COSMO-RS-trained fragment contribution models (FCMs) to predict partition properties of chlorinated paraffin (CP) congeners were refined and extended. The improvement includes (i) the use of an improved conformer generation method for COSMO-RS, (ii) extension of training and validation sets for FCMs up to C<sub>20</sub> congeners covering short-chain (SCCPs), medium-chain (MCCPs) and long-chain CPs (LCCPs), and (iii) more realistic simulation of industrial CP mixture compositions by using a stochastic algorithm. Extension of the training set markedly improved the accuracy of model predictions for MCCPs and LCCPs, as compared to the previous study. The predicted values of the log octanol/water partition coefficients (<i>K</i><sub>ow</sub>) for CP mixtures agreed well with experimentally determined values from the literature. Using the established FCMs, this study provided a set of quantum chemically based predictions for 193 congener groups (C<sub>10–20</sub>, Cl<sub>0–21</sub>) regarding <i>K</i><sub>ow</sub>, air/water (<i>K</i><sub>aw</sub>), and octanol/air (<i>K</i><sub>oa</sub>) partition coefficients, subcooled liquid vapor pressure (VP) and aqueous solubility (<i>S</i><sub>w</sub>) in a temperature range of 5–45 °C as well as the respective enthalpy and internal energy changes.<br><br>This is a preprint version and has not yet been peer reviewed.
Predicting Partition Coefficients of Short-Chain Chlorinated Paraffin Congeners by COSMO-RS-Trained Fragment Contribution Models
