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Quantitative investigation of the two-state picture for water in the normal liquid and the supercooled regime

pmid: 21573766
Several evidences have helped to establish the two-state nature of liquid water. Thus, within the normal liquid and supercooled regimes water has been shown to consist of a mixture of well-structured, low-density molecules and unstructured, high-density ones. However, quantitative analyses have faced the burden of unambiguously determining both the presence and the fraction of each kind of water "species". A recent approach by combining a local structure index with potential-energy minimisations allows us to overcome this difficulty. Thus, in this work we extend such study and employ it to quantitatively determine the fraction of structured molecules as a function of temperature for different densities. This enables us to validate predictions of two-state models.
- National Research Council Italy
- Sapienza University of Rome Italy
- Roma Tre University Italy
- Universidad Nacional del Sur Argentina
- Universidad Nacional del Sur Argentina
DYNAMICS, GLASS-TRANSITION, Biophysics, Water, Hydrogen Bonding, Cold Temperature, Solutions, Models, Chemical, PHASE-TRANSITION, Solvents, TEMPERATURE, ENERGY LANDSCAPE
DYNAMICS, GLASS-TRANSITION, Biophysics, Water, Hydrogen Bonding, Cold Temperature, Solutions, Models, Chemical, PHASE-TRANSITION, Solvents, TEMPERATURE, ENERGY LANDSCAPE
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).55 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
