Excited State Opto‐Ionic Reservoir Computing in Hybrid Perovskite Electrochemically‐Gated Luminescent Cells
Year: 2026
Type: article
Abstract: ABSTRACT 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 10 6 nodes per cm 2 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.
Source: Advanced Materials
Institution: Heidelberg University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $6,070
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W7128026315
