Abstract
AbstractA series of quantitative structure‐retention relationship models were developed to predict gas chromatographic relative retention times (GC‐RRTs) for 209 polybrominated diphenyl ether (PBDE) congeners on 10 stationary phases. A genetic algorithm with twofold leave‐multiple‐out cross validation (LMOCV) was used to select optimal subsets from large‐size molecular descriptors. Overall multiple‐linear regression fitting correlation coefficients (R2) are greater than 0.988, except for the CP‐Sil 19 column, in which QLMOCV2 (correlation coefficient of LMOCV), QLOOCV2 (correlation coefficient of leave‐one‐out cross validation, LOOCV), and Rpre2 (correlation coefficients of prediction set) are larger than 0.98. The excellent statistical parameters reveal that the models are robust and have high internal and external predictive capability. According to the descriptors for constructing the models, the GC‐RRTs in various stationary phases are highly dependent on distances among atoms, branches of molecules, and molecular properties. PBDE congeners with 1, 9, and 10 bromines are major outliers based on the results of the application domain.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.