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Predicting Density of Amorphous Solid Materials Using Molecular Dynamics Simulation.

Mustafa Bookwala1, Kevin DeBoyace1, Ira S Buckner1

  • 1Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, 600 Forbes Avenue, 422C Mellon Hall, Pittsburgh, Pennsylvania, 15282, USA.

AAPS Pharmscitech
|February 28, 2020
PubMed
Summary

Molecular dynamic simulations accurately predict amorphous solid density, outperforming crystallographic approximations. This method is crucial when experimental density measurements are unfeasible.

Keywords:
amorphous densitycrystallographic densityhelium pycnometrymolecular dynamics

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Solid-State Physics

Background:

  • Accurate amorphous solid density is vital for materials behavior studies and modeling.
  • Experimental density measurement via helium pycnometry is standard but has limitations.
  • Crystallographic density approximations are often inaccurate or impossible for unknown structures.

Purpose of the Study:

  • To assess the accuracy of molecular dynamic (MD) simulations for predicting amorphous solid density.
  • To compare MD predictions with experimental helium pycnometry data.
  • To provide a reliable method for density calculation when experiments are not feasible.

Main Methods:

  • Molecular dynamic simulations were employed to predict the densities of 20 amorphous solid materials.
  • Calculated densities for 10 materials were compared against experimental helium pycnometry measurements.
  • Amorphous densities were also approximated from crystallographic densities for comparison.

Main Results:

  • MD simulations yielded amorphous densities with an average percent error of -0.7% compared to experimental values.
  • Crystallographic approximations showed a larger average percent error of +3.7% against experimental data.
  • MD simulations proved significantly more accurate than crystallographic approximations.

Conclusions:

  • Molecular dynamic simulations offer a highly accurate method for predicting amorphous solid densities.
  • This computational approach overcomes limitations of experimental measurements and crystallographic approximations.
  • MD simulations enable reliable density determination for amorphous materials where experimental data is unobtainable.