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

• Published in: Nature (London) Vol. 544; no. 7651; pp. 456 - 459
• Main Authors: 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.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.04.2017; Nature Publishing Group
• Subjects: 119/118; 639/301/1034; 639/638/298/921; 639/638/563/980; Algorithms; Calcite; Calcium Carbonate - chemistry; Condensation; Crystal growth; Crystal structure; Crystallization; Cystine - chemistry; Humanities and Social Sciences; Kinetics; letter; Models, Chemical; Monte Carlo Method; multidisciplinary; Science; Topology; Urea; Urea - chemistry; Zeolites; Zeolites - chemistry
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature21684

A general simulation approach that can replicate, and in theory predict, the growth of a wide range of crystal types, including porous, molecular and ionic crystals, is demonstrated. Crystals of Monte Carlo Understanding crystal growth is essential for controlling functionality in modern materials. Michael Anderson et al . describe a simulation approach to predicting crystal growth that can replicate, and in theory predict, the fine details of surface structure and habit for a wide range of crystal types, including porous crystalline materials, metal–organic frameworks and ionic crystals. The method is based on Monte Carlo simulations of 'units of growth'—space-filling tiles or Voronoi polyhedra, depending on the nature of the crystal. This is a coarse-grained alternative to the computationally intensive and sometimes intractable problem of simulating individual atomic positions. The approach replicates the surface structure of experimentally grown crystals that incorporate growth modifiers or common defects, and those grown out of equilibrium, and could be applicable across a variety of crystal systems, the authors say. Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years 1 , 2 , 3 , 4 , 5 , it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy 6 , 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 system 9 , 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.