Issue |
MATEC Web Conf.
Volume 67, 2016
International Symposium on Materials Application and Engineering (SMAE 2016)
|
|
---|---|---|
Article Number | 07023 | |
Number of page(s) | 7 | |
Section | Chapter 7 Materials Application and Engineering | |
DOI | https://doi.org/10.1051/matecconf/20166707023 | |
Published online | 29 July 2016 |
Prediction of Partition Coefficients of Organic Compounds for SPME/PDMS
1 Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Rd., Taichung 40402, Taiwan
2 Department of Industrial Management, ChienHsin University of Science & Technology, 229 Jianxing Rd., Taoyuan 32097, Taiwan
* Corresponding author: kpchao@mail.cmu.edu.tw
The partition coefficients of 51 organic compounds between SPME/PDMS and gas were compiled from the literature sources in this study. The effect of physicochemical properties and descriptors on the partitioning process of partition coefficients was explicated by the correlation analysis. The PDMS-gas partition coefficients were well correlated to the molecular weight of organic compounds (r = 0.832, p < 0.05). An empirical model, consisting of the molecular weight and the polarizability, was developed to appropriately predict the partition coefficients of organic compounds. The empirical model for estimating the PDMS-gas partition coefficient will contribute to the practical applications of the SPME technique.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.