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

机译:COSMO-RS训练碎片贡献模型预测短链氯化石蜡Congeners的分配系数

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摘要

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 C_4 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 (K_(ow)), air-water (K_(aw)), and octanol-air (K_(oa)) partition coefficients of SCCP congeners with an accuracy of 0.1-0.3 log units root-mean-squared errors. The FCM predictions for K_(ow) 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 K_(ow) ranges of industrial CP mixtures. As an application of the developed FCMs, the predicted K_(aw) and K_(oa) were plotted to evaluate the bioaccumulation potential of each SCCP congener group.
机译:氯化石蜡(CPS)是具有不同链长和氯化图案的多氯N-烷烃的高度复杂混合物。关于个体同源物的物理化学性质的知识是有限的,但需要了解他们的环境命运和潜在风险。这项工作使用了一种复杂但时间苛刻的量子化学基础的方法Cosmo-RS和快速运行的片段贡献方法,以实现大量短链氯化石蜡(SCCP)Congeners的分配系数预测。使用CP分子中长度为C_4的分子片段开发片段贡献模型(FCMS)作为训练数据的解释变量和COSMO-RS计算的分区系数。得到的FCM可以快速提供辛醇 - 水(K_(OW)),空水(K_(AW))和SCCP Congeners的辛醇 - 空气(K_(OA))分区系数的COSMO-RS预测0.1-0.3日志单位根均方误差。 K_(OW)的FCM预测与1个日志单位内单个构成异构体的实验值同意。计算每个SCCP Congener组的分配系数分布,其成功再现了工业CP混合物的实验日志K_(OW)范围。作为开发的FCMS的应用,绘制了预测的K_(AW)和K_(OA)以评估每个SCCP Congener组的生物积累潜力。

著录项

  • 来源
    《Environmental Science & Technology》 |2020年第23期|15162-15169|共8页
  • 作者

    Satoshi Endo; Jort Hammer;

  • 作者单位

    Center for Health and Environmental Risk Research National Institute for Environmental Studies (NIES) 305-8506 Tsukuba Ibaraki Japan;

    Center for Health and Environmental Risk Research National Institute for Environmental Studies (NIES) 305-8506 Tsukuba Ibaraki Japan;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 22:37:04

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