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QSPRs for Molecular Diffusion Coefficients in Polymeric Passive Samplers: A Comparison of Simple Molecular and Quantum‐mechanical Sigma‐moment Descriptors
Author(s) -
Lampic Alina M.,
Mackay Donald,
Parnis J. Mark
Publication year - 2019
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201800110
Subject(s) - quantitative structure–activity relationship , molecular descriptor , low density polyethylene , mean squared error , correlation coefficient , chemistry , moment (physics) , diffusion , computational chemistry , mathematics , polyethylene , thermodynamics , organic chemistry , stereochemistry , statistics , physics , classical mechanics
Linear quantitative structure‐property relationships (QSPRs) for the prediction of diffusion coefficients (log D p ) were developed for organic contaminants in two common passive sampler materials, polydimethylsiloxane (PDMS) and low‐density polyethylene (LDPE). Literature data was compiled for both PDMS and LDPE resulting in final data sets of 196 and 79 compounds, respectively. Data sets contained compounds with log D p values that ranged over about 5 log units and 3 log units for PDMS and LDPE, respectively. The quality of log D p prediction using either simple molecular descriptors or quantum‐chemical based COSMO‐RS sigma moment descriptors was compared for both materials. For PDMS, the sigma moment descriptor QSPR had the best predictivity with a correlation coefficient of R 2 =0.85 and root mean square error (RMSE) of 0.36 for log D p . The molecular descriptor QSPR resulted in a correlation coefficient of R 2 =0.78 and RMSE of 0.45 for log D p . For LDPE, the molecular descriptor QSPR had the best predictivity, with the final correlation coefficient of R 2 =0.86 and RMSE of 0.21 for log D p . The sigma moment descriptor QSPR resulted in a correlation coefficient of R 2 =0.66 and RMSE of 0.33 for log D p . The purely electronic structure‐based sigma moments are therefore shown to be a viable option for descriptors compared to the more commonly used molecular descriptors for organic contaminants in PDMS. The significance of the descriptors in each QSPR is discussed.