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Abstract
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 an objective function that encodes these orientations and atomic positions, and filtering based on the vdW free volume and intermolecular close contact distributions derived from the Cambridge Structural Database, stable structures and polymorphs for a given crystal can be predicted entirely mathematically without reliance on an interaction model.
Reliable prediction of the organic molecular crystal structures is critical across numerous industries yet remains a significant challenge. Here, the authors develop a mathematical workflow based on topological concepts that reduces solution time to mere hours.
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1 New York University, Department of Chemistry, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753)
2 New York University, Department of Chemistry, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753); New York University, Courant Institute of Mathematical Sciences, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753); NYU Shanghai, NYU-ECNU Center for Computational Chemistry, Shanghai, China (GRID:grid.449457.f) (ISNI:0000 0004 5376 0118); Simons Center for Computational Physical Chemistry at New York University, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753)