es101181g_si_002.pdf (23.63 kB)
Prediction of Aqueous Solubility, Vapor Pressure and Critical Micelle Concentration for Aquatic Partitioning of Perfluorinated Chemicals
journal contribution
posted on 2011-10-01, 00:00 authored by Barun Bhhatarai, Paola GramaticaThe majority of perfluorinated chemicals (PFCs) are of increasing
risk to biota and environment due to their physicochemical stability,
wide transport in the environment and difficulty in biodegradation.
It is necessary to identify and prioritize these harmful PFCs and
to characterize their physicochemical properties that govern the solubility,
distribution and fate of these chemicals in an aquatic ecosystem.
Therefore, available experimental data (10−35 compounds) of
three important properties: aqueous solubility (AqS), vapor pressure
(VP) and critical micelle concentration (CMC) on per- and polyfluorinated
compounds were collected for quantitative structure−property
relationship (QSPR) modeling. Simple and robust models based on theoretical
molecular descriptors were developed and externally validated for
predictivity. Model predictions on selected PFCs were compared with
available experimental data and other published in silico predictions.
The structural applicability domains (AD) of the models were verified
on a bigger data set of 221 compounds. The predicted properties of
the chemicals that are within the AD, are reliable, and they help
to reduce the wide data gap that exists. Moreover, the predictions
of AqS, VP, and CMC of most common PFCs were evaluated to understand
the aquatic partitioning and to derive a relation with the available
experimental data of bioconcentration factor (BCF).
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AqSBCFbioconcentration factorphysicochemical stabilitypolyfluorinated compounds221 compoundsperfluorinated chemicalsModel predictionsmicelle concentrationmodelCritical Micelle Concentrationapplicability domainsCMCdata gapsolubilityVPPerfluorinated ChemicalsThe majorityVapor PressurePFCADAquatic Partitioningsilico predictionsQSPRphysicochemical propertiesAqueous Solubility
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