Polymorph-Specific Solubility Prediction of Urea Using Constant Chemical Potential Molecular Dynamics Simulations

Area of Science:

• Computational chemistry and materials science.
• Investigating solid-state properties and solution behavior.

Background:

• Solubility is a critical material property with broad applications.
• Traditional computational methods for solubility prediction have limitations.
• Molecular dynamics (MD) simulations offer a powerful approach to study material properties.

Purpose of the Study:

• To predict the solubility of different urea polymorphs in aqueous solutions.
• To utilize Constant Chemical Potential Molecular Dynamics (CCPMD) for accurate solubility determination.
• To differentiate between urea polymorphs based on their solubility profiles.

Main Methods:

• Employed Constant Chemical Potential Molecular Dynamics (CCPMD), a variant of direct coexistence simulation.
• Maintained a constant chemical potential over extended simulation times to overcome limitations of direct simulation.
• Focused on three distinct polymorphs of urea as a model system.

Main Results:

• Successfully discriminated between urea polymorphs using their predicted solubility values.
• Identified Polymorph III as having the highest aqueous solubility.
• Determined the solubility order: Polymorph III > Form IV > Form I.

Conclusions:

• CCPMD is an effective method for predicting and differentiating the solubility of crystalline polymorphs.
• The study provides valuable solubility data for urea polymorphs, aiding in material selection and processing.
• This approach advances computational solubility prediction for crystalline solids.