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A statistical mechanical model of supercooled water based on minimal clusters of correlated molecules.
Daidone, Isabella; Foffi, Riccardo; Amadei, Andrea; Zanetti-Polzi, Laura.
Afiliação
  • Daidone I; Department of Physical and Chemical Sciences, University of L'Aquila, via Vetoio (Coppito 1), L'Aquila 67010, Italy.
  • Foffi R; Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, ETH Zürich, Laura-Hezner-Weg 7, 8093 Zürich, Switzerland.
  • Amadei A; Department of Chemical and Technological Sciences, University of Rome "Tor Vergata," Via della Ricerca Scientifica, I-00185 Rome, Italy.
  • Zanetti-Polzi L; Center S3, CNR-Institute of Nanoscience, Via Campi 213/A, 41125 Modena, Italy.
J Chem Phys ; 159(9)2023 Sep 07.
Article em En | MEDLINE | ID: mdl-37655770
ABSTRACT
In this paper, we apply a theoretical model for fluid state thermodynamics to investigate simulated water in supercooled conditions. This model, which we recently proposed and applied to sub- and super-critical fluid water [Zanetti-Polzi et al., J. Chem. Phys. 156(4), 44506 (2022)], is based on a combination of the moment-generating functions of the enthalpy and volume fluctuations as provided by two gamma distributions and provides the free energy of the system as well as other relevant thermodynamic quantities. The application we make here provides a thermodynamic description of supercooled water fully consistent with that expected by crossing the liquid-liquid Widom line, indicating the presence of two distinct liquid states. In particular, the present model accurately reproduces the Widom line temperatures estimated with other two-state models and well describes the heat capacity anomalies. Differently from previous models, according to our description, a cluster of molecules that extends beyond the first hydration shell is necessary to discriminate between the statistical fluctuation regimes typical of the two liquid states.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article