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Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270.

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Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270.

QDB archive DOI: 10.15152/QDB.190   DOWNLOAD

QsarDB content

Property logKMXa: Cuticular polymer matrix/air partition coefficient as logKMXa

Eq.5: Model for volatile organic compounds

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training set training 36 0.929 0.150

Citing

When using this QDB archive, please cite (see details) it together with the original article:

  • Piir, G. Data for: Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. QsarDB repository, QDB.190. 2017. http://dx.doi.org/10.15152/QDB.190

  • Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270. http://dx.doi.org/10.1360/02tb9281

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Title: Zhang, C.; Feng, L.; Wei, J. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors. Chin. Sci. Bull. 2002, 47, 1270.
Abstract: Based on theoretical linear solvation energy relationship and quantum chemical descriptors computed by AM1 Hamiltonian, a new model is developed to predict the partitioning of some volatile organic compounds between the plant cuticular matrix and air.
URI: http://hdl.handle.net/10967/190
http://dx.doi.org/10.15152/QDB.190
Date: 2017-03-23


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