Dynamical Disorder in the Mesophase Ferroelectric HdabcoClO4: A Machine-Learned Force Field Study

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Main Authors: Sødahl, Elin Dypvik, Carrete, Jesús, Madsen, Georg K. H., Berland, Kristian
Format: Preprint
Published: 2024
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_version_ 1866917810414813184
author Sødahl, Elin Dypvik
Carrete, Jesús
Madsen, Georg K. H.
Berland, Kristian
author_facet Sødahl, Elin Dypvik
Carrete, Jesús
Madsen, Georg K. H.
Berland, Kristian
contents Hybrid molecular ferroelectrics with orientationally disordered mesophases offer significant promise as lead-free alternatives to traditional inorganic ferroelectrics owing to properties such as room temperature ferroelectricity, low-energy synthesis, malleability, and potential for multiaxial polarization. The ferroelectric molecular salt HdabcoClO4 is of particular interest due to its ultrafast ferroelectric room-temperature switching. However, so far, there is limited understanding of the nature of dynamical disorder arising in these compounds. Here, we employ the neural network NeuralIL to train a machine-learned force field (MLFF) with training data generated using density functional theory. The resulting MLFF-MD simulations exhibit phase transitions and thermal expansion in line with earlier reported experimental results, for both a low-temperature phasetransition coinciding with the orientational disorder of ClO4- molecules and the onset of rotation of Hdabco+ and ClO4- molecules in a high-temperature phase transition. We also find proton transfer even in the low-temperature phase, which increases with temperature and leads to associated proton disorder as well as the onset of disorder in the direction of the hydrogen-bonded chains.
format Preprint
id arxiv_https___arxiv_org_abs_2410_15746
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dynamical Disorder in the Mesophase Ferroelectric HdabcoClO4: A Machine-Learned Force Field Study
Sødahl, Elin Dypvik
Carrete, Jesús
Madsen, Georg K. H.
Berland, Kristian
Materials Science
Hybrid molecular ferroelectrics with orientationally disordered mesophases offer significant promise as lead-free alternatives to traditional inorganic ferroelectrics owing to properties such as room temperature ferroelectricity, low-energy synthesis, malleability, and potential for multiaxial polarization. The ferroelectric molecular salt HdabcoClO4 is of particular interest due to its ultrafast ferroelectric room-temperature switching. However, so far, there is limited understanding of the nature of dynamical disorder arising in these compounds. Here, we employ the neural network NeuralIL to train a machine-learned force field (MLFF) with training data generated using density functional theory. The resulting MLFF-MD simulations exhibit phase transitions and thermal expansion in line with earlier reported experimental results, for both a low-temperature phasetransition coinciding with the orientational disorder of ClO4- molecules and the onset of rotation of Hdabco+ and ClO4- molecules in a high-temperature phase transition. We also find proton transfer even in the low-temperature phase, which increases with temperature and leads to associated proton disorder as well as the onset of disorder in the direction of the hydrogen-bonded chains.
title Dynamical Disorder in the Mesophase Ferroelectric HdabcoClO4: A Machine-Learned Force Field Study
topic Materials Science
url https://arxiv.org/abs/2410.15746