Memristor
holds great potential for enabling next-generation neuromorphic
computing hardware. Controlling the interfacial characteristics of
the device is critical for seamlessly integrating and replicating
the synaptic dynamic behaviors; however, it is commonly overlooked.
Herein, we report the straightforward oxidation of a Mo electrode
in air to design MoO
x
memristors that
exhibit nonvolatile ultrafast switching (0.6–0.8 mV/decade,
<1 mV/decade) with a high on/off ratio (>104), a
long
durability (>104 s), a low power consumption (17.9 μW),
excellent device-to-device uniformity, ingeniously synaptic behavior,
and finely programmable multilevel analog switching. The analyzed
physical mechanism of the observed resistive switching behavior might
be the conductive filaments formed by the oxygen vacancies. Intriguingly,
upon organization into memristor-based crossbar arrays, in addition
to simulated multipattern memorization, edge detection on random images
can be implemented well by parallel processing of pixels using a 3
× 3 × 2 array of Prewitt filter groups. These are vital
functions for neural system hardware in efficient in-memory computing
neural systems with massive parallelism beyond a von Neumann architecture.