Cristin-resultat-ID: 1467321
Sist endret: 7. juni 2021, 14:06
NVI-rapporteringsår: 2017
Resultat
Vitenskapelig artikkel
2017

Predicting crystal growth via a unified kinetic three-dimensional partition model

Bidragsytere:
  • Michael W Anderson
  • James T. Gebbie-Rayet
  • Adam R. Hill
  • Nani Farida
  • Martin P. Attfield
  • Pablo Cubillas
  • mfl.

Tidsskrift

Nature
ISSN 0028-0836
e-ISSN 1476-4687
NVI-nivå 2

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2017
Publisert online: 2017
Trykket: 2017
Volum: 544
Hefte: 7651
Sider: 456 - 459
Open Access

Importkilder

Scopus-ID: 2-s2.0-85017417418

Beskrivelse Beskrivelse

Tittel

Predicting crystal growth via a unified kinetic three-dimensional partition model

Sammendrag

Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years, it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy. To organize and understand this large amount of new information, new rules for crystal growth need to be developed and tested. However, because of the complexity and variety of different crystal systems, attempts to understand crystal growth in detail have so far relied on developing models that are usually applicable to only one system9,10,11. Such models cannot be used to achieve the wide scope of understanding that is required to create a unified model across crystal types and crystal structures. Here we describe a general approach to understanding and, in theory, predicting the growth of a wide range of crystal types, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic three-dimensional partition model. This entails dividing the structure into ‘natural tiles’ or Voronoi polyhedra that are metastable and, consequently, temporally persistent. As such, these units are then suitable for re-construction of the crystal via a Monte Carlo algorithm. We demonstrate our approach by predicting the crystal growth of a diverse set of crystal types, including zeolites, metal–organic frameworks, calcite, urea and L-cystine.

Bidragsytere

Michael W Anderson

  • Tilknyttet:
    Forfatter
    ved University of Manchester

James T. Gebbie-Rayet

  • Tilknyttet:
    Forfatter
    ved University of Manchester

Adam R. Hill

  • Tilknyttet:
    Forfatter
    ved University of Manchester

Nani Farida

  • Tilknyttet:
    Forfatter
    ved University of Manchester

Martin P. Attfield

  • Tilknyttet:
    Forfatter
    ved University of Manchester
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