Understanding Recombination Dynamics from Electroluminescence of Organic Light-Emitting Diodes Using Artificial Intelligence

Research output: Contribution to journalConference articlepeer-review

Abstract

Distinguishing exciton and polaron dynamics in the electroluminescence (EL) of organic light-emitting diodes (OLEDs) is difficult since the delayed EL originated from a combination of the excitonic process and slow recombination process. In this work, the recombination dynamics was extracted from the transient EL only via prediction of the recombination coefficient using artificial intelligence (AI). AI model with a high prediction accuracy (R2) of 0.947 successfully analyzed the polaron dynamics of exciplex-forming co-host-based OLEDs.

Original languageEnglish
Pages (from-to)1575-1578
Number of pages4
JournalDigest of Technical Papers - SID International Symposium
Volume54
Issue number1
DOIs
StatePublished - 2023
EventSID International Symposium Digest of Technical Papers, 2023 - Los Angeles, United States
Duration: 21 May 202326 May 2023

Keywords

  • electroluminescence
  • organic light-emitting diodes
  • recombination coefficient, artificial intelligence

Fingerprint

Dive into the research topics of 'Understanding Recombination Dynamics from Electroluminescence of Organic Light-Emitting Diodes Using Artificial Intelligence'. Together they form a unique fingerprint.

Cite this