Revealing the Low Temperature Phase of FAPbI$_3$ using A Machine-Learned Potential

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Dutta, Sangita, Fransson, Erik, Hainer, Tobias, Gallant, Benjamin M., Kubicki, Dominik J., Erhart, Paul, Wiktor, Julia
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866914014809817088
author Dutta, Sangita
Fransson, Erik
Hainer, Tobias
Gallant, Benjamin M.
Kubicki, Dominik J.
Erhart, Paul
Wiktor, Julia
author_facet Dutta, Sangita
Fransson, Erik
Hainer, Tobias
Gallant, Benjamin M.
Kubicki, Dominik J.
Erhart, Paul
Wiktor, Julia
contents FAPbI$_3$ is a material of interest for its potential in solar cell applications, driven by its remarkable optoelectronic properties. However, the low-temperature phase of FAPbI$_3$ remains poorly understood, with open questions surrounding its crystal structure, octahedral tilting, and the arrangement of formamidinium (FA) cations. Using our trained machine-learned potential in combination with large-scale molecular dynamics simulations, we provide a detailed investigation of this phase, uncovering its structural characteristics and dynamical behavior. Our analysis reveals the octahedral tilt pattern and sheds light on the rotational dynamics of FA cations in the low temperature phase. Strikingly, we find that the FA cations become frozen in a metastable configuration, unable to reach the thermodynamic ground state. By comparing our simulated results with experimental nuclear magnetic resonance (NMR) and inelastic neutron scattering (INS) spectra, we demonstrate good agreement, further validating our findings. This phenomenon mirrors experimental observations and offers a compelling explanation for the experimental challenges in accessing the true ground state. These findings provide critical insights into the fundamental physics of FAPbI$_3$ and its low-temperature behavior, advancing our understanding of this technologically important material.
format Preprint
id arxiv_https___arxiv_org_abs_2503_23974
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Revealing the Low Temperature Phase of FAPbI$_3$ using A Machine-Learned Potential
Dutta, Sangita
Fransson, Erik
Hainer, Tobias
Gallant, Benjamin M.
Kubicki, Dominik J.
Erhart, Paul
Wiktor, Julia
Materials Science
FAPbI$_3$ is a material of interest for its potential in solar cell applications, driven by its remarkable optoelectronic properties. However, the low-temperature phase of FAPbI$_3$ remains poorly understood, with open questions surrounding its crystal structure, octahedral tilting, and the arrangement of formamidinium (FA) cations. Using our trained machine-learned potential in combination with large-scale molecular dynamics simulations, we provide a detailed investigation of this phase, uncovering its structural characteristics and dynamical behavior. Our analysis reveals the octahedral tilt pattern and sheds light on the rotational dynamics of FA cations in the low temperature phase. Strikingly, we find that the FA cations become frozen in a metastable configuration, unable to reach the thermodynamic ground state. By comparing our simulated results with experimental nuclear magnetic resonance (NMR) and inelastic neutron scattering (INS) spectra, we demonstrate good agreement, further validating our findings. This phenomenon mirrors experimental observations and offers a compelling explanation for the experimental challenges in accessing the true ground state. These findings provide critical insights into the fundamental physics of FAPbI$_3$ and its low-temperature behavior, advancing our understanding of this technologically important material.
title Revealing the Low Temperature Phase of FAPbI$_3$ using A Machine-Learned Potential
topic Materials Science
url https://arxiv.org/abs/2503.23974