Achieving 19.4% organic solar cell via an in situ formation of p-i-n structure with built-in interpenetrating network

  • Ying Zhang
  • , Wanyuan Deng
  • , Christopher E. Petoukhoff
  • , Xinxin Xia
  • , Yongwen Lang
  • , Hao Xia
  • , Hua Tang
  • , Hrisheekesh Thachoth Chandran
  • , Sudhi Mahadevan
  • , Kuan Liu
  • , Patrick W.K. Fong
  • , Yongmin Luo
  • , Jiaying Wu
  • , Sai Wing Tsang
  • , Frédéric Laquai
  • , Hongbin Wu
  • , Xinhui Lu
  • , Yang Yang
  • , Gang Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

114 Citations (Scopus)

Abstract

Vibrant research has demonstrated that the layer-by-layer (LBL) approach can achieve a preferable vertical microstructure; however, the lack of precise control over vertical composition and molecular organization remains. Herein, we demonstrated a guest polymer-tailored LBL (GPT-LBL) strategy to achieve the p-i-n microstructure constructed by in situ monitoring pre-aggregation behaviors of non-fullerene acceptors. This superior structure with built-in interpenetrating networks alleviates the trap density states and the energy loss, improves hole transfer dynamics, and balances the charge transport, thus maximizing open-circuit voltage (VOC), short-circuit current density (JSC), and fill factor (FF) simultaneously. Consequently, a highly efficient GPT-LBL organic solar cell (OSC) with a power conversion efficiency (PCE) of 19.41% (certified 19.0%) was achieved. Noticeably, the large-area (1.03 cm2) device for GPT-LBL OSCs yields a satisfactory PCE of 17.52% in open-air blade coating, which is one of the best values in green-solvent-processed OSCs. The insights for p-i-n structure will give implications for the device engineering and photo physics understanding, offering an effective way to enable efficient, stable, and scalable OSCs.

Original languageEnglish
Pages (from-to)509-526
Number of pages18
JournalJoule
Volume8
Issue number2
DOIs
Publication statusPublished - 21 Feb 2024

Keywords

  • eco-friendly OSCs
  • GPT-LBL
  • highly efficient
  • p-i-n structure
  • stable

ASJC Scopus subject areas

  • General Energy

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