Mapping uncharted territory in ice from zeolite networks to ice structures

Authors: Edgar A. Engel1*, Andrea Anelli2, Michele Ceriotti2, Chris J. Pickard4,3, Richard J. Needs1

  1. TCM Group, Cavendish Laboratory, J J Thomson Avenue, Cambridge, CB3 0HE, UK
  2. Laboratory of Computational Science and Modeling, Institute of Materials, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Vaud, Switzerland
  3. Department of Materials Science and Metallurgy, 27 Charles Babbage Road, Cambridge CB3 0FS, UK
  4. Advanced Institute for Materials Research, Tohoku University, 2-1-1 Katahira, Aoba, Sendai 980-8577, Japan
  • Corresponding author email: eae32@cam.ac.uk

DOI10.24435/materialscloud:2018.0010/v1 (version v1, submitted on 19 May 2018)

How to cite this entry

Edgar A. Engel, Andrea Anelli, Michele Ceriotti, Chris J. Pickard, Richard J. Needs, Mapping uncharted territory in ice from zeolite networks to ice structures, Materials Cloud Archive (2018), doi: 10.24435/materialscloud:2018.0010/v1.

Description

We report a large-scale density-functional-theory study of the configuration space of water ice. We geometry optimise 74,963 ice structures, which are selected and constructed from over five million tetrahedral networks listed in the databases of Treacy and Deem, and the International Zeolite Association database. All prior knowledge of ice is set aside and we introduce generalised convex hulls to identify configurations stabilised by appropriate thermodynamic constraints. We thereby rediscover all known phases (I to XVII, i, 0 and the quartz phase) except the metastable ice IV. Crucially, we also find promising candidates for ices XVIII through LI. Using the sketch-map dimensionality-reduction algorithm we construct an a priori, navigable map of configuration space, which reproduces similarity relations between structures and highlights the novel candidates. By relating the known phases to the tractably small, yet structurally diverse set of synthesisable candidate structures, we provide an excellent starting point for identifying formation pathways.

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Files

File name Size Description
properties.dat
MD5MD5: a38a1b64b1e726917a9220b8ce3d1587
1007.4 KiB Properties of all structures (identifier, number of atoms per unit cell, density, configurational energy, and energy with respect to the energy-density convex hull).
dataset.xyz
MD5MD5: 7b8efa3f0773afe4adcaec310814d967
50.7 MiB Structures in xyz format for 15,869 ice structures geometry optimised using PBE-DFT in Castep (plane-wave energy cut-off of 490eV, maximum k-point spacing of 2pi * 0.07 inverse Angstrom, and on-the-fly generated ultrasoft pseudopotentials).

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.

External references

Journal reference
E. A. Engel, A. Anelli, M. Ceriotti, C. J. Pickard, and R. J. Needs.; Nat. Comm. 9, 2173 (2018) doi:10.1038/s41467-018-04618-6

Keywords

3D three-dimensional database high-throughput water ice DFT first-principles

Version history

19 May 2018 [This version]