Photo-Enhanced Resistive Switching Effect in High-Performance MAPbI₃ Memristors

The rapid development of artificial intelligence (AI) requires processing vast amounts of complex information, which has accelerated the exploration of neuromorphic computing systems. Artificial neuromorphic synapses based on memristors of organic-inorganic halide perovskites (OHPs) potentially exploit a niche area for brain-inspired neuromorphic computing, which can be operated as biological synapses to realize signal processing. Here, MAPbI(3)-based memristors with reliable resistance states triggered by electric fields or photons are reported. A model for resistive switching (RS) originated from conductive filaments (CFs) based on intrinsic defect migrations is proposed. Importantly, the unique photoresponsive characteristic provides the opportunity to enhance the RS through multifunctional photo-coupling. Enhanced by monochromatic illumination, memristors exhibit RS with remarkable characteristics such as ultralow operating voltage, high ON/OFF ratio (4.3 x 10(3)), small HRS/LRS variation coefficient (29.91%/13.82%), stable endurance (10(4) cycles), long retention time (10(5) s), and ultralow power consumption. Moreover, photons can modulate the nonvolatile devices to maintain a great ON/OFF ratio over 9 days under ambient conditions without any encapsulation. The research presents plausible applications of memristors in coupling ions, electrons, and photons, thus contributing to applicability for multifunctional optoelectronics and optogenetics tunable neuromorphic systems.