Literature DB >> 33207873

Predicting Partition Coefficients of Short-Chain Chlorinated Paraffin Congeners by COSMO-RS-Trained Fragment Contribution Models.

Satoshi Endo1, Jort Hammer1.   

Abstract

Chlorinated paraffins (CPs) are highly complex mixtures of polychlorinated n-alkanes with differing chain lengths and chlorination patterns. Knowledge on physicochemical properties of individual congeners is limited but needed to understand their environmental fate and potential risks. This work used a sophisticated but time-demanding quantum chemically based method COSMO-RS and a fast-running fragment contribution approach to enable prediction of partition coefficients for a large number of short-chain chlorinated paraffin (SCCP) congeners. Fragment contribution models (FCMs) were developed using molecular fragments with a length of up to C4 in CP molecules as explanatory variables and COSMO-RS-calculated partition coefficients as training data. The resulting FCMs could quickly provide COSMO-RS predictions for octanol-water (Kow), air-water (Kaw), and octanol-air (Koa) partition coefficients of SCCP congeners with an accuracy of 0.1-0.3 log units root-mean-squared errors. The FCM predictions for Kow agreed with experimental values for individual constitutional isomers within 1 log unit. The distribution of partition coefficients for each SCCP congener group was computed, which successfully reproduced experimental log Kow ranges of industrial CP mixtures. As an application of the developed FCMs, the predicted Kaw and Koa were plotted to evaluate the bioaccumulation potential of each SCCP congener group.

Entities:  

Year:  2020        PMID: 33207873     DOI: 10.1021/acs.est.0c06506

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  Congener-specific partition properties of chlorinated paraffins evaluated with COSMOtherm and gas chromatographic retention indices.

Authors:  Jort Hammer; Hidenori Matsukami; Satoshi Endo
Journal:  Sci Rep       Date:  2021-02-24       Impact factor: 4.379

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.