Highly Linear and Symmetric Synaptic Memtransistors Based on Polarization Switching in Two-Dimensional Ferroelectric Semiconductors

Abstract

Brain-inspired neuromorphic computing hardware based on artificial synapses offers efficient solutions to perform computational tasks. However, the nonlinearity and asymmetry of synaptic weight updates in reported artificial synapses have impeded achieving high accuracy in neural networks. Here, this work develops a synaptic memtransistor based on polarization switching in a two-dimensional (2D) ferroelectric semiconductor (FES) of α-In₂ Se₃ for neuromorphic computing. The α-In₂ Se₃ memtransistor exhibits outstanding synaptic characteristics, including near-ideal linearity and symmetry and a large number of programmable conductance states, by taking the advantages of both memtransistor configuration and electrically configurable polarization states in the FES channel. As a result, the α-In₂ Se₃ memtransistor-type synapse reaches high accuracy of 97.76% for digit patterns recognition task in simulated artificial neural networks. This work opens new opportunities for using multiterminal FES memtransistors in advanced neuromorphic electronics.

Keywords: artificial synapses; ferroelectric semiconductors; memtransistors; neuromorphic computing; two-dimensional nanomaterials.