Dynamical Disorder in the Mesophase Ferroelectric HdabcoClO<sub>4</sub>: A Machine-Learned Force Field Study

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 HdabcoClO<sub>4</sub> 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 phase transition coinciding with the orientational disorder of ClO<sub>4</sub> <sup>-</sup> and the onset of rotation of both Hdabco<sup>+</sup> and ClO<sub>4</sub> <sup>-</sup> 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.

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Publication Details

Journal
The Journal of Physical Chemistry C
Published
2024-12-18
DOI
https://doi.org/10.1021/acs.jpcc.4c06615
Citations
1
Primary Topic
Solid-state spectroscopy and crystallography
Type
article
Field-Weighted Citation Impact
0.12

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article

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

Kristian Berland, Georg K. H. Madsen, Jesús Carrete, Elin Dypvik Sødahl
1 citations
The Journal of Physical Chemistry C
Solid-state spectroscopy and crystallography
0.12
article

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

Kristian Berland, Georg K. H. Madsen, Jesús Carrete, Elin Dypvik Sødahl
article en
1 citations

Abstract

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 HdabcoClO<sub>4</sub> 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 phase transition coinciding with the orientational disorder of ClO<sub>4</sub> <sup>-</sup> and the onset of rotation of both Hdabco<sup>+</sup> and ClO<sub>4</sub> <sup>-</sup> 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.

The Journal of Physical Chemistry CVol. 129(1)
TU Wien (AT), Universidad de Zaragoza (ES), Instituto de Nanociencia y Materiales de Aragón (ES), Norwegian University of Life Sciences (NO)
European Commission, Norges Forskningsråd, Gobierno de Aragón, Agencia Estatal de Investigación
Openalex Percentile: Top 57%
Solid-state spectroscopy and crystallography
0.12
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