Understanding and predicting the diffusivity of organic compounds in polydimethylsiloxane material for passive sampler applications using a simple quantitative structure–property relationship model. (17th April 2018)

• Record Type: Journal Article
• Authors: Belles, Angel; Franke, Christine; Alary, Claire; Aminot, Yann; Readman, James W.
• Is Part Of: Environmental toxicology and chemistry. Volume 37:Number 5(2018)
• Page Start: 1291
• Page End: 1300
• Publication Date: 2018-04-17
• Subjects: Passive sampler -- Contaminants -- Quantitative structure–activity relationships -- Analytical chemistry; Pollution -- Environmental aspects -- Periodicals; Environmental chemistry -- Periodicals; 615.902
• DOI: 10.1002/etc.4101
• Languages: English
• ISSNs: 0730-7268

Abstract

Abstract: The diffusivity of 145 compounds in polydimethylsiloxane (PDMS) material was determined in the laboratory using a film stacking technique. The results were pooled with available literature data, providing a final data set of 198 compounds with diffusivity ( D PDMS ) spanning over approximately 5 log units. The principal variables controlling the diffusivity of penetrants were investigated by comparing D PDMS within and between different homologous series. The dipole moment, molecular size, and flexibility of penetrants appear to be the most prevalent factors controlling a compound's diffusivity. A nonlinear quantitative structure–property relationship is proposed using as predicting variables the molecular volume, the number of rotatable bonds, the topological polar surface area, and the number of O and N atoms. The final relationship has a correlation coefficient of R 2 = 0.81 and a mean absolute error of 0.26 m 2 s −1 (log unit), approaching the average error for the experimentally determined values (0.12 m 2 s −1 ). The model, based on a heuristic approach, is ready for use by analytical chemists with no specific background in theoretical chemistry (notably for passive sampler development). Environ Toxicol Chem 2018;37:1291–1300. © 2018 SETAC