Abstract
Synthonic engineering tools, including grid-based searching molecular modelling, are applied to investigate the wetting interactions of the solute and four crystallisation solvents (ethanol, ethyl acetate, acetonitrile and toluene) with the {100}, {001} and {011} forms of RS-ibuprofen. The grid-based methods, in particular the construction of a crystal slab parallel to a given plane in a coordinate system with one axis perpendicular to the surface, are defined in detail. The interaction strengths and nature (dispersive, hydrogen bonding (H-bonding) or coulombic forces) are related to the crystal growth rates and morphologies. The solute is found to interact strongest with the capping {011}, then the side {001} and weakest with the top {100} habit surfaces. The solute interactions with the {100} and {001} surfaces are found to be almost solely dominated by dispersive force contributions, whilst the same with the {011} surfaces are found to have a greater contribution from H-bonding and coulombic forces. The increased surface rugosity, at the molecular level of the {011} surfaces, results in a favourable docking site in a surface 'valley', not present in the {100} and {001} surfaces. The H-bonding solvents ethanol, acetonitrile and ethyl acetate are found to strongly interact with the {011} surfaces and weakly with the {001} surfaces, with the {011} interactions having a much greater contribution from H-bonding and coulombic forces. The interaction energies of the apolar and aprotic solvent toluene, with the {011} and {001} surfaces, are found to be very close. Toluene is found having slightly stronger interactions with the {001} than the {011} surfaces, which are all dominated by dispersive interactions. The ratio of the average energy of the top 100 solvent interactions with the {001} surface divided by the average energy of the top 100 interactions with the {011} surface is compared to the ratio of the experimentally measured growth rates of the same forms. In general, the interaction energy ratio is found to have an inverse ratio with the growth rates, implying that the solvents which are calculated to interact strongly with a particular surface are impeding the growth of that surface and reducing the growth rate, in turn impacting upon the final morphology of the material.
Highlights
IntroductionBennema and van der Eerden, upon examination of the interfacial forces associated with crystallisation from solution, derived a molar enthalpy (DH(T)diss) associated with the making and breaking of the intermolecular forces (Fi) over all the molecules of i associated with the crystallisation process,[7,8,9] expressed as: DHðT Þdiss 1⁄4 N Xn ÂFdi f À 0:5ÀFfif þ Fdi dÁÃ (1)
It has been frequently observed that can the different surfaces of organic molecular crystals grow at different rates, but that these face-specific growth rates can vary depending on the solvent from which the material is crystallised, impacting upon the solvent dependent crystal morphology.[1,2,3,4,5] For example, in the case of needle-shaped crystals where the faces forming the ‘tip’ of the needle grow very much faster than the rest
This study reveals how the surface rugosity, along with the solute/surface and solvent/surface interaction strength and nature can influence the individual crystal surface growth rates of RS-ibuprofen, and the degree of needle-like morphology produced from solution
Summary
Bennema and van der Eerden, upon examination of the interfacial forces associated with crystallisation from solution, derived a molar enthalpy (DH(T)diss) associated with the making and breaking of the intermolecular forces (Fi) over all the molecules of i associated with the crystallisation process,[7,8,9] expressed as: DHðT Þdiss 1⁄4 N Xn ÂFdi f À 0:5ÀFfif þ Fdi dÁÃ (1). More computationally efficient methods have been applied to calculating the solvent-dependent morphologies of organic materials.[29,33,34,35] In particular, the development of grid-based searching methods at the single molecule and crystal surface level has been effective in the modelling of crystalline properties, such as solving structures from powder X-ray diffraction data,[36] solvent-dependent crystal morphologies,[5,29] impurity segregation[37,38] and excipient interactions with active pharmaceutical ingredient crystals.[39] By comparison, the grid based search methods use a more approximate approach of the solution–surface interactions, these simulations require only a molecular structures of the host and probe species, whereby the simulation often takes minutes on a laptop computer, and the outputted data requires no further processing In this respect grid based search methods compliment MD simulations, providing a means of quickly assessing solvent wettability and potentially guiding the modeller regarding which solvents to run more complex simulations on. This analysis is coupled with the calculations of the solute interactions with the crystal surface and linked to its overall crystal morphology and growth rates when crystallised from these four solvents
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
