Hildebrand and Hansen solubility parameters from Molecular Dynamics with applications to electronic nose polymer sensors

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 consist...

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Veröffentlicht in:Journal of computational chemistry 2004-11, Vol.25 (15), p.1814-1826
Hauptverfasser: Belmares, M., Blanco, M., Goddard III, W. A., Ross, R. B., Caldwell, G., Chou, S.-H., Pham, J., Olofson, P. M., Thomas, Cristina
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container_end_page 1826
container_issue 15
container_start_page 1814
container_title Journal of computational chemistry
container_volume 25
creator Belmares, M.
Blanco, M.
Goddard III, W. A.
Ross, R. B.
Caldwell, G.
Chou, S.-H.
Pham, J.
Olofson, P. M.
Thomas, Cristina
description 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 (σ = 0.4 hildebrands). The CED method yields first‐principles Hildebrand parameter predictions in good agreement with experiment [root‐mean‐square (rms) = 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 R2 coefficients between 0.82 and 0.99. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1814–1826, 2004
doi_str_mv 10.1002/jcc.20098
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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 R2 coefficients between 0.82 and 0.99. © 2004 Wiley Periodicals, Inc. 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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 (σ = 0.4 hildebrands). The CED method yields first‐principles Hildebrand parameter predictions in good agreement with experiment [root‐mean‐square (rms) = 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 R2 coefficients between 0.82 and 0.99. © 2004 Wiley Periodicals, Inc. 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source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Algorithms
cohesive energy
Computer Simulation
electronic nose
Hansen solubility parameters
Models, Chemical
Molecular biology
molecular dynamics method
Parameter estimation
Polymers
Polymers - chemistry
Sensors
Solubility
Thermodynamics
title Hildebrand and Hansen solubility parameters from Molecular Dynamics with applications to electronic nose polymer sensors
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