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A quantitative structure-property relationship (QSPR) for estimating solid material-air partition coefficients of organic compounds

机译:用于估算有机化合物的固体材料-空气分配系数的定量结构-性质关系(QSPR)

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摘要

The material-air partition coefficient (K-ma) is a key parameter to estimate the release of chemicals incorporated in solid materials and resulting human exposures. Existing correlations to estimate K-ma are applicable for a limited number of chemical-material combinations without considering the effect of temperature. The present study develops a quantitative structure-property relationship (QSPR) to predict K-ma for a large number of chemical-material combinations. We compiled a dataset of 991 measured K-ma for 179 chemicals in 22 consolidated material types. A multiple linear regression model predicts K-ma as a function of chemical's K-oa, enthalpy of vaporization ( increment H-v), temperature, and material type. The model shows good fitting of the experimental dataset with adjusted R-2 of 0.93 and has been verified by internal and external validations to be robust, stable and has good predicting ability (R-ext(2) 0.78). A generic QSPR is also developed to predict K-ma from chemical properties and temperature only (adjusted R-2 = 0.84), without the need to assign a specific material type. These QSPRs provide correlation methods to estimate K-ma for a wide range of organic chemicals and materials, which will facilitate high-throughput estimates of human exposures for chemicals in solid materials, particularly building materials and furniture.
机译:物料-空气分配系数(K-ma)是估算掺入固体材料中的化学物质的释放量以及由此导致的人体暴露的关键参数。现有的估计K-ma的相关性适用于有限数量的化学材料组合,而无需考虑温度的影响。本研究开发了一种定量的结构-性质关系(QSPR),以预测大量化学物质组合的K-ma。我们对22种合并材料类型中的179种化学物质编制了991个测得的K-ma数据集。多元线性回归模型可预测K-ma是化学品的K-oa,汽化焓(增量H-v),温度和材料类型的函数。该模型显示调整后的R-2为0.93的实验数据集拟合良好,并且已通过内部和外部验证进行了验证,具有较强的稳定性和预测能力(R-ext(2)> 0.78)。还开发了通用QSPR来仅根据化学性质和温度(调整后的R-2 = 0.84)来预测K-ma,而无需指定特定的材料类型。这些QSPR提供了相关方法来估算各种有机化学物质和材料的K-ma,这将有助于高通量估算人体对固体材料(尤其是建筑材料和家具)中化学物质的暴露量。

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