Abstract:We introduce the Cohesive Energy Density (CED) method, a multiple sampling Molecular Dynamics computer simulation procedure that may offer higher consistency in the estimation of Hildebrand and Hansen solubility parameters. The use of a multiple sampling technique, combined with a simple but consistent molecular force field and quantum mechanically determined atomic charges, allows for the precise determination of solubility parameters in a systematic way ( ϭ 0.4 hildebrands). The CED method yields first-principles Hildebrand parameter predictions in good agreement with experiment [root-mean-square (rms) ϭ 1.1 hildebrands]. We apply the CED method to model the Caltech electronic nose, an array of 20 polymer sensors. Sensors are built with conducting leads connected through thin-film polymers loaded with carbon black. Odorant detection relies on a change in electric resistivity of the polymer film as function of the amount of swelling caused by the odorant compound. The amount of swelling depends upon the chemical composition of the polymer and the odorant molecule. The pattern is unique, and unambiguously identifies the compound. Experimentally determined changes in relative resistivity of seven polymer sensors upon exposure to 24 solvent vapors were modeled with the CED estimated Hansen solubility components. Predictions of polymer sensor responses result in Pearson R 2 coefficients between 0.82 and 0.99.

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