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Prediction of partition coefficients of organic compounds between SPME/PDMS and aqueous solution.
Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen.
Affiliation
  • Chao KP; Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Rd., Taichung 40402, Taiwan. kpchao@mail.cmu.edu.tw.
  • Lu YT; Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Rd., Taichung 40402, Taiwan. disney-14014@hotmail.com.
  • Yang HW; Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Rd., Taichung 40402, Taiwan. hwyang1224@gmail.com.
Int J Mol Sci ; 15(2): 2585-95, 2014 Feb 14.
Article in En | MEDLINE | ID: mdl-24534804
ABSTRACT
Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Organic Chemicals / Dimethylpolysiloxanes / Solid Phase Microextraction Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Int J Mol Sci Year: 2014 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Organic Chemicals / Dimethylpolysiloxanes / Solid Phase Microextraction Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Int J Mol Sci Year: 2014 Document type: Article Affiliation country: