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A Functional Approach to Solubility Parameter Computations.

Jason Howell1, Miranda Roesing2, David Boucher2

  • 1Department of Mathematics, College of Charleston , 66 George St., Charleston, South Carolina 29424, United States.

The Journal of Physical Chemistry. B
|April 11, 2017
PubMed
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This study introduces a new 3D solubility function to accurately determine solute solubility parameters, overcoming limitations of current methods. This approach improves predictions for solvent affinity and reliability in solubility assessments.

Area of Science:

  • Materials Science
  • Physical Chemistry
  • Computational Chemistry

Background:

  • Determining solute solubility parameters is a complex mathematical challenge.
  • Current methods rely on binary solvent affinity classification and simplified geometric models (spherical/ellipsoidal) in Hansen space.
  • These existing approaches use arbitrary thresholds and assume symmetry in intermolecular forces, which often contradicts experimental data.

Purpose of the Study:

  • To introduce a novel approach for calculating solubility parameters using a three-dimensional solubility function, 'f'.
  • To overcome the limitations of arbitrary thresholds and symmetry assumptions inherent in current methods.
  • To provide a reliable method for predicting solubility in various solvents.

Main Methods:

Related Experiment Videos

  • Development of a new approach utilizing accurate solubility data to define a three-dimensional solubility function, 'f'.
  • Detailed discussion of the principles for constructing the solubility function.
  • Description of procedures for computing solubility parameters using the function 'f'.
  • Application of the method to PCBM ( [6,6]-phenyl-C61-butyric acid methyl ester ) solubility data.

    • Main Results:

    • The new method accurately describes solute solubility using a 3D function.
    • Demonstration of the method's efficacy using PCBM solubility data.
    • The function 'f' can be used to predict solubility in new solvents.

    Conclusions:

    • The proposed 3D solubility function offers a more accurate and reliable method for determining solubility parameters compared to existing techniques.
    • This approach overcomes the limitations of binary classification and simplified geometric models.
    • The method provides a robust tool for predicting and assessing solubility with a measure of reliability.