From Lattice Fluctuations to Ion Migration: The Dynamics of Halide Perovskites from Machine Learning Potential
Shuxia Tao a
a Intelligent Materials Theory, Department of Applied Physics, Eindhoven University of Technology, The Netherlands
Proceedings of MATSUS Fall 2026 Conference (MATSUSFall26)
B1 Fundamentals and Emerging Phenomena in Halide Perovskites
Palma, Spain, 2026 October 26th - 30th
Organizers: Sascha Feldmann, Paulina Plochocka and Alexander Urban
Invited Speaker, Shuxia Tao, presentation 022
Publication date: 22nd July 2026

Metal halide perovskites are highly dynamic materials in which structural fluctuations, defects, and electronic excitations are strongly coupled across a broad range of length and time scales. These dynamic processes govern key properties relevant to photovoltaics, light emission, and radiation detection, yet many of the underlying atomistic mechanisms remain poorly understood.

In this talk, I will present our recent efforts to understand the dynamic behavior of halide perovskites using atomistic simulations spanning multiple scales. Starting from lattice vibrations and structural phase transitions, I will discuss how local distortions and dynamic disorder influence material properties and give rise to emerging phenomena such as chiral phonons and temperature-dependent chirality. I will then address the role of charged defects, polarons, and ion migration, highlighting how their interactions with the dynamic lattice affect transport, stability, and performance.

Many of these processes occur on timescales that are inaccessible to conventional simulations. By combining machine-learning interatomic potentials with enhanced-sampling and rare-event techniques, we can access slow activated processes such as low-temperature ion migration, crystal growth, and degradation pathways while retaining near first-principles accuracy.

Together, these studies provide a unified picture of perovskite dynamics, linking ultrafast lattice motions, defect physics, and long-timescale structural evolution. The insights gained help explain the unique properties of halide perovskites and provide a foundation for the rational design of next-generation functional materials.

References: 

1. Tyagi, V.; Pols, M.; Brocks, G.; Tao, S. Tracing Ion Migration in Halide Perovskites with Machine-Learned Force Fields. J. Phys. Chem. Lett. 2025, 16, 5153–5159.

2. Tyagi, V.; Brocks, G.; Tao, S. A Unified Microscopic Picture of Cation and Anion Migration in MAPbI₃. arXiv:2605.02685 (2026).

3. Tyagi, V.; Pols, M.; Brocks, G.; Tao, S. Halide Diffusion in Mixed-Halide Perovskites and Heterojunctions. Chem. Mater. 2026, 38, 4703–4711.

4. Pols, M.; Brocks, G.; Calero, S.; Tao, S. Temperature-Dependent Chirality in Halide Perovskites. J. Phys. Chem. Lett. 2024, 15, 8057–8064.

5. Pols, M.; Brocks, G.; Calero, S.; Tao, S. Chiral Phonons in 2D Halide Perovskites. Nano Lett. 2025, 25, 10003–10009.

6. Wilke, K.; Tyagi, V.; van Erp, T. S.; Tao, S. Bridging Timescales in CsPbBr₃: Low-Temperature Ion Migration from Machine-Learning Potentials and Path Sampling. Manuscript in preparation.

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