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Direct identification of interfacial degradation in blue OLEDs using nanoscale chemical depth profiling

Author

Listed:
  • Gustavo F. Trindade

    (National Physical Laboratory, NiCE-MSI)

  • Soohwan Sul

    (Samsung Electronics Co., Ltd.)

  • Joonghyuk Kim

    (Samsung Electronics Co., Ltd.)

  • Rasmus Havelund

    (National Physical Laboratory, NiCE-MSI)

  • Anya Eyres

    (National Physical Laboratory, NiCE-MSI)

  • Sungjun Park

    (Samsung Electronics Co., Ltd.)

  • Youngsik Shin

    (Samsung Electronics Co., Ltd.)

  • Hye Jin Bae

    (Samsung Electronics Co., Ltd.)

  • Young Mo Sung

    (Samsung Electronics Co., Ltd.)

  • Lidija Matjacic

    (National Physical Laboratory, NiCE-MSI)

  • Yongsik Jung

    (Samsung Electronics Co., Ltd.)

  • Jungyeon Won

    (Samsung Electronics Co., Ltd.)

  • Woo Sung Jeon

    (Samsung Electronics Co., Ltd.)

  • Hyeonho Choi

    (Samsung Electronics Co., Ltd.)

  • Hyo Sug Lee

    (Samsung Electronics Co., Ltd.)

  • Jae-Cheol Lee

    (Samsung Electronics Co., Ltd.
    Korea Research Institute of Material Property Analysis (KRIMPA))

  • Jung-Hwa Kim

    (Samsung Electronics Co., Ltd.)

  • Ian S. Gilmore

    (National Physical Laboratory, NiCE-MSI)

Abstract

Understanding the degradation mechanism of organic light-emitting diodes (OLED) is essential to improve device performance and stability. OLED failure, if not process-related, arises mostly from chemical instability. However, the challenges of sampling from nanoscale organic layers and interfaces with enough analytical information has hampered identification of degradation products and mechanisms. Here, we present a high-resolution diagnostic method of OLED degradation using an Orbitrap mass spectrometer equipped with a gas cluster ion beam to gently desorb nanometre levels of materials, providing unambiguous molecular information with 7-nm depth resolution. We chemically depth profile and analyse blue phosphorescent and thermally-activated delayed fluorescent (TADF) OLED devices at different degradation levels. For OLED devices with short operational lifetimes, dominant chemical degradation mainly relate to oxygen loss of molecules that occur at the interface between emission and electron transport layers (EML/ETL) where exciton distribution is maximised, confirmed by emission zone measurements. We also show approximately one order of magnitude increase in lifetime of devices with slightly modified host materials, which present minimal EML/ETL interfacial degradation and show the method can provide insight for future material and device architecture development.

Suggested Citation

  • Gustavo F. Trindade & Soohwan Sul & Joonghyuk Kim & Rasmus Havelund & Anya Eyres & Sungjun Park & Youngsik Shin & Hye Jin Bae & Young Mo Sung & Lidija Matjacic & Yongsik Jung & Jungyeon Won & Woo Sung, 2023. "Direct identification of interfacial degradation in blue OLEDs using nanoscale chemical depth profiling," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43840-9
    DOI: 10.1038/s41467-023-43840-9
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    References listed on IDEAS

    as
    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    2. Yifan Zhang & Jaesang Lee & Stephen R. Forrest, 2014. "Tenfold increase in the lifetime of blue phosphorescent organic light-emitting diodes," Nature Communications, Nature, vol. 5(1), pages 1-7, December.
    3. Naoya Aizawa & Yong-Jin Pu & Michitake Watanabe & Takayuki Chiba & Kazushige Ideta & Naoki Toyota & Masahiro Igarashi & Yoshiyuki Suzuri & Hisahiro Sasabe & Junji Kido, 2014. "Solution-processed multilayer small-molecule light-emitting devices with high-efficiency white-light emission," Nature Communications, Nature, vol. 5(1), pages 1-7, December.
    4. Sinheui Kim & Hye Jin Bae & Sangho Park & Wook Kim & Joonghyuk Kim & Jong Soo Kim & Yongsik Jung & Soohwan Sul & Soo-Ghang Ihn & Changho Noh & Sunghan Kim & Youngmin You, 2018. "Degradation of blue-phosphorescent organic light-emitting devices involves exciton-induced generation of polaron pair within emitting layers," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    5. Maria Vasilopoulou & Abd. Rashid bin Mohd Yusoff & Matyas Daboczi & Julio Conforto & Anderson Emanuel Ximim Gavim & Wilson Jose Silva & Andreia Gerniski Macedo & Anastasia Soultati & George Pistolis &, 2021. "High efficiency blue organic light-emitting diodes with below-bandgap electroluminescence," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
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