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Updated: Jul 1, 2026
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On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature
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Assessing crystallisation behaviour in molecular crystals through particle rugosities.
Marta Brocca1, Dominic Evans1, Helen Blade2
1Department of Chemistry, University of Durham, Durham, UK.
Communications Chemistry
|June 29, 2026
Summary
We developed a new method to calculate crystal surface rugosity, a key factor in crystal formation. Lower rugosity generally indicates crystals that are easier to nucleate and grow, aiding in the identification of experimentally accessible forms.
Area of Science:
- Crystallography
- Materials Science
- Computational Chemistry
Background:
- Surface properties critically influence molecular crystal nucleation, growth, and crystallization.
- Existing surface rugosity metrics are limited by incomplete surface topology descriptions.
Purpose of the Study:
- To introduce a novel computational workflow for calculating surface descriptors across crystal facets.
- To establish a new particle rugosity metric based on the Surface Area Ratio (SAR) for improved crystal analysis.
Main Methods:
- Developed a workflow to compute surface descriptors for crystal facets.
- Utilized the Surface Area Ratio (SAR) definition for surface rugosity.
- Calculated average particle rugosity using three offset selection criteria for diverse crystallization conditions.
Main Results:
- Analyzed particle rugosities for polymorphs, CSD datasets, and crystal structure prediction (CSP) landscapes.
- Observed that lower rugosity generally correlates with enhanced nucleation and growth.
- Demonstrated the metric's ability to differentiate experimentally accessible polymorphs from elusive ones.
Conclusions:
- Particle rugosity serves as a valuable descriptor for crystal nucleation and growth.
- This metric can aid in predicting and classifying the experimental feasibility of computationally generated polymorphs.
- The findings support the use of rugosity as a complementary tool in crystal engineering and discovery.
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