Classification of 5-bit Binary Light Pulse Sequences Using Photoluminescence of Metal Halide Perovskite Memlumors
Source abstract
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
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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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