TY - JOUR
T1 - Revisiting Hansen Solubility Parameters by Including Thermodynamics
AU - Louwerse, Manuel J
AU - Fernández-Maldonado, Ana María
AU - Rousseau, Simon
AU - Moreau-Masselon, Chloe
AU - Roux, Bernard
AU - Rothenberg, Gadi
N1 - © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
PY - 2017/11/3
Y1 - 2017/11/3
N2 - The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy and enthalpy, several corrections are suggested that make the methodology thermodynamically sound without losing its ease of use. The most important corrections include accounting for the solvent molecules' size, the destruction of the solid's crystal structure, and the specificity of hydrogen-bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures. Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54 % to 78 %. Full Matlab scripts are included in the Supporting Information, allowing readers to implement these improvements on their own datasets.
AB - The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy and enthalpy, several corrections are suggested that make the methodology thermodynamically sound without losing its ease of use. The most important corrections include accounting for the solvent molecules' size, the destruction of the solid's crystal structure, and the specificity of hydrogen-bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures. Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54 % to 78 %. Full Matlab scripts are included in the Supporting Information, allowing readers to implement these improvements on their own datasets.
U2 - 10.1002/cphc.201700408
DO - 10.1002/cphc.201700408
M3 - Article
C2 - 28759147
SN - 1439-4235
VL - 18
SP - 2999
EP - 3006
JO - ChemPhysChem
JF - ChemPhysChem
IS - 21
ER -