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Computed Crystal Energy Landscapes for Understanding and Predicting Organic Crystal Structures and Polymorphism
Abstract
The phenomenon of polymorphism, the ability of a molecule to adopt more than one crystal structure, is a well-established property of crystalline solids. The possible variations in physical properties between polymorphs make the reliable reproduction of a crystalline form essential for all research using organic materials, as well as quality control in manufacture. Thus, the last two decades have seen both an increase in interest in polymorphism and the availability of the computer power needed to make the computational prediction of organic crystal structures a practical possibility. In the past decade, researchers have made considerable improvements in the theoretical basis for calculating the sets of structures that are within the energy range of possible polymorphism, called crystal energy landscapes. It is common to find that a molecule has a wide variety of ways of packing with lattice energy within a few kilojoules per mole of the most stable structure. However, as we develop methods to search for and characterize "all" solid forms, it is also now usual for polymorphs and solvates to be found. Thus, the computed crystal energy landscape reflects and to an increasing extent "predicts" the emerging complexity of the solid state observed for many organic molecules. This Account will discuss the ways in which the calculation of the crystal energy landscape of a molecule can be used as a complementary technique to solid form screening for polymorphs. Current methods can predict the known crystal structure, even under "blind test" conditions, but such successes are generally restricted to those structures that are the most stable over a wide range of thermodynamic conditions. The other low-energy structures can be alternative polymorphs, which have sometimes been found in later experimental studies. Examining the computed structures reveals the various compromises between close packing, hydrogen bonding, and pi-pi stacking that can result in energetically feasible structures. Indeed, we have observed that systems with many almost equi-energetic structures that contain a common interchangeable motif correlate with a tendency to disorder and problems with control of the crystallization product. Thus, contrasting the computed crystal energy landscape with the known crystal structures of a given molecule provides a valuable complement to solid form screening, and the examination of the low-energy structures often leads to a rationalization of the forms found.
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Citations
Cited by
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Sutton, C., Risko, C., & Brédas, J.-L. (2016) · Chemistry of Materials · doi:10.1021/acs.chemmater.5b03266 · Cited by 265
Metadata
- Authors
- Price, S. (. L.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-10-17
- Volume
- 42
- Issue
- 1
- Pages
- 117-126
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W1997011211
- Cited by
- 360
- References
- 0
- FWCI
- 11.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- Price, S. (. L. (2009). Computed Crystal Energy Landscapes for Understanding and Predicting Organic Crystal Structures and Polymorphism. Accounts of Chemical Research. https://doi.org/10.1021/ar800147t
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