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Combining mixing rules with QSPR models for pure chemicals to predict the flash points of binary organic liquid mixtures

机译:将纯化学药品的混合规则与QSPR模型结合起来,以预测二元有机液体混合物的闪点

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摘要

Flash point is a key property of liquids to evaluate the safety of industrial processes. Mixing rules are commonly used to calculate the flash point of liquid mixtures, but they need knowledge of the ones of pure compounds. Theoretical methods notably based on quantitative structure property relationships (QSPR) already exist to predict flash points of pure compounds. So, in this paper, direct combination of these two types of approaches was investigated to achieve predictions even when the flash points of pure compounds were unknown. Three relevant mixing rules and four QSPR models, based on simple constitutional descriptors, were considered. Based on a data. set of 284 experimental data of binary mixtures extracted from literature, two reliable combinations were highlighted. The most accurate one reached an error in prediction of only 2.9 degrees C but needed knowledge of the boiling point and Antoine's coefficients of each component of the mixture. A new full-predictive method was in particular proposed with also a low error in prediction (4.4 degrees C), requiring only knowledge of the molecular structure of each pure compound and molar fraction of the mixture. Errors in each predictive method keep quite reasonable against expected accuracies of direct measurements of flash point of binary mixtures. (C) 2015 Elsevier Ltd. All rights reserved.
机译:闪点是液体评估工业过程安全性的关键特性。混合规则通常用于计算液体混合物的闪点,但它们需要了解纯化合物。已经特别存在基于定量结构性质关系(QSPR)的理论方法来预测纯化合物的闪点。因此,在本文中,研究了这两种类型方法的直接组合以实现预测,即使当纯化合物的闪点未知时也是如此。基于简单的构造描述符,考虑了三个相关的混合规则和四个QSPR模型。基于数据。从文献中提取的284种二元混合物的实验数据集,突出显示了两种可靠的组合。最准确的一个预测误差只有2.9摄氏度,但需要了解混合物的每种成分的沸点和安托万系数。特别提出了一种新的全预测方法,该方法的预测误差也很小(4.4摄氏度),只需要了解每种纯化合物的分子结构和混合物的摩尔分数即可。相对于直接测量二元混合物闪点的预期精度,每种预测方法中的误差都相当合理。 (C)2015 Elsevier Ltd.保留所有权利。

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