Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells

We introduce a neuromorphic reservoir computing concept that leverages the complex interplay between electronic and ionic states in lead halide perovskites to run algorithms by harnessing opto-ionic modulation of photoexcited state populations. The system leverages the heterogeneous material microstructure and ultrafast spatio-temporal electronic state dynamics in perovskite microcrystals to generate a high-dimensional internal state space reservoir within the charge carrier populations. This reservoir exhibits complex, nonlinear, and adaptive behavior. The computation output is read directly from the photogenerated luminescence using diffraction-limited resolution with 10⁶ nodes per cm² and energy of 800 pJ per node-operation. The system performs robustly in distinguishing 4-bit pulse sequences with a mean accuracy of 87%, showcasing its potential for neuromorphic computing tasks. Our work reveals excited-state dynamics as a platform for exploring nanoscale computing with photoactive materials, also at high speeds using ultrafast photophysics, with large potential for the development of next-generation neuromorphic technologies.