2017) 'Predicting crystal growth via a uni ed kinetic three-dimensional partition model. ', Nature., 544 (7651). pp. 456-459. Further information on publisher's website:https://doi.org/10.1038/nature21684Publisher's copyright statement:Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Understanding and predicting the course of crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for over one hundred years 1-5 it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopies 6-8 . In order to bring some order and understanding to this vast amount of new information requires new rules to be developed and tested. To date, because of the complexity and variety of different crystal systems, this has relied on developing models that are usually constrained to one system only 9-11 . Such work is painstakingly slow and will not be able to achieve the wide scope of understanding in order to create a unified model across crystal types and crystal structures. Here we describe a new approach to understand and, in theory, predict the growth of crystals, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic 3-D partition model. We exemplify our approach by predicting the crystal growth of a diverse set of crystal types including zeolites, metal-organic frameworks, calcite, urea and L-cystine.By understanding crystal growth at the molecular scale we have the possibility to control crystal habit, crystal size, the elimination or incorporation of defects and the development of intergrowth structures. As crystals are used in technologies from pharmaceuticals to gas storage and separation materials, from optoelectronic devices to heterogeneous catalysts, such understanding is vital. If we take an example of a very complex and yet very important crystal type, that of zeolites 12 which form the backbone of the heterogeneous catalysis industry, then many of the problems that must be addressed in crystal growth can be illustrated. Zeolites are nanoporous materials were the framework of the material is constructed from a strong covalently bonded network of Si -O and Al -O bonds. The pores of the material are filled with water and cations that balance the negative charge on the framework. Crystals of zeolites grow from aqueous solutions at temperatures up to about 230 o C and it is well known from NMR spectroscopy that...

Generic in silico methodology – CrystalGrower – for simulating crystal habit and nanoscopic surface topology to determine crystallisation free energies.

We discover that the crystal morphology of zeolite-LTL could be modified by crown ether (21-crown-7, CE), where CE decreases the aspect ratio of zeolite-LTL while increasing the nucleation of domains on the (0001) face and hindering their growth along the c-axes. Moreover, the study using scanning electron microscopy supports that the ratio between the rates for generation of cancrinite columns and bridging cancrinite columns on the {101̅ 0} face remains constant among the LTL frameworks with different amounts of CE molecules. In addition, X-ray diffraction analysis shows that potassium cations redistribute into pore cavities (t-lil) from cancrinite cages (t-can) and t-ste cages by the strong interactions between potassium and CE as the amount of CE molecules is increased. Additionally, Monte Carlo simulations clarify that stabilization of the t-lil cage via the redistribution of potassium cations at high CE concentration is attributed to the dominant effect in the crystal morphology changes observed. To understand the catalytic and adsorption properties of zeolites, it is important to investigate their structure/ property relationships. Especially, studying the morphology of an anisotropic zeolite crystals has been of great interest because of the strong influence on controlling its properties. Thus, morphological control of the material with a particular crystallographic direction is highly desirable to obtain maximum properties for applications.

To me, it suggests a theoretical pathway to computing the kinetic Wulff shape, which oen is not the same as the thermodynamic Wulff shape. Unfortunately, as you show, your calculation is very expensive. I'm wondering if there are any heuristics or faster ways to reach a kinetic Wulff shape, perhaps from DFTcomputable parameters?Kristen Fichthorn responded: Kinetics is so system-dependent. I'm not certain there is an easy universal approach to the kinetic Wulff shape. In this work, we used DFT-computable parameters to get at linear-facet growth rates (though we did not explicitly mention this in the current paper, we did mention it in the past 1,2 ). This could be done with considerable computational expense. Is there a faster way? In a past study, we could show (with the support of experiments) that it was the case that one facet was completely covered by a self-assembled monolayer of capping agent, while the other major facet present during growth did not have surfactant for the same solution-phase chemical potential. From there, we could conclude that solution-phase ion adsorption occurred only on the one facet, but not on the other, leading to certain experimentally observed kinetic shapes. 3,4 These DFT calculations were relatively easy, but the result was not "automatic".

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