DMREF Publications
Efficient Polymorph Screening through Crystallization from Bulk and Confined Melts
Crystallization from the melt can allow the achievement of high driving force for crystallization accompanied by relatively slow growth, nucleation, and transformation rates, features that favor its use as an efficient polymorph screening method. Surprisingly, even though melt crystallization has a long history, it has been employed less often in the search for new polymorphs than solution crystallization. Applications of melt crystallization to 21 highly polymorphic, well-characterized compounds with at least five ambient polymorphs revealed that melt crystallization afforded more than half of the known polymorphs and in many cases revealed new polymorphs not detected by other screening methods. A statistical analysis revealed that polymorphs grown from the melt have a greater propensity for high Z′ values, which are not easily accessible by other crystallization protocols and are often not detectable by crystal structure prediction methods. Melt crystallization within nanopores (8−100 nm) performed for 19 of the 21 compounds mostly resulted in polymorphs that dominated crystallization from the bulk melt at similar temperatures. The total number of polymorphs observed in nanopores was less than that observed during crystallization from the bulk melt, however, and melt crystallization under confinement revealed new polymorphs not detected by other crystallization methods.
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N. Fellah, L. Tahsin, C. Jin Zhang, B. Kahr, M. D. Ward, A. G. Shtukenberg, Cryst. Growth Des. 2022, 22, 7527–7543.
Geometric Deep Learning for Molecular Crystal Structure Prediction
We develop and test new machine learning strategies for accelerating molecular crystal structure ranking and crystal property prediction using tools from geometric deep learning on molecular graphs. Leveraging developments in graph-based learning and the availability of large molecular crystal data sets, we train models for density prediction and stability ranking which are accurate, fast to evaluate, and applicable to molecules of widely varying size and composition. Our density prediction model, MolXtalNet-D, achieves state-of-the-art performance, with lower than 2% mean absolute error on a large and diverse test data set. Our crystal ranking tool, MolXtalNet-S, correctly discriminates experimental samples from synthetically generated fakes and is further validated through analysis of the submissions to the Cambridge Structural Database Blind Tests 5 and 6. Our new tools are computationally cheap and flexible enough to be deployed within an existing crystal structure prediction pipeline both to reduce the search space and score/filter crystal structure candidates.
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M. Kilgour, J. Rogal, M. Tuckerman, J. Chem. Theory Comput. 2023, 19, 4743–4756.
Chlorfenapyr Crystal Polymorphism and Insecticidal Activity
Optical micrographs of chlorfenapyr polymorphs. Polarizers are crossed for images (A–E). (A) Form I was crystallized from the melt at 80 °C. (B) Form I crystallized from the melt at 23 °C. (C) Transformation of form I into form II/III starting from the edge of the slide at the lower left corner. (D) Feathery flakes of form IV grown from the melt and surrounded by spherulites of form I. (E) Spherulite form IV nucleated at 50 °C. (F) Crystal of form III grown from hexanes. (G) Needle of form II formed on the surface of a poly(ethylene) fiber. If not specified, the scale bars are 0.5 mm..
The search for new insecticides - a.k.a. the “insecticide treadmill - with new mechanisms of action for the control of rapidly reproducing organisms that transmit disease continues. Malarial (Anopheles) mosquitoes are now widely resistant to pyrethroids, synthetic compounds related to pyrethrum, a natural insecticide found in chrysanthemums. Since the 1980s, pyrethroids have shouldered the lion’s share of malaria control. For decades, no new adulticides for vector control were approved by the World Health Organization (WHO). In the face of worldwide pyrethroid resistance, however, the WHO approved chlorfenapyr, a pyrrole proinsecticide typically used alongside pyrethroids to combat pyrethroid resistance. Here, DMREF investigators discovered four crystalline polymorphs of chlorfenapyr, three of which are. considered polytypic. Chlorfenapyr polymorphs show similar lethality against fruit flies (Drosophila melanogaster) and mosquitoes (Anopheles quadrimaculatus) with the least stable polymorph showing slightly higher lethality. Knockdown kinetics, however, depend on an internal metabolic activating step, which further complicates polymorph-dependent bioavailability.
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R. Aronin, P. Brázda, L. N. Smith, C. J. Zhang, J. B. Benedict, Z. Y. Marr, B. Rybtchinski, H. Weissman, A. G. Shtukenberg, B. Kahr, Cryst. Growth Des. 2024, XXXX, XXX, XXX-XXX (https://doi.org/10.1021/acs.cgd.3c01257)
Topological Crystal Structure Prediction
Organic molecular crystals constitute a class of materials of critical importance in numerous industries. Despite the ubiquity of these systems, our ability to predict molecular crystal structures starting only from a two-dimensional diagram of the constituent compound(s) remains a significant challenge. Most structure-prediction protocols require a customized interatomic interaction model on which the quality of the results can depend sensitively. To overcome this problem, we introduce a new topological approach to molecular crystal structure prediction. The approach posits that in a stable structure, molecules are oriented such that principal axes and normal ring plane vectors are aligned with specific crystallographic directions and that heavy atoms occupy positions that correspond to minima of a set of geometric order parameters. By minimizing a loss function that encodes these orientations and atomic positions, stable structures and polymorphs for a given crystal can be predicted entirely mathematically without reliance on an interaction model.
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M. Tuckerman, N. Galanakis, Nat. Commun. 2024, under review, preprint available
Suppressing Disorder in Benzamide and Thiobenzamide Crystals by Fluorine Substitution
Disorder is a common feature of molecular crystals that complicates determination of structures and can potentially affect electric and mechanical properties. Suppression of disorder is observed in otherwise severely disordered benzamide and thiobenzamide crystals by substituting hydrogen with fluorine in the ortho-position of the phenyl ring. Fluorine occupancies of 20−30% are sufficient to suppress disorder without changing the packing motif. Crystal structure prediction calculations reveal a much denser lattice energy landscape for benzamide compared to 2-fluorobenzamide, suggesting that fluorine substitution makes disorder less likely.
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A. G. Shtukenberg, D. E. Braun, M. Tan, N. Fellah, B. Kahr, Cryst. Growth Des. 2024, 24, 5276–5284.
Polymorphism in benzamide − 2-fluorobenzamide (A) and thiobenzamide − 2-fluorothiobenzamide series (B). Increasing color intensity corresponds to increasing disorder. Red bars indicate compositions for which single crystal structure determinations have been realized.
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Machine Learning Classification of Local Environments in Molecular Crystals
Identifying local structural motifs and packing patterns of molecular solids is a challenging task for both simulation and experiment. We demonstrate two novel approaches to characterize local environments in different polymorphs of molecular crystals using learning models that employ either flexibly learned or handcrafted molecular representations. In the first case, we follow our earlier work on graph learning in molecular crystals, deploying an atomistic graph convolutional network combined with molecule-wise aggregation to enable per-molecule environmental classification. For the second model, we develop a new set of descriptors based on symmetry functions combined with a point-vector representation of the molecules, encoding information about the positions and relative orientations of the molecule. We demonstrate very high classification accuracy for both approaches on urea and nicotinamide crystal polymorphs and practical applications to the analysis of dynamical trajectory data for nanocrystals and solid–solid interfaces. Both architectures are applicable to a wide range of molecules and diverse topologies, providing an essential step in the exploration of complex condensed matter phenomena.
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D. Kuroshima, M. Kilgour, M. E. Tuckerman, J. Rogal, J. Chem. Theory Comput. 2024, 20, 6197−6206.
