Prediction of Aqueous Solubility, Vapor Pressure and Critical Micelle Concentration for Aquatic Partitioning of Perfluorinated Chemicals Barun Bhhatarai Paola Gramatica 10.1021/es101181g.s002 https://acs.figshare.com/articles/journal_contribution/Prediction_of_Aqueous_Solubility_Vapor_Pressure_and_Critical_Micelle_Concentration_for_Aquatic_Partitioning_of_Perfluorinated_Chemicals/2609203 The 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). 2011-10-01 00:00:00 AqS BCF bioconcentration factor physicochemical stability polyfluorinated compounds 221 compounds perfluorinated chemicals Model predictions micelle concentration model Critical Micelle Concentration applicability domains CMC data gap solubility VP Perfluorinated ChemicalsThe majority Vapor Pressure PFC AD Aquatic Partitioning silico predictions QSPR physicochemical properties Aqueous Solubility