Artificial Synapse Based on a 2D-SnO2 Memtransistor with Dynamically Tunable Analog Switching for Neuromorphic Computing

A new type of two-dimensional (2D) SnO2 semiconductor-based gate-tunable memristor, that is, a memtransistor, an integrated device of a memristor and a transistor, was demonstrated to advance next-generation neuromorphic computing technology. The polycrystalline 2D-SnO2 memristors derived from a low-temperature and vacuum-free liquid metal process offer several interesting resistive switching properties such as excellent digital/analog resistive switching, multistate storage, and gatetunability function of resistance switching states. Significantly, the gate tunability function that is not achievable in conventional two-terminal memristors provides the capability to implement heterosynaptic analog switching by regulating gate bias for enabling complex neuromorphic learning. We successfully demonstrated that the gate-tunable synaptic device dynamically modulated the analog switching behavior with good linearity and an improved conductance change ratio for high recognition accuracy learning. The presented gate-tunable 2D-oxide memtransistor will advance neuromorphic device technology and open up new opportunities to design learning schemes with an extra degree of freedom.

Automated summary

The study demonstrates a new type of gate-tunable memristor based on 2D-SnO2 material, which can achieve complex neuromorphic learning. By regulating the gate bias, the gate-tunable synaptic device dynamically modulates the analog switching behavior, while exhibiting excellent linearity and an improved conductance change ratio. This new device opens up new opportunities for advancing neuromorphic device technology.