skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide

Abstract

Impurities in semiconductors, for example, lead-based hybrid perovskites, have a major influence on their performance as photovoltaic (PV) light absorbers. While impurities could create harmful trap states that lead to nonradiative recombination of charge carriers and adversely affect PV efficiency, they could also potentially increase absorption via midgap energy levels that act as stepping stones for subgap photons or introduce charge carriers via doping. To unearth trends in impurity energy states, we use first principles density functional theory calculations to extensively study partial substitution of Pb in methylammonium lead bromide (MAPbBr 3), a representative lead-halide perovskite. Investigation of the density of states and energy levels related to the transition of the substitutional defect from one charge state to another reveals that several elements create midgap energy states in MAPbBr 3. We machine learned trends and design rules from the computational data and discovered that a few easily computed properties of the bromide compounds of any element can be used to predict the energetics and energy levels of the substitutional defect related to that element. The calculated Fermi level-dependent defect formation energies lead to the observation that substitution by transition metals, Zr, Hf, Nb, and Sc, and group V element Sbmore » can shift the equilibrium Fermi level and change the perovskite conductivity, as determined by the dominant intrinsic point defects. Finally, metal-substituted MAPbBr 3 compounds of Bi, Sc, Ni, and Zr were experimentally investigated, and while there was an improvement in the thin-film morphology and an enhancement in charge carrier lifetimes, no clear evidence of subgap absorption features owing to the substituent being incorporated in the MAPbBr 3 lattice could be seen.« less

Authors:
ORCiD logo [1];  [2];  [3];  [3]; ORCiD logo [1]; ORCiD logo [3]; ORCiD logo [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States). Center for Nanoscale Materials
  2. Imperial College London, London (United Kingdom)
  3. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1542595
Grant/Contract Number:  
AC02-06CH11357; AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Chemistry of Materials
Additional Journal Information:
Journal Volume: 31; Journal Issue: 10; Journal ID: ISSN 0897-4756
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Mannodi-Kanakkithodi, Arun, Park, Ji-Sang, Jeon, Nari, Cao, Duyen H., Gosztola, David J., Martinson, Alex B. F., and Chan, Maria K. Y. Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide. United States: N. p., 2019. Web. doi:10.1021/acs.chemmater.8b04017.
Mannodi-Kanakkithodi, Arun, Park, Ji-Sang, Jeon, Nari, Cao, Duyen H., Gosztola, David J., Martinson, Alex B. F., & Chan, Maria K. Y. Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide. United States. doi:10.1021/acs.chemmater.8b04017.
Mannodi-Kanakkithodi, Arun, Park, Ji-Sang, Jeon, Nari, Cao, Duyen H., Gosztola, David J., Martinson, Alex B. F., and Chan, Maria K. Y. Tue . "Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide". United States. doi:10.1021/acs.chemmater.8b04017. https://www.osti.gov/servlets/purl/1542595.
@article{osti_1542595,
title = {Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide},
author = {Mannodi-Kanakkithodi, Arun and Park, Ji-Sang and Jeon, Nari and Cao, Duyen H. and Gosztola, David J. and Martinson, Alex B. F. and Chan, Maria K. Y.},
abstractNote = {Impurities in semiconductors, for example, lead-based hybrid perovskites, have a major influence on their performance as photovoltaic (PV) light absorbers. While impurities could create harmful trap states that lead to nonradiative recombination of charge carriers and adversely affect PV efficiency, they could also potentially increase absorption via midgap energy levels that act as stepping stones for subgap photons or introduce charge carriers via doping. To unearth trends in impurity energy states, we use first principles density functional theory calculations to extensively study partial substitution of Pb in methylammonium lead bromide (MAPbBr3), a representative lead-halide perovskite. Investigation of the density of states and energy levels related to the transition of the substitutional defect from one charge state to another reveals that several elements create midgap energy states in MAPbBr3. We machine learned trends and design rules from the computational data and discovered that a few easily computed properties of the bromide compounds of any element can be used to predict the energetics and energy levels of the substitutional defect related to that element. The calculated Fermi level-dependent defect formation energies lead to the observation that substitution by transition metals, Zr, Hf, Nb, and Sc, and group V element Sb can shift the equilibrium Fermi level and change the perovskite conductivity, as determined by the dominant intrinsic point defects. Finally, metal-substituted MAPbBr3 compounds of Bi, Sc, Ni, and Zr were experimentally investigated, and while there was an improvement in the thin-film morphology and an enhancement in charge carrier lifetimes, no clear evidence of subgap absorption features owing to the substituent being incorporated in the MAPbBr3 lattice could be seen.},
doi = {10.1021/acs.chemmater.8b04017},
journal = {Chemistry of Materials},
issn = {0897-4756},
number = 10,
volume = 31,
place = {United States},
year = {2019},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

Save / Share:

Works referencing / citing this record:

Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides
journal, April 2020

  • Mannodi-Kanakkithodi, Arun; Toriyama, Michael Y.; Sen, Fatih G.
  • npj Computational Materials, Vol. 6, Issue 1
  • DOI: 10.1038/s41524-020-0296-7