Nature, volume 544, issue 7651, pages 456-459
Predicting crystal growth via a unified kinetic three-dimensional partition model.
Anderson Michael W.
1
,
Gebbie Rayet James T
1, 2
,
Hill Adam R
1
,
Farida Nani
1
,
Attfield Martin P
1
,
Cubillas Pablo
1, 2
,
Blatov Vladislav A.
3, 4
,
Proserpio Davide M.
3, 5
,
Akporiaye Duncan
6
,
Arstad Bjørnar
6
,
Gale Julian D.
7
1
4
6
SINTEF Materials and Chemistry, Blindern, Norway
|
Publication type: Journal Article
Publication date: 2017-04-01
Multidisciplinary
Abstract
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 system. 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.
Citations by journals
Citations by publishers
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5
10
15
20
25
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American Chemical Society (ACS)
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American Chemical Society (ACS)
24 publications, 27.59%
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Elsevier
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14 publications, 16.09%
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Royal Society of Chemistry (RSC)
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13 publications, 14.94%
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Wiley
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Wiley
7 publications, 8.05%
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Springer Nature
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6 publications, 6.9%
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Pleiades Publishing
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Pleiades Publishing
4 publications, 4.6%
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Multidisciplinary Digital Publishing Institute (MDPI)
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3 publications, 3.45%
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American Physical Society (APS)
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American Physical Society (APS)
2 publications, 2.3%
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Walter de Gruyter
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Walter de Gruyter
1 publication, 1.15%
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Bentham Science
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Bentham Science
1 publication, 1.15%
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Chemical Industry Press
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Chemical Industry Press, 1, 1.15%
Chemical Industry Press
1 publication, 1.15%
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IOP Publishing
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IOP Publishing
1 publication, 1.15%
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Frontiers Media S.A.
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Frontiers Media S.A.
1 publication, 1.15%
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Oxford University Press
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Oxford University Press
1 publication, 1.15%
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Proceedings of the National Academy of Sciences (PNAS)
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Proceedings of the National Academy of Sciences (PNAS)
1 publication, 1.15%
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Annual Reviews
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Annual Reviews
1 publication, 1.15%
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American Institute of Physics (AIP)
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American Institute of Physics (AIP)
1 publication, 1.15%
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- We do not take into account publications that without a DOI.
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- Statistics recalculated weekly.
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Anderson M. W. et al. Predicting crystal growth via a unified kinetic three-dimensional partition model. // Nature. 2017. Vol. 544. No. 7651. pp. 456-459.
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Anderson M. W., Gebbie Rayet J. T., Hill A. R., Farida N., Attfield M. P., Cubillas P., Blatov V. A., Proserpio D. M., Akporiaye D., Arstad B., Gale J. D. Predicting crystal growth via a unified kinetic three-dimensional partition model. // Nature. 2017. Vol. 544. No. 7651. pp. 456-459.
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TY - JOUR
DO - 10.1038/nature21684
UR - https://doi.org/10.1038%2Fnature21684
TI - Predicting crystal growth via a unified kinetic three-dimensional partition model.
T2 - Nature
AU - Anderson, Michael W.
AU - Gebbie Rayet, James T
AU - Hill, Adam R
AU - Farida, Nani
AU - Attfield, Martin P
AU - Cubillas, Pablo
AU - Blatov, Vladislav A.
AU - Proserpio, Davide M.
AU - Akporiaye, Duncan
AU - Arstad, Bjørnar
AU - Gale, Julian D.
PY - 2017
DA - 2017/04/01 00:00:00
PB - Springer Nature
SP - 456-459
IS - 7651
VL - 544
SN - 0028-0836
SN - 1476-4687
ER -
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@article{2017_Anderson,
author = {Michael W. Anderson and James T Gebbie Rayet and Adam R Hill and Nani Farida and Martin P Attfield and Pablo Cubillas and Vladislav A. Blatov and Davide M. Proserpio and Duncan Akporiaye and Bjørnar Arstad and Julian D. Gale},
title = {Predicting crystal growth via a unified kinetic three-dimensional partition model.},
journal = {Nature},
year = {2017},
volume = {544},
publisher = {Springer Nature},
month = {apr},
url = {https://doi.org/10.1038%2Fnature21684},
number = {7651},
pages = {456--459},
doi = {10.1038/nature21684}
}
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MLA
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Anderson, Michael W., et al. “Predicting crystal growth via a unified kinetic three-dimensional partition model..” Nature, vol. 544, no. 7651, Apr. 2017, pp. 456-459. https://doi.org/10.1038%2Fnature21684.
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