On the increase of the melting temperature of water confined in one-dimensional nano-cavities

Water confined in nanoscale cavities plays a crucial role in everyday phenomena in geology and biology, as well as technological applications at the water-energy nexus. However, even understanding the basic properties of nano-confined water is extremely challenging for theory, simulations, and experiments. In particular, determining the melting temperature of quasi-one-dimensional ice polymorphs confined in carbon nanotubes has proven to be an exceptionally difficult task, with previous experimental and classical simulation approaches reporting values ranging from ∼180 K up to ∼450 K at ambient pressure. In this work, we use a machine learning potential that delivers first principles accuracy (trained to the density functional theory approximation revPBE0-D3) to study the phase diagram of water for confinement diameters 9.5 < d < 12.5 Å. We find that several distinct ice polymorphs melt in a surprisingly narrow range between ∼280 and ∼310 K, with a melting mechanism that depends on the nanotube diameter. These results shed new light on the melting of ice in one-dimension and have implications for the operating conditions of carbon-based filtration and desalination devices.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2024-12-10
DOI
https://doi.org/10.1063/5.0239452
Citations
3
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
Field-Weighted Citation Impact
0.55

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article

On the increase of the melting temperature of water confined in one-dimensional nano-cavities

Dario Alfè, Venkat Kapil, Andrea Zen, Angelos Michaelides et al.
3 citations
The Journal of Chemical Physics
Nanopore and Nanochannel Transport Studies
0.55
article

On the increase of the melting temperature of water confined in one-dimensional nano-cavities

Dario Alfè, Venkat Kapil, Andrea Zen, Angelos Michaelides, Fabian L. Thiemann, Flaviano Della Pia
article en
3 citations

Abstract

Water confined in nanoscale cavities plays a crucial role in everyday phenomena in geology and biology, as well as technological applications at the water-energy nexus. However, even understanding the basic properties of nano-confined water is extremely challenging for theory, simulations, and experiments. In particular, determining the melting temperature of quasi-one-dimensional ice polymorphs confined in carbon nanotubes has proven to be an exceptionally difficult task, with previous experimental and classical simulation approaches reporting values ranging from ∼180 K up to ∼450 K at ambient pressure. In this work, we use a machine learning potential that delivers first principles accuracy (trained to the density functional theory approximation revPBE0-D3) to study the phase diagram of water for confinement diameters 9.5 < d < 12.5 Å. We find that several distinct ice polymorphs melt in a surprisingly narrow range between ∼280 and ∼310 K, with a melting mechanism that depends on the nanotube diameter. These results shed new light on the melting of ice in one-dimension and have implications for the operating conditions of carbon-based filtration and desalination devices.

The Journal of Chemical PhysicsVol. 161(22)
University of Cambridge (GB), London Centre for Nanotechnology (GB), Thomas Young Centre (GB), University College London (GB), University of Naples Federico II (IT)
Dell EMC, Leverhulme Trust, European Commission, Leverhulme Research Centre for Functional Materials Design, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council, National Supercomputing Center, Korea Institute of Science and Technology Information, HORIZON EUROPE European Research Council
Openalex Percentile: Top 36%
Nanopore and Nanochannel Transport Studies
0.55
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