Literature DB >> 29298058

Is Water at the Graphite Interface Vapor-like or Ice-like?

Yuqing Qiu1, Laura Lupi1, Valeria Molinero1.   

Abstract

Graphitic surfaces are the main component of soot, a major constituent of atmospheric aerosols. Experiments indicate that soots of different origins display a wide range of abilities to heterogeneously nucleate ice. The ability of pure graphite to nucleate ice in experiments, however, seems to be almost negligible. Nevertheless, molecular simulations with the monatomic water model mW with water-carbon interactions parameterized to reproduce the experimental contact angle of water on graphite predict that pure graphite nucleates ice. According to classical nucleation theory, the ability of a surface to nucleate ice is controlled by the binding free energy between ice immersed in liquid water and the surface. To establish whether the discrepancy in freezing efficiencies of graphite in mW simulations and experiments arises from the coarse resolution of the model or can be fixed by reparameterization, it is important to elucidate the contributions of the water-graphite, water-ice, and ice-water interfaces to the free energy, enthalpy, and entropy of binding for both water and the model. Here we use thermodynamic analysis and free energy calculations to determine these interfacial properties. We demonstrate that liquid water at the graphite interface is not ice-like or vapor-like: it has similar free energy, entropy, and enthalpy as water in the bulk. The thermodynamics of the water-graphite interface is well reproduced by the mW model. We find that the entropy of binding between graphite and ice is positive and dominated, in both experiments and simulations, by the favorable entropy of reducing the ice-water interface. Our analysis indicates that the discrepancy in freezing efficiencies of graphite in experiments and the simulations with mW arises from the inability of the model to simultaneously reproduce the contact angle of liquid water on graphite and the free energy of the ice-graphite interface. This transferability issue is intrinsic to the resolution of the model, and arises from its lack of rotational degrees of freedom.

Entities:  

Year:  2018        PMID: 29298058     DOI: 10.1021/acs.jpcb.7b11476

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  2 in total

1.  Homogeneous ice nucleation in an ab initio machine-learning model of water.

Authors:  Pablo M Piaggi; Jack Weis; Athanassios Z Panagiotopoulos; Pablo G Debenedetti; Roberto Car
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-08       Impact factor: 12.779

2.  Machine learning coarse grained models for water.

Authors:  Henry Chan; Mathew J Cherukara; Badri Narayanan; Troy D Loeffler; Chris Benmore; Stephen K Gray; Subramanian K R S Sankaranarayanan
Journal:  Nat Commun       Date:  2019-01-22       Impact factor: 14.919

  2 in total

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