Materials Processing Routes to Trap-Free Halide Perovskites

Andrei Buin, Patrick Pietsch, Jixian Xu, Oleksandr Voznyy, Alexander H. Ip, Riccardo Comin, Edward H. Sargent

Research output: Contribution to journalArticlepeer-review

584 Scopus citations


© 2014 American Chemical Society. Photovoltaic devices based on lead iodide perovskite films have seen rapid advancements, recently achieving an impressive 17.9% certified solar power conversion efficiency. Reports have consistently emphasized that the specific choice of growth conditions and chemical precursors is central to achieving superior performance from these materials; yet the roles and mechanisms underlying the selection of materials processing route is poorly understood. Here we show that films grown under iodine-rich conditions are prone to a high density of deep electronic traps (recombination centers), while the use of a chloride precursor avoids the formation of key defects (Pb atom substituted by I) responsible for short diffusion lengths and poor photovoltaic performance. Furthermore, the lowest-energy surfaces of perovskite crystals are found to be entirely trap-free, preserving both electron and hole delocalization to a remarkable degree, helping to account for explaining the success of polycrystalline perovskite films. We construct perovskite films from I-poor conditions using a lead acetate precursor, and our measurement of a long (600 ± 40 nm) diffusion length confirms this new picture of the importance of growth conditions.
Original languageEnglish (US)
Pages (from-to)6281-6286
Number of pages6
JournalNano Letters
Issue number11
StatePublished - Oct 13 2014
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-11-009-21
Acknowledgements: This publication is based in part on work supported by Award KUS-11-009-21, made by King Abdullah University of Science and Technology (KAUST), by the Ontario Research Fund Research Excellence Program, and by the Natural Sciences and Engineering Research Council (NSERC) of Canada. Computations were performed on the Southern Ontario Smart Computing Innovation Platform (SOSCIP) Blue Gene/Q supercomputer located at the University of Toronto's SciNet50 HPC facility. The SOS CIF multiuniversity/industry consortium is funded by the Ontario Government and the Federal SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund-Research Excellence; and the University of Toronto. We thank Dr. Pongsakorn Kanjanaboos for AFM images and Dr. Zhijun Ning and Dr. Mingjian Yuan for the fruitful discussions.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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