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Evidence of ferroelectric features in low-density supercooled water from ab initio deep neural-network simulations.
Malosso, Cesare; Manko, Natalia; Izzo, Maria Grazia; Baroni, Stefano; Hassanali, Ali.
Afiliación
  • Malosso C; Scuola Internazionale Superiore di Studi Avanzati, Trieste 34136, Italy.
  • Manko N; Condensed Matter and Statistical Physics (CMSP), The Abdus Salam Centre for Theoretical Physics, Trieste 34151, Italy.
  • Izzo MG; Scuola Internazionale Superiore di Studi Avanzati, Trieste 34136, Italy.
  • Baroni S; Scuola Internazionale Superiore di Studi Avanzati, Trieste 34136, Italy.
  • Hassanali A; Consiglio Nazionale delle Ricerche-Istituto Officina dei Materiali, Scuola Internazionale Superiore di Studi Avanzati Unit, Trieste 34136, Italy.
Proc Natl Acad Sci U S A ; 121(32): e2407295121, 2024 Aug 06.
Article en En | MEDLINE | ID: mdl-39083416
ABSTRACT
Over the last decade, an increasing body of evidence has emerged, supporting the existence of a metastable liquid-liquid critical point in supercooled water whereby two distinct liquid phases of different densities coexist. Analyzing long molecular dynamics simulations performed using deep neural-network force fields trained to accurate quantum mechanical data, we demonstrate that the low-density liquid phase displays a strong propensity toward spontaneous polarization, as witnessed by large and long-lived collective dipole fluctuations. Our findings suggest that the dynamical stability of the low-density phase, and hence the transition from high-density to low-density liquid, is triggered by a collective process involving an accumulation of rotational angular jumps, which could ignite large dipole fluctuations. This dynamical transition involves subtle changes in the electronic polarizability of water molecules which affects their rotational mobility within the two phases. These findings hold the potential for catalyzing activity in the search for dielectric-based probes of the putative second critical point.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article País de afiliación: Italia