Computational Study of Structural and Electronic Properties of Lead-Free CsMI3 Perovskites (M = Ge, Sn, Pb, Mg, Ca, Sr, and Ba)

Debmalya Ray, Catherine Clark, Hung Q. Pham, Joshua Borycz, Russell J. Holmes, Eray S. Aydil, Laura Gagliardi

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

Electronic structure calculations of five crystallography-imitated structures of CsMI3 perovskites with M = Ge, Sn, Pb, Mg, Ca, Sr, and Ba were performed. The formation energy of different perovskite phases, their relative stability, and structural and electronic properties were explored. The sensitivity of the calculations to the choice of the density functional was investigated, and the predictions were compared with experimental results. The outcome of this study is that Mg and Ba perovskites are unlikely to form in the cubic, tetragonal, or orthorhombic phases because they have positive formation energies. Although Ca and Sr perovskites have negative formation energies with respect to the metal-iodide precursors, they exhibit wide band gaps and high hygroscopicity, making these unlikely candidates for applications in photovoltaic devices. Our results suggest that the performance of a local density functional with a nonseparable gradient approximation (NGA) is similar to that of hybrid functionals in terms of band gap predictions, when M in CsMI3 is a p-block element (Pb, Sn, and Ge). However, local density functionals with NGA predictions for the band gap are similar to other local functionals with a generalized gradient approximation (PBE, PBEsol, and PBE-D3) and are worse than those of HSE06, when M is an s-block element (Mg, Ca, Sr, and Ba).

Original languageEnglish
Pages (from-to)7838-7848
Number of pages11
JournalJournal of Physical Chemistry C
Volume122
Issue number14
DOIs
StatePublished - Apr 12 2018
Externally publishedYes

Funding

This work was supported primarily by the National Science Foundation through the University of Minnesota MRSEC under Award Number DMR-1420013 and the iSuperseed program. Parts of this work were carried out in the College of Science and Engineering Characterization Facility, University of Minnesota, which has received capital equipment funding from the NSF through the UMN MRSEC program under Award Number DMR-1420013. We would also like to thank the Minnesota Supercomputing Institute for computing resources.

FundersFunder number
UMN MRSEC
University of Minnesota MRSECDMR-1420013
National Science Foundation
University of Minnesota
Norsk Sykepleierforbund
National Science Foundation

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