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Title: Investigating the Effects of Chemical Gradients on Performance and Reliability within Perovskite Solar Cells with TOF-SIMS

Abstract

Time-of-flight secondary-ion mass spectrometry (TOF-SIMS), a powerful analytical technique sensitive to all components of perovskite solar cell (PSC) materials, can differentiate between the various organic species within a PSC absorber or a complete device stack. The ability to probe chemical gradients through the depth of a device (both organic and inorganic), with down to 100 nm lateral resolution, can lead to unique insights into the relationships between chemistry in the absorber bulk, at grain boundaries, and at interfaces as well as how they relate to changes in performance and/or stability. In this review, the technique is described; then, from the literature, several examples of how TOF-SIMS have been used to provide unique insight into PSC absorbers and devices are covered. Finally, the common artifacts that can be introduced if the data are improperly collected, as well as methods to mitigate these artifacts are discussed.

Authors:
ORCiD logo [1];  [2];  [1]; ORCiD logo [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. University at Illinois at Urbana-Champaign
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1603928
Report Number(s):
NREL/JA-5K00-75344
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
Advanced Energy Materials
Additional Journal Information:
Journal Name: Advanced Energy Materials
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 36 MATERIALS SCIENCE; degradation; performance; perovskite solar cells; time-of-flight secondary-ion mass spectrometry

Citation Formats

Harvey, Steven P, Messinger, Jonah, Zhu, Kai, Luther, Joseph M, and Berry, Joseph J. Investigating the Effects of Chemical Gradients on Performance and Reliability within Perovskite Solar Cells with TOF-SIMS. United States: N. p., 2020. Web. doi:10.1002/aenm.201903674.
Harvey, Steven P, Messinger, Jonah, Zhu, Kai, Luther, Joseph M, & Berry, Joseph J. Investigating the Effects of Chemical Gradients on Performance and Reliability within Perovskite Solar Cells with TOF-SIMS. United States. doi:10.1002/aenm.201903674.
Harvey, Steven P, Messinger, Jonah, Zhu, Kai, Luther, Joseph M, and Berry, Joseph J. Mon . "Investigating the Effects of Chemical Gradients on Performance and Reliability within Perovskite Solar Cells with TOF-SIMS". United States. doi:10.1002/aenm.201903674.
@article{osti_1603928,
title = {Investigating the Effects of Chemical Gradients on Performance and Reliability within Perovskite Solar Cells with TOF-SIMS},
author = {Harvey, Steven P and Messinger, Jonah and Zhu, Kai and Luther, Joseph M and Berry, Joseph J},
abstractNote = {Time-of-flight secondary-ion mass spectrometry (TOF-SIMS), a powerful analytical technique sensitive to all components of perovskite solar cell (PSC) materials, can differentiate between the various organic species within a PSC absorber or a complete device stack. The ability to probe chemical gradients through the depth of a device (both organic and inorganic), with down to 100 nm lateral resolution, can lead to unique insights into the relationships between chemistry in the absorber bulk, at grain boundaries, and at interfaces as well as how they relate to changes in performance and/or stability. In this review, the technique is described; then, from the literature, several examples of how TOF-SIMS have been used to provide unique insight into PSC absorbers and devices are covered. Finally, the common artifacts that can be introduced if the data are improperly collected, as well as methods to mitigate these artifacts are discussed.},
doi = {10.1002/aenm.201903674},
journal = {Advanced Energy Materials},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {2}
}

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