Related Experiment Videos
The electrostatic origin of Abraham's solute polarity parameter
J Samuel Arey1, William H Green, Philip M Gschwend
1Department of Marine Chemistry and Geochemistry, MS #4, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA. arey@alum.mit.edu
The Journal of Physical Chemistry. B
|July 21, 2006
Summary
A new computational method accurately predicts solute polarity (S) using fundamental polarizability and electrostatic terms. This approach offers a more precise alternative to existing models for various organic solutes.
Area of Science:
- Computational Chemistry
- Physical Chemistry
- Quantitative Structure-Property Relationships (QSPR)
Background:
- The empirical Linear Solvation Energy Relationship (LSER) uses the solute polarity parameter, S, which is crucial for predicting chemical behavior.
- Existing methods for calculating S often lack accuracy or rely on less fundamental descriptors.
- Understanding the interplay between solute polarizability and electrostatics is key to refining S parameter calculations.
Purpose of the Study:
- To develop a novel computational method for calculating the LSER solute polarity parameter, S.
- To relate S to fundamental quantities: solute polarizability and solvent-accessible surface electrostatics.
- To provide quantitative insights into the contributions of polarizability and electrostatics to S.
Main Methods:
- Developed a computational method linking the empirical S parameter to polarizability and computed solvent-accessible surface electrostatic terms.
- Performed electrostatics computations using density functional theory (B3LYP/6-311G(2df,2p)) and Hartree-Fock (HF/MIDI!) methods with continuum models (PCM, SCIPCM, IPCM).
- Calculated electrostatic parameters at electron isodensity solute surfaces for 90 polar and nonpolar organic solutes.
Main Results:
- Electrostatic parameters derived from solvent-accessible surfaces showed significantly better correlation with empirical S values compared to those from fixed atomic radii surfaces.
- The best-fit expression, S(fit)() = 0.46E - 0.091SigmaV(s)()(2), achieved a squared correlation coefficient of 0.96.
- The model utilizes a measured solute excess polarizability scale (E) and a quantum-calculated solute electrostatic descriptor (SigmaV(s)()(2)).
Conclusions:
- The developed computational method accurately predicts the LSER S parameter using fundamental molecular properties.
- The model is more accurate than previous estimation approaches and requires only two fitted coefficients.
- This method has potential applicability to a wide range of organic solutes containing common elements (C, H, N, O, S, F, Cl, Br).