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Revisiting Aspirin Polymorphic Stability Using a Machine Learning Potential.

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This study reveals aspirin Form I is more stable than Form II at room temperature, thanks to anharmonic effects and rotational entropy. This computational approach advances understanding of organic crystal polymorphism.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Solid-state chemistry

Background:

  • Polymorphism in organic crystals, like aspirin, significantly impacts material properties.
  • Accurately predicting the free energy stability of different polymorphs remains a challenge.
  • Previous simulations often failed to capture subtle energy differences crucial for stability ranking.

Purpose of the Study:

  • To computationally determine the free energy difference between aspirin Form I and Form II.
  • To investigate the role of anharmonic effects and molecular dynamics in polymorphic stability.
  • To establish a reliable method for predicting crystal stability in organic systems.

Main Methods:

  • Development of a neural network interatomic potential (NNIP) model for aspirin.
  • Training the NNIP model using diverse configurations for accurate crystal dynamics simulation.
  • Employing thermodynamic integration with anharmonic effects in large supercells (512 molecules).

Main Results:

  • Demonstrated that aspirin Form I is more stable than Form II at 300 K (0.74–1.83 kJ/mol/molecule).
  • Highlighted the critical importance of anharmonic effects and rotational entropy in determining stability.
  • Correlated free energy differences with observed thermal expansion behaviors.

Conclusions:

  • Aspirin Form I exhibits superior thermodynamic stability over Form II at ambient conditions.
  • The computational strategy, including anharmonic effects, provides accurate predictions for organic crystal polymorphism.
  • The findings offer a promising approach for stability studies in drug design and materials science.