Heterosynaptic Plasticity and Neuromorphic Boolean Logic Enabled by Ferroelectric Polarization Modulated Schottky Diodes

Abstract

Neuromorphic computing employs a great number of artificial synapses which transfer information between neurons. Conventional two- or three-terminal artificial synapses with homosynaptic plasticity suffer from a positive feedback loop problem. Synapses with heterosynaptic plasticity are thus required to perform learning, processing and modulating simultaneously. Here, complementary metal-oxide-semiconductor compatible artificial synapses based on ferroelectric polarization modulated Schottky diodes (FEMOD) on silicon, which enables heterosynaptic plasticity with multi-functionalities, high endurance, low power consumption, and high speed, are presented. High accuracy is obtained in the supervised learning simulation of artificial neural networks due to the large number of conductance states, good linearity, and small variations of FEMOD synapses. Boolean functions are demonstrated with only one or two FEMOD devices operating at low voltage and low power consumption. The proposed device structure performs multi-functions of biological synapse and Boolean logic, thus provides high potential for the future large scale and low power neuromorphic computing applications.