Capturing Crystal Shape Evolution from Molecular Simulations.

Area of Science:

• Materials Science
• Computational Chemistry
• Crystallography

Background:

• Understanding crystal morphology is crucial for predicting material properties and behavior.
• Tracking crystal shape evolution during simulations provides insights into growth and dissolution processes.
• Existing methods may require extensive input or lack the ability to detect novel crystal faces.

Purpose of the Study:

• To develop a simple and efficient algorithm for tracking the shape evolution of small-molecule organic crystals during molecular simulations.
• To enable automatic detection of existing and newly forming crystal faces and edges.
• To provide a tool valuable for predicting crystal growth and dissolution kinetics.

Main Methods:

• The algorithm reconstructs crystal surfaces from molecular coordinates using alpha-shape triangulation.
• DBSCAN clustering of neighboring triangles with similar normal vectors identifies crystal faces.
• Only unit cell parameters are required as initial input.

Main Results:

• The algorithm successfully tracks shape evolution in small-molecule organic crystals.
• It automatically detects existing and forming crystal faces and edges without prior information.
• Demonstrated effectiveness for aspirin and paracetamol crystals.

Conclusions:

• The developed algorithm offers a simple and efficient method for analyzing crystal morphology in simulations.
• Its ability to detect new crystal faces is valuable for predicting kinetic processes.
• This approach enhances the study of crystal growth and dissolution dynamics.