Surface premelting of water ice

Slater, Ben; Michaelides, Angelos

doi:10.1038/s41570-019-0080-8

Cited by 198 publications

(213 citation statements)

References 192 publications

(247 reference statements)

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“…The authors would like to thank A. Michaelides and B. Slater for providing us a copy of Ref. [46] prior to publication, as well as Eva G. Noya for helpful discussions. We also wish to thank the Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional (FEDER) for research grant FIS-89361-C3-2-P. P.L.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Structure and fluctuations of the premelted liquid film of ice at the triple point

et al. 2019

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In this paper we study the structure of the ice/vapor interface in the neighborhood of the triple point for the TIP4P/2005 model. We probe the fluctuations of the ice/film and film/vapor surfaces that separate the liquid film from the coexisting bulk phases at basal, primary prismatic and secondary prismatic planes. The results are interpreted using a coupled sine Gordon plus Interface Hamiltonian model. At large length-scales, the two bounding surfaces are correlated and behave as a single complex ice/vapor interface. For small length, on the contrary, the ice/film and film/vapor surfaces behave very much like independent ice/water and water/vapor interfaces.The study suggests that the basal facet of the TIP4P/2005 model is smooth, the prismatic facet is close to a roughening transition, and the secondary prismatic facet is rough. For the faceted basal face, our fluctuation analysis allows us to estimate the step free energy in good agreement with experiment. Our results allow for a quantitative characterization of the extent to which the adsorbed quasi-liquid layer behaves as water, and explains experimental observations which reveal similar activation energies for crystals grown in bulk vapor or bulk water.

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Section: Acknowledgmentsmentioning

confidence: 99%

Structure and fluctuations of the premelted liquid film of ice at the triple point

et al. 2019

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“…In spite of more than a century of investigation, the very origin of this puzzling property is not settled yet and remains highly debated. Since the seminal work of Faraday [6], a consensus has been reached on the existence of a liquid-like layer wetting the ice surface [7][8][9][10][11][12], with a thickness varying between 1 and 100 nm depending on the temperature [13], although the underlying mechanism of formation remains debated [14,15]. Now, under sliding the fate of the interfacial film remains largely unknown [16].…”

Section: Introductionmentioning

confidence: 99%

Nanorheology of Interfacial Water during Ice Gliding

et al. 2019

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The slipperiness of ice is an everyday-life phenomenon which, surprisingly, remains controversial despite a long scientific history. The very small friction measured on ice is classically attributed to the presence of a thin self-lubricating film of meltwater between the slider and the ice. But while the macroscale friction behavior of ice and snow has been widely investigated, very little is known about the interfacial water film and its mechanical properties. In this work, we develop a stroke-probe force measurement technique to uncover the microscopic mechanisms underlying ice lubrication. We simultaneously measure the shear friction of a bead on ice and quantify the in-situ mechanical properties of the interfacial film, as well as its thickness, under various regimes of speed and temperature. In contrast with standard views, meltwater is found to exhibit a complex viscoelastic rheology, with a viscosity up to two orders of magnitude larger than pristine water. The non-conventional rheology of meltwater provides a new, consistent, rationale for ice slipperiness. Hydrophobic coatings are furthermore shown to strongly reduce friction due to a surprising change in the local viscosity, providing an unexpected explanation for waxing effects in winter sports. Beyond ice friction, our results suggest new avenues towards self-healing lubricants to achieve ultralow friction.

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“…We also retrieved effective radius of ice crystal using CAR data for fresh fallen snow on the 15 Though the real nature of ice crystal shape at the time of measurement is not known to us, the impact of temperature on morphology of snow grain particles has been debated in previous studies. The results of such studies are now compared with our findings (Slater and Michaelides, 2019;Shultz, 2018;Libbrecht, 2007;Bailey and Hallett, 2004;Yang et al, 2003).…”

Section: Retrieval Of Snow Grain Size and Shapementioning

confidence: 86%

On the retrieval of snow grain morphology, the accuracy of simulated reflectance over snow using airborne measurements in the Arctic

Jafariserajehlou¹,

Розанов²,

Vountas³

et al. 2020

Preprint

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Abstract. Accurate knowledge of the reflectance from snow/ice covered surface is of fundamental importance for the investigation and retrieval of snow parameters and atmospheric constituents. This is a prerequisite for identifying and quantifying changes in the environment and climate in Polar Regions. However, the current differences between simulated and measured reflectance in a coupled snow-atmosphere system, leads to systematic errors in the determination of the amount of trace gases, aerosol and cloud parameters from space based and airborne passive remote sensing observations. In this paper, we describe studies of the retrieval of snow grain morphologies, also called habits, and their use to determine reflectance and test the accuracy of our radiative transfer model simulations of reflectance by comparison with measurements. Firstly we report on a sensitivity study. This addresses the requirement for adequate a priori knowledge about snow models and ancillary information about the atmosphere; the objective being to minimize differences between measurements and simulation. For this aim we use the well-validated phenomenological radiative transfer model SCIATRAN. Secondly and more importantly, we present a novel two-stage snow grain morphology (i.e. size and shape of ice crystals in the snow) retrieval algorithm. We then describe the use of this new retrieval to estimate the most representative snow model, using different types of snow morphologies, for the airborne observation conditions, performed by NASA's Cloud Absorption Radiometer (CAR). The results show that the retrieved ice crystal shapes are consistent with the expected snow morphology (estimated from temperature information) in the measurement area over Barrow/Utqiaġvik, Alaska in 2008. Thirdly, we present a comprehensive comparison of the simulated reflectance (using retrieved snow grain size and shape as well as independent atmospheric data) with that from airborne CAR measurements in the visible and NIR wavelength range. The results of this comparison are used to assess the quality and accuracy of the radiative transfer model in the simulation of the reflectance in a coupled snow-atmosphere system. Assuming that that snow layer consists of ice crystals with aggregates of 8 column ice habit having an effective radius ~ 98.83 μm, we find that for a surface covered by old snow, the Pearson correlation coefficient, R, between measurements and simulations to be 0.98 (R2 ~ 0.96). For freshly fallen snow on areas having surface inhomogenity, the correlation is ~ 0.97 (R2 ~ 0.94) in the infrared and 0.88 (R2 ~ 0.77) in the visible wavelengths assuming that snow layer consists of aggregate of 5 plate ice habit with effective radius ~ 83.41 μm. Largest differences between simulated and measured values are observed in glint, i.e. in the angular regions of specular and near-specular reflection, with relative azimuth angles

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Surface premelting of water ice

Cited by 198 publications

References 192 publications

Structure and fluctuations of the premelted liquid film of ice at the triple point

Structure and fluctuations of the premelted liquid film of ice at the triple point

Nanorheology of Interfacial Water during Ice Gliding

On the retrieval of snow grain morphology, the accuracy of simulated reflectance over snow using airborne measurements in the Arctic

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