CrystalGrower: a generic computer program for Monte Carlo modelling of crystal growth

Abstract

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

Simulating intergrowth formation in zeolite crystals: impact on habit and functionality

“…Simulations were run using the CrystalGrower simulation package. 22,23 The scheme used is adapted from that proposed for use in the program MONTY, as reported in 2004 by Meekes et al 24 Crystallisation was modelled as a series of reversible transitions between a growth solution and a crystal surface, with the mother phase parameterised by bulk values and the crystal surface broken down into a limited number of site types, where site type is determined by the number of neighbouring units with which an attaching growth unit can form an interaction. 25,26 Monte Carlo 'trial moves' corresponded to attachment or dissolution of single growth units at surface sites.…”

“…The partitioning of crystal structures in these examples is as reported in our previous work. 22,23 Supersaturation prole and crystallisation free energies The approach outlined above requires knowledge of values for supersaturation (Dm) and the crystallisation free energies associated with different bonding interactions (DU i ). Determination of these values is a matter of particular difficulty for zeolite crystals.…”

“…In light of this, the CrystalGrower simulation package was developed as a means to rapidly simulate 3D maps of crystal surfaces using a kinetic Monte-Carlo method, allowing detailed comparison to images obtained using scanning probe microscopy. 22,23 CrystalGrower achieves this aim by partitioning crystal structures into units, then reassembling these units in silico, thereby simulating the surface topology at each stage of the crystallisation. This is realised using a model which divides crystal surfaces into site types for growth and dissolution based on the number and type of intracrystalline bonds which could be formed if a growth unit attached at a certain site.…”

“…and earlier), it was not possible to incorporate stacking faults or intergrowths into the model. 22,23 This prevented the application of the soware to materials which contained a high level of disorder. In this study, a modied version of the CrystalGrower Monte Carlo approach has been developed and applied to create models of crystal growth and dissolution in two disordered zeolite frameworks which contain high levels of stacking faults, namely zeolite T and zeolite beta.…”

The extensive solid-form landscape of sulfathiazole: geometrical similarity and interaction energies

“…[15][16][17] Successes in CSP are also increasing at a steady rate and the current state of the art means that structures with many degrees of freedom and multi-component crystals can often be predicted, using a number of programs. 13 Synergy between CSP and experimental studies has been realised in some cases, [18][19][20] and the long-term potential for application of machine learning and artificial intelligence to the design of solid forms is clear. [21][22][23][24] In this context, one compound that we have studied extensively is sulfathiazole (SLFZ), a well-known active pharmaceutical ingredient (API; Scheme 1).…”