journal article·2025-08-08Open access

Classification of 5-bit Binary Light Pulse Sequences Using Photoluminescence of Metal Halide Perovskite Memlumors

Jitendra Kumar, Daniel Lizotte, Alexandr Marunchenko, Dmitry Tatarinov, Shivam Singh, Yana Vaynzof, Ivan. G. Scheblykin

ACS Energy Letters· Volume 10· Issue 8

Abstract

High Resolution Image Download MS PowerPoint Slide A memlumor is an innovative neuromorphic luminescent device with a state-dependent photoluminescence quantum yield (PLQY) designed for optical neuromorphic computing applications. Metal halide perovskite memlumors leverage charge trapping and photodoping to modulate the PLQY, making it dependent on the excitation light history. Here, we demonstrate the ability of perovskite memlumors to classify time-dependent binary optical signals on sub-microsecond timescales. Sequences of laser pulses (representing ones) and gaps (absence of pulses representing zeros) were used to excite photoluminescence in MAPbBr 3 and triple cation perovskite films. By reading only the time-integrated PL signal, we completely recognized the time-dependent input patterns containing 5 bits of information. The potential of perovskites for applications in optical reservoir computing based on their complex and diverse photophysics is discussed.
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Research context

OpenAlex topics: Perovskite Materials and Applications · Neural Networks and Reservoir Computing · Advanced Memory and Neural Computing

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Affiliations

Chemical Physics and NanoLund

Lund University

School of Physics and Engineering

ITMO University

Chair for Emerging Electronic Technologies

Technical University of Dresden

Leibniz-Institute for Solid State and Materials Research Dresden

Funding

Vetenskapsr?det · NanoLund, Lunds Universitet · Deutsche Forschungsgemeinschaft · Crafoordska Stiftelsen · H2020 Marie Sklodowska-Curie Actions · Wenner-Gren Foundation · Joint Indo Swedish project

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