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Electrofreezing of liquid water at ambient conditions

Author

Listed:
  • Giuseppe Cassone

    (National Research Council)

  • Fausto Martelli

    (IBM Research Europe
    University of Manchester)

Abstract

Water is routinely exposed to external electric fields. Whether, for example, at physiological conditions, in contact with biological systems, or at the interface of polar surfaces in countless technological settings, water responds to fields on the order of a few V Å−1 in a manner that is under intense investigation. Dating back to the 19th century, the possibility of solidifying water upon applying electric fields – a process known as electrofreezing – is an alluring promise that has canalized major efforts since, with uncertain outcomes. Here, we perform long (up to 500 ps per field strength) ab initio molecular dynamics simulations of water at ambient conditions under external electric fields. We show that fields of 0.10 − 0.15 V Å−1 induce electrofreezing to a ferroelectric amorphous phase which we term f-GW (ferroelectric glassy water). The transition occurs after ~ 150 ps for a field of 0.15 V Å−1 and after ~ 200 ps for a field of 0.10 V Å−1 and is signaled by a structural and dynamic arrest and the suppression of the fluctuations of the hydrogen bond network. Our work reports evidence of electrofreezing of bulk liquid water at ambient conditions and therefore impacts several fields, from fundamental chemical physics to biology and catalysis.

Suggested Citation

  • Giuseppe Cassone & Fausto Martelli, 2024. "Electrofreezing of liquid water at ambient conditions," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46131-z
    DOI: 10.1038/s41467-024-46131-z
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    References listed on IDEAS

    as
    1. Yaolong Zhang & Bin Jiang, 2023. "Universal machine learning for the response of atomistic systems to external fields," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Pablo G. Debenedetti & Frank H. Stillinger, 2001. "Supercooled liquids and the glass transition," Nature, Nature, vol. 410(6825), pages 259-267, March.
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    Cited by:

    1. Kit Joll & Philipp Schienbein & Kevin M. Rosso & Jochen Blumberger, 2024. "Machine learning the electric field response of condensed phase systems using perturbed neural network potentials," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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