Artificial optoelectronic synapses based on organic–inorganic hybrid perovskite ferroelectrics for reservoir computing

Abstract

The rapid advancement of artificial intelligence (AI) demands faster processing units and more efficient algorithms. This study introduces a neuromorphic visual system based on a single-layer ferroelectric semiconductor material, specifically the [R-1-(4-chlorophenyl)ethylammonium]₂PbI₄ (R-LIPF) organic–inorganic perovskite ferroelectric layer, integrated into a reservoir computing (RC) system for digital image recognition. The R-LIPF device demonstrates tunable synaptic functions, including short-term plasticity (STP), paired-pulse facilitation (PPF), and long-term plasticity (LTP) under optical stimulation. By pre-applying voltage, we successfully modulated the polarization state of the R-LIPF layer, enabling control over synaptic relaxation behavior. Unlike traditional ferroelectric oxide semiconductor photon synapses, the R-LIPF-based device offers enhanced functionality and simplified device architecture. This research paves the way for highly efficient neuromorphic computing hardware, with potential applications in energy-efficient machine vision systems.