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Title: Structural and Chemical Features Giving Rise to Defect Tolerance of Binary Semiconductors

Journal Article · · Chemistry of Materials
ORCiD logo [1]; ORCiD logo [2];  [1];  [2]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States); Colorado School of Mines, Golden, CO (United States)

Defect tolerance, or the resilience of electronic transport properties of a crystalline material to the presence of defects, has emerged as a critical factor in the success of hybrid lead halide perovskites as photovoltaic absorbers. A key aspect of defect tolerance is the shallow character of dominant intrinsic defects. However, while qualitative heuristics to identify other defect-tolerant materials have been proposed, in particular, the presence of a partially oxidized ns2 cation such as Pb, no compelling comprehensive understanding of how these shallow defects arise has yet emerged. Using modern defect theory and defect calculations, we conduct a detailed investigation of the mechanisms and identify specific features related to the chemical composition and crystal structure that give rise to defect tolerance. We find that an ns2 cation is necessary but not sufficient to guarantee shallow cation vacancies in an s-p system, and that a compound's crystal structure can ensure shallow anion vacancies in a variety of ways. Specifically, the crystal site symmetry can enforce weak interactions between the orbitals that form the defect states, thus ensuring that those defect states are shallow. We substantiate our findings by computing defect formation energies in several known as well as hypothetical materials and conclude by discussing prospects for identifying semiconductors that satisfy these criteria.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1476979
Report Number(s):
NREL/JA-5K00-72569
Journal Information:
Chemistry of Materials, Vol. 30, Issue 16; ISSN 0897-4756
Publisher:
American Chemical Society (ACS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 26 works
Citation information provided by
Web of Science

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Cited By (4)

Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks journal May 2019
Electronic Structure and Optoelectronic Properties of Bismuth Oxyiodide Robust against Percent‐Level Iodine‐, Oxygen‐, and Bismuth‐Related Surface Defects journal March 2020
The complex defect chemistry of antimony selenide journal January 2019
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks preprint January 2018

Figures / Tables (7)


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