Monolayer Hexagonal Boron Nitride: An Efficient Electron Blocking Layer in Organic Photovoltaics
Name
10.1002-adfm.202101238.pdf
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1.78 MB
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Author(s)
Tavakoli, Mohammad Mahdi
Park, Ji‐Hoon
Mwaura, Jeremiah
Saravanapavanantham, Mayuran
Bulović, Vladimir
Kong, Jing
Date Issued
April 22, 2021
Journal
Advanced Functional Materials
Publisher
Wiley
Citation
Tavakoli, M. M., Park, J.-H., Mwaura, J., Saravanapavanantham, M., Bulović, V., Kong, J., Monolayer Hexagonal Boron Nitride: An Efficient Electron Blocking Layer in Organic Photovoltaics. Adv. Funct. Mater. 2021, 31, 2101238
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Author's final manuscript
Abstract
In this study, monolayer hexagonal boron nitride (h-BN) grown via chemical vapor deposition (CVD) as an effective electron blocking layer (EBL) for the organic photovoltaics (OPVs) is proposed. Unexpectedly, it is found that h-BN can replace the commonly used hole transport layers (HTLs), i.e., molybdenum trioxide (MoO3) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) in an inverted device architecture. Here, a wet-transfer technique is employed and a single layer of h-BN on top of the PV2000:PC60BM blend is successfully placed. Analysis of the bandgap diagram shows that the monolayer h-BN makes smaller barrier for holes but significantly larger barrier for electrons. This makes the h-BN effective in blocking electrons while creating a possible path for the holes through tunneling to the electrode, due to the low energy barrier at the PV2000/h-BN interface. Using h-BN as an EBL, efficient inverted OPVs are achieved with an average solar-to-power conversion efficiency of 6.13%, which is comparable with that of reference devices based on MoO3 (7.3%) and PEDOT:PSS (7.6%) as HTLs. Interestingly, the devices with h-BN shows great light-soak stability. The study reveals that the monolayer h-BN grown by CVD could be an effective alternative EBL for the fabrication of efficient, lightweight, and stable OPVs.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1002/adfm.202101238
