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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 microst...

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Main Authors: Kollenz, Philipp (Author) , Herrle, Carina (Author) , Göhringer, Leonard (Author) , Solhtalab, Nasrin (Author) , Wickenhäuser, Tom (Author) , Pernice, Wolfram (Author) , Klingeler, Rüdiger (Author) , Deschler, Felix (Author)
Format: Article (Journal)
Language:English
Published: 6 March 2026
In: Advanced materials
Year: 2026, Volume: 38, Issue: 14, Pages: 1-9
ISSN:1521-4095
DOI:10.1002/adma.202512575
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1002/adma.202512575
Verlag, kostenfrei, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202512575
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Author Notes:Philipp Kollenz, Carina Herrle, Leonard Göhringer, Nasrin Solhtalab, Tom Wickenhäuser, Wolfram Pernice, Rüdiger Klingeler, Felix Deschler
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Summary: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.
Item Description:Online veröffentlicht: 5. Februar 2026
Gesehen am 15.04.2026
Physical Description:Online Resource
ISSN:1521-4095
DOI:10.1002/adma.202512575

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