Artificial HfO 2 /TiO x Synapses with Controllable Memory Window and High Uniformity for Brain-Inspired Computing.

Artificial neural networks, as a game-changer to break up the bottleneck of classical von Neumann architectures, have attracted great interest recently. As a unit of artificial neural networks, memristive devices play a key role due to their similarity to biological synapses in structure, dynamics, and electrical behaviors. To achieve highly accurate neuromorphic computing, memristive devices with a controllable memory window and high uniformity are vitally important. Here, we first report that the controllable memory window of an HfO 2 /TiO x memristive device can be obtained by tuning the thickness ratio of the sublayer. It was found the memory window increased with decreases in the thickness ratio of HfO 2 and TiO x . Notably, the coefficients of variation of the high-resistance state and the low-resistance state of the nanocrystalline HfO 2 /TiO x memristor were reduced by 74% and 86% compared with the as-deposited HfO 2 /TiO x memristor. The position of the conductive pathway could be localized by the nanocrystalline HfO 2 and TiO 2 dot, leading to a substantial improvement in the switching uniformity. The nanocrystalline HfO 2 /TiO x memristive device showed stable, controllable biological functions, including long-term potentiation, long-term depression, and spike-time-dependent plasticity, as well as the visual learning capability, displaying the great potential application for neuromorphic computing in brain-inspired intelligent systems.