002/adma.202106913. Epub 2021 Dec 23.

Abstract

Memristors integrated into a crossbar-array architecture (CAA) are promising candidates for nonvolatile memory elements in artificial neural networks. However, the relatively low reliability of memristors coupled with crosstalk and sneak currents in CAAs have limited the realization of the full potential of this technology. Here, high-reliability Na-doped TiO2 memristors grown in situ by atomic layer deposition (ALD) are demonstrated, where reversible Na migration underlies the resistive-switching mechanism. By employing ALD growth with an aqueous NaOH reactant in deionized water, uniform implantation of Na dopants is achieved in the crystallized TiO2 thin films at 250 °C without post-annealing. The resulting Na-doped TiO2 memristors show electroforming-free and self-rectifying resistive-switching behavior, and they are ideally suited for selectorless CAAs. Effective addressing of selectorless nodes is demonstrated via electrical measurement of individual memristors in a 6 × 6 crossbar using a read current of less than 1 µA with negligible sneak current at or below the noise level of ≈100 pA. Finally, the long-term potentiation and depression synaptic behavior from these Na-doped TiO2 memristors achieves greater than 99.1% accuracy for image-recognition tasks using a convolutional neural network based on the selectorless of crossbar arrays.

Keywords: Na-doped TiO 2; artificial neural networks; atomic layer deposition; long-term potentiation/depression; synaptic response.