Combining Structural Rugosity and Crystal Packing Comparison: A Route to More Polymorphs?

Abstract

In this study, we have combined structural comparisons and the rugosity model to investigate experimental and predicted crystal structures from previous results of a crystal structure prediction study on a group of three rigid, planar small molecules, 2-methyl-, 3-methyl-, and 2,3-dimethyl-benzo­[b]­thiophene 1,1-dioxide. The results of the crystal structure comparisons provided some insights into the possibility that pairs of predictions, close in energy, might be related by potential phase transitions. In particular, we observed that for some pairs of predictions, a transformation from one type of crystal packing to the other would require only small shifts between adjacent molecules. This raised the question of whether only a few of these predictions can effectively be experimentally isolated. The calculations of the structural rugosity, a parameter that correlates surface rugosity with ease of crystallization, indicated smooth surfaces only for a few predictions. With the aim to isolate new polymorphs, we performed a small experimental study, limited to a few common solvents and crystallizations from the melt. Crystallizations from the melt selectively produced single crystals of new polymorphs for the 3-methyl- and the 2,3-methyl-benzothiophene derivatives. These showed good correlations with the above calculations, suggesting that the combination of crystal structure analysis and experimental screening might represent a useful approach in polymorphism screenings.

Reducing overprediction of molecular crystal structures via threshold clustering

“…While threshold clustering does not represent a singular solution for overprediction, and many of the factors that contribute to overprediction, in particular crystallization kinetics, will still need to be addressed, we see threshold clustering as a valuable addition to the toolset for identifying observable polymorphs. We expect the reduced set of structures to combine synergistically with methods such as DFT+D calculations to more accurately determine energy rankings, dynamics simulations to probe thermal stability and thermal averaging, and rugosity calculations ( 32 ) to estimate the relative ease of crystallization. Ongoing studies are investigating a number of optimizations and improvements to the algorithm, including convergence criteria to improve sampling efficiency and more system-specific energy models, such as machine-learned and tailor-made force fields, to improve the accuracy of the underlying energy surface.…”

“…The prominence of overprediction in CSP has led to efforts to systematically reduce the number of candidate structures from the initial CSP landscape toward a smaller set of structures more likely to be observed experimentally. Methods based on arguments of crystallization kinetics ( 30 , 31 ) and packing similarity ( 32 ) have been proposed. However, the most developed methodology involves a series of molecular dynamics (MD) and enhanced sampling simulations to group the CSP structures into free energy clusters ( 33 – 40 ).…”

What has scripting ever done for us? The CSD Python application programming interface (API)

“…Iuzzolino et al (2017) have used the conformer generator built into the API programmatically to enhance sampling in crystal structure prediction. In another CSP-related report, access to rugosity calculations has led to suggestions of paths for identifying accessible but so far unobserved crystal structures (Montis et al, 2022).…”

Reducing Overprediction of Molecular Crystal Structures via Threshold Clustering

“…29 The prominence of overprediction in CSP has led to efforts to systematically reduce the number of candidate structures from the initial CSP landscape towards a smaller set of structures more likely to be observed experimentally. Methods based on arguments of crystallisation kinetics 30,31 and packing similarity 32 have been proposed. However, the most developed methodology involves a series of molecular dynamics (MD) and enhanced sampling simulations to group the CSP structures into free energy clusters.…”