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A New Software Framework for Implementing Crystal Growth Models to Materials of Any Crystallographic Complexity

By Zhao, Yongsheng; Tilbury, Carl J. Landis, Steven Sun, Yuanyuan; Li, Jinjin; Zhu, Peng; Doherty, Michael F.

Published on CMKC

Abstract

To continue the realization of new therapeutics, a more diverse range of solid forms is being considered. Synthetic modalities are broadening beyond simple organic molecules to more complicated structures, including organic salts, cocrystals, and solvates. As in all crystalline applications, engineering the morphology of such systems remains an important consideration, but traditional in silico approaches require further development to become capable of accurately describing these systems. A necessary, but not sufficient, condition to enact mechanistic crystal growth models is to calculate and organize solid-state interactions between growth units. The typical software framework for acquiring this information is to apply crystallographic symmetry operations to generate a unit cell from the asymmetric unit. While this approach is feasible for systems where the asymmetric unit corresponds to the growth unit itself, many systems do not satisfy this criterion, particularly the emerging therapeutic solid forms. By redesigning the input preparation software framework, we can build a description of the solid-state interactions that is independent of the asymmetric unit and applicable to any crystallographic complexity. We demonstrate the application of this method to three organic molecular crystals with crystallography of varying degrees of complexity. The studied systems are naphthalene (Z′ = 0.5), benzoic acid (Z′ = 1), and tazofelone (Z′ = 2), respectively (where Z′ is the number of molecules in the asymmetric unit). This new software framework lays the groundwork for rapid in silico habit predictions of organic salts, cocrystals, and solvates.

Journal

Crystal Growth & Design. Volume 20, 5, 2020, 2885-2892

DOI

10.1021/acs.cgd.9b01105

Type of publication

Peer-reviewed journal

Affiliations

  • University of California, Santa Barbara, Department of Chemical Engineering

Article Classification

Research Article

Classification Areas

  • Modeling

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