Charge Trapping and Defect Dynamics as Origin of Memory Effects in Metal Halide Perovskite Memlumors

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Alexandr Marunchenko - , Lund University, St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Jitendra Kumar - , Lund University (Autor:in)
  • Alexander Kiligaridis - , Lund University (Autor:in)
  • Shraddha M. Rao - , Lund University (Autor:in)
  • Dmitry Tatarinov - , St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Ivan Matchenya - , St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Elizaveta Sapozhnikova - , St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Ran Ji - , Professur für Neuartige Elektroniktechnologien (gB/IFW und cfaed), Leibniz-Institut für Festkörper- und Werkstoffforschung Dresden (Autor:in)
  • Oscar Telschow - , Professur für Neuartige Elektroniktechnologien (gB/IFW und cfaed), Leibniz-Institut für Festkörper- und Werkstoffforschung Dresden (Autor:in)
  • Julius Brunner - , Professur für Neuartige Elektroniktechnologien (gB/IFW und cfaed), Leibniz-Institut für Festkörper- und Werkstoffforschung Dresden (Autor:in)
  • Alexei Yulin - , St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Anatoly Pushkarev - , St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO) (Autor:in)
  • Yana Vaynzof - , Center for Advancing Electronics Dresden (cfaed), Professur für Neuartige Elektroniktechnologien (gB/IFW und cfaed), Leibniz-Institut für Festkörper- und Werkstoffforschung Dresden (Autor:in)
  • Ivan G. Scheblykin - , Lund University (Autor:in)

Abstract

Large language models for artificial intelligence applications require energy-efficient computing. Neuromorphic photonics has the potential to reach significantly lower energy consumption in comparison with classical electronics. A recently proposed memlumor device uses photoluminescence output that carries information about its excitation history via the excited state dynamics of the material. Solution-processed metal halide perovskites can be used as efficient memlumors. We show that trapping of photogenerated charge carriers modulated by photoinduced dynamics of the trapping states themselves explains the memory response of perovskite memlumors on time scales from nanoseconds to minutes. The memlumor concept shifts the paradigm of the detrimental role of charge traps and their dynamics in metal halide perovskite semiconductors by enabling new applications based on these trap states. The appropriate control of defect dynamics in perovskites allows these materials to enter the field of energy-efficient photonic neuromorphic computing, which we illustrate by proposing several possible realizations of such systems.

Details

OriginalspracheEnglisch
Seiten (von - bis)6256-6265
Seitenumfang10
FachzeitschriftJournal of Physical Chemistry Letters
Jahrgang15
Ausgabenummer24
Frühes Online-Datum6 Juni 2024
PublikationsstatusVeröffentlicht - 20 Juni 2024
Peer-Review-StatusJa

Externe IDs

PubMed 38843474

Schlagworte