Skip to main content

Research Repository

Advanced Search

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

Anderson, Michael W.; Gebbie-Rayet, James T.; Hill, Adam R.; Farida, Nani; Attfield, Martin P.; Cubillas, Pablo; Blatov, Vladislav A.; Proserpio, Davide M.; Akporiaye, Duncan; Arstad, Bjørnar; Gale, Julian D.

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


Authors

Michael W. Anderson

James T. Gebbie-Rayet

Adam R. Hill

Nani Farida

Martin P. Attfield

Pablo Cubillas

Vladislav A. Blatov

Davide M. Proserpio

Duncan Akporiaye

Bjørnar Arstad

Julian D. Gale



Abstract

Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years1, 2, 3, 4, 5, it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy6, 7, 8. 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.

Citation

Anderson, M. W., Gebbie-Rayet, J. T., Hill, A. R., Farida, N., Attfield, M. P., Cubillas, P., …Gale, J. D. (2017). Predicting crystal growth via a unified kinetic three-dimensional partition model. Nature, 544(7651), 456-459. https://doi.org/10.1038/nature21684

Journal Article Type Article
Acceptance Date Feb 1, 2017
Online Publication Date Apr 3, 2017
Publication Date Apr 3, 2017
Deposit Date Jun 1, 2017
Publicly Available Date Mar 28, 2024
Journal Nature
Print ISSN 0028-0836
Electronic ISSN 1476-4687
Publisher Nature Research
Peer Reviewed Peer Reviewed
Volume 544
Issue 7651
Pages 456-459
DOI https://doi.org/10.1038/nature21684

Files




You might also like



Downloadable Citations