ArticleNature communications2024
Rapid prediction of molecular crystal structures using simple topological and physical descriptors.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Interpretable Machine Learning of Nanoparticle Stability through Topological Layer Embeddings.The journal of physical chemistry. A · 2026Article
- Hydration control in molecular salts through counterion selection.Nature communications · 2026Article
- Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials.Crystal growth & design · 2025Article
- Dynamic Collision Fingerprints (DCF): Introducing a New Descriptor Linking Lattice Interactions to 2D Structural Data Signatures.Journal of chemical theory and computation · 2025Article
- 3D conformation and crystal interaction insights into drug development challenges for HCV drug analogues via molecular simulations.Communications chemistry · 2025Article
- Accurate and efficient machine learning interatomic potentials for finite temperature modelling of molecular crystals.Chemical science · 2025Article
- Unlocking COiScience · 2025Review
- One Size Fits All? Development of the CPOSS209 Data Set of Experimental and Hypothetical Polymorphs for Testing Computational Modeling Methods.Crystal growth & design · 2025Article
- Rapid prediction of molecular crystal structures using simple topological and physical descriptors.Nature communications · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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.
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Registered trials
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