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

Regression model (regression)

Name	Type	n	R2	σ
Training set	training	36	0.929	0.150

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. https://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. https://doi.org/10.1360/02tb9281

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

Name	Description	Format	Size	View
2002CSB1270.qdb.zip	Model for volatile organic compounds	application/zip	7.468Kb	View/Open

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Miscellaneous publications (by other authors)
University of Tartu (Estonia), Institute of Chemistry, Molecular Technology