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Reducing overprediction of molecular crystal structures via threshold clustering
Patrick W V Butler1, Graeme M Day1
1School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom.
Summary
Crystal structure prediction often overestimates polymorphs. This study introduces a threshold algorithm to cluster energy minima, identifying kinetically stable forms and reducing overprediction for molecular compounds.
Area of Science:
- Crystallography
- Computational Chemistry
- Materials Science
Background:
- Crystal structure prediction is vital for understanding molecular compound polymorphism.
- Current methods often overpredict the number of possible polymorphs.
- This overprediction stems from neglecting the merging of energy minima at finite temperatures.
Purpose of the Study:
- To address the overprediction issue in crystal structure prediction.
- To identify kinetically stable polymorphs.
- To refine computational assessments of molecular compound polymorphism.
Main Methods:
- Developed a method utilizing the threshold algorithm.
- Clustered potential energy minima into distinct basins.
- Incorporated finite temperature effects on energy landscapes.
Main Results:
- Successfully clustered energy minima, distinguishing between distinct basins.
- Identified kinetically stable polymorphs by considering energy barrier coalescence.
- Demonstrated a reduction in the overprediction of polymorphs.
Conclusions:
- The threshold algorithm effectively identifies kinetically stable polymorphs.
- Accounting for energy barrier coalescence significantly improves crystal structure prediction accuracy.
- This method offers a more realistic assessment of polymorphism in molecular compounds.
