Compression-Induced Lattice Tilting Quenches Ion Migration at Metal Halide Perovskite Grain Boundaries: A Machine Learning Molecular Dynamics Study

Ion migration at grain boundaries (GBs) is a key issue leading to the performance degradation of metal halide perovskites (MHPs). Given the weak lattice interactions, the properties of MHPs are highly sensitive to external strain, which is inevitable in practical applications. Nevertheless, a fundamental understanding of the GB behavior under strain is still lacking. Using machine learning molecular dynamics, we demonstrate that uniaxial strain dictates both structural variation and ion migration at a CsPbBr<sub>3</sub> GB. Tensile and strain-free conditions lead to grain sliding along the boundaries, creating versatile migration channels for all species. In contrast, compressive strain triggers lattice tilting within each grain and generates amorphous GB structures, blocking migration channels and ultimately quenching ion mobility. Our work elucidates the pivotal role of strain in determining the performance of MHPs and establishes compressive strain engineering as a promising strategy for enhancing their stability.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2025-12-12
DOI
https://doi.org/10.1021/acs.jpclett.5c03637
Primary Topic
Perovskite Materials and Applications
Type
article
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article

Compression-Induced Lattice Tilting Quenches Ion Migration at Metal Halide Perovskite Grain Boundaries: A Machine Learning Molecular Dynamics Study

Huanping Zhou, Emir S. Amirov, Dongyu Liu, Andrey S. Vasenko et al.
The Journal of Physical Chemistry Letters
Perovskite Materials and Applications
article

Compression-Induced Lattice Tilting Quenches Ion Migration at Metal Halide Perovskite Grain Boundaries: A Machine Learning Molecular Dynamics Study

Huanping Zhou, Emir S. Amirov, Dongyu Liu, Andrey S. Vasenko, Oleg V. Prezhdo, Pavel A. Troshin, M A Bubnova, А. Е. Абрамешин, Mikhail R. Samatov, Weibin Chu, Alexei Kramarenko
article en

Abstract

Ion migration at grain boundaries (GBs) is a key issue leading to the performance degradation of metal halide perovskites (MHPs). Given the weak lattice interactions, the properties of MHPs are highly sensitive to external strain, which is inevitable in practical applications. Nevertheless, a fundamental understanding of the GB behavior under strain is still lacking. Using machine learning molecular dynamics, we demonstrate that uniaxial strain dictates both structural variation and ion migration at a CsPbBr<sub>3</sub> GB. Tensile and strain-free conditions lead to grain sliding along the boundaries, creating versatile migration channels for all species. In contrast, compressive strain triggers lattice tilting within each grain and generates amorphous GB structures, blocking migration channels and ultimately quenching ion mobility. Our work elucidates the pivotal role of strain in determining the performance of MHPs and establishes compressive strain engineering as a promising strategy for enhancing their stability.

The Journal of Physical Chemistry LettersVol. 16(51)
National Research University Higher School of Economics (RU), University of New Mexico (US), Peking University (CN), Fudan University (CN), Ministry of Education (IR), Institute of Problems of Chemical Physics (RU), Computational Physics (United States) (US), Donostia International Physics Center (ES)
Openalex Percentile: Top 60%
Perovskite Materials and Applications
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