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

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.