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Classical density functional theory, unconstrained crystallization, and polymorphic behavior.

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Summary
This summary is machine-generated.

Classical density functional theory (cDFT) can now effectively model crystallization by using a simpler heuristic model, overcoming previous numerical instabilities. This allows for accurate simulation of crystal formation and melting in inhomogeneous systems.

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Area of Science:

  • Physical Chemistry
  • Computational Physics
  • Materials Science

Background:

  • Classical density functional theory (cDFT) has theoretical potential for studying crystallization.
  • Practical applications have been limited by numerical instabilities in sophisticated models.

Purpose of the Study:

  • To investigate the reasons for technical difficulties in applying cDFT to crystalline systems.
  • To propose and validate a more stable heuristic model for cDFT calculations.
  • To demonstrate the capability of cDFT in describing crystallization in inhomogeneous systems.

Main Methods:

  • Analysis of numerical instabilities in tensor functionals within cDFT.
  • Implementation and testing of an older, heuristic cDFT model.
  • Simulations of Lennard-Jones fluid droplets on a hydrophobic wall and in periodic cells.
  • Thermodynamic analysis of liquid, amorphous, and crystalline phases.

Main Results:

  • The proposed heuristic model eliminates technical difficulties associated with tensor functionals.
  • Spontaneous crystallization into hexagonal close-packed (HCP) structures observed for droplets on a wall.
  • Amorphous structures with glass-like characteristics formed in periodic cells at lower temperatures.
  • Face-centered cubic (fcc) crystals formed under slightly altered conditions, showing lower free energy than amorphous structures.
  • Melting of solid clusters observed as temperature increases, demonstrating energy barriers between phases.

Conclusions:

  • A revised heuristic approach significantly improves the applicability of cDFT for crystallization studies.
  • cDFT can accurately model spontaneous formation, structural characteristics, and phase transitions (melting) of crystalline and amorphous solids in inhomogeneous environments.
  • The study highlights the importance of model selection for overcoming computational challenges in cDFT.