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Cited by 336

The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.

Nonradiative Losses in Metal Halide Perovskites

Open access
Stranks, Samuel D.·2017·ACS Energy Letters

Abstract

Metal halide perovskites are generating enormous interest for their use in solar cells and light-emission applications. One property linking the high performance of these devices is a high radiative efficiency of the materials; indeed, a prerequisite for these devices to reach their theoretical efficiency limits is the elimination of all nonradiative decay. Despite remarkable progress, there exists substantial parasitic nonradiative recombination in thin films of the materials and when interfaced into devices, and the origin of these processes is still poorly understood. In this Perspective, I will highlight key observations of these parasitic pathways on both the macro- and microscale in thin films and full devices. I will summarize our current understanding of the origin of nonradiative decay, as well as existing solutions that hint at facile ways to remove these processes. I will also show how these nonradiative decay pathways are intimately related to ionic migration, leading to the tantalizing conclusion that eliminating one phenomenon could in turn remove the other, ultimately pushing devices to their theoretical limits.

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Crossref · 10.1021/acsenergylett.7b00239

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Metadata

Authors
Stranks, S. D.
Venue
ACS Energy Letters
Published
2017-06-06
Volume
2
Issue
7
Pages
1515-1525
ISSN
2380-8195 (ISSN-L)
OpenAlex
W2617238042
Cited by
336
References
106
FWCI
18.35
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Nonradiative Losses in Metal Halide Perovskites. https://app.cochat.ai/papers/10.1021/acsenergylett.7b00239
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Stranks, S. D. (2017). Nonradiative Losses in Metal Halide Perovskites. ACS Energy Letters. https://doi.org/10.1021/acsenergylett.7b00239

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.