Hildebrand-Assessed Margules (HAM) interaction parameter: applications to surfactant and polar oil partition

09 August 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The Hildebrand-Assessed Margules (HAM) method uses Henry's law constant and vapor pressure for pure components from free cheminformatic software to obtain the interaction parameter of a component "i" with water (Aiw) and its molar volume (Vmi). Inspired by the concept of the solubility parameter of Hildebrand (δi), where (Aiw/Vmi)^0.5 = (δi-δw), HAM makes a simple assessment of the binary interaction parameter Aij: (δi-δj) =(Aij/Vmi)^0.5 = (δi-δw)-(δi-δw)= (Aiw/Vmi)^0.5- (Ajw/Vmi)^0.5. The Aij predictions from this relatively simple expression were compared to literature Aij data obtained from activity coefficients of "i" at infinite dilution in a solvent "j". The performance of the HAM framework was compared to other predictive models, UNIFAC, MOSCED, COSMO-RS, HSP and the original Hildebrand model. The HAM method overpredicted Aij (>1Aij unit) in systems where the solvent was an acid or a base that could dissociate in the presence of water. However, for most systems (small polar molecules, short chain alcohols, medium chain alcohols, aromatics and alkanes), the Aij values were predicted within 1 Aij unit and commonly within 0.5 Aij units. A systemic underprediction of Aij was observed when the HAM-predicted log P was compared to predictions from the ACD/Labs software, which required the introduction of a correction term. The corrected HAM method reproduced the partition coefficient of surfactant and polar molecules with an RMSE of 1.05 and an NRMSE of 15%, comparable to other models that require more inputs and resources.


liquid equilibrium
predictive methods


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