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A Model for Predicting the Auto-ignition Temperature using Quantitative Structure Property Relationship Approach

机译:基于定量结构性质关系法的自燃温度预测模型

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摘要

[[abstract]]While flammable materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a flammable material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of flammable materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.
机译:[[摘要]]在过程工业中使用易燃材料时,电气设备应防爆,以减少起火或爆炸的可能性。易燃材料的自燃温度(AIT)是确定这些防爆设备规格的主要特征。但是,由于实验的限制,在不同数据汇编中报告的化合物的AIT差异很大,在许多情况下,不同汇编之间的差异被发现大于300K。因此,在这方面,预测可燃材料AIT的有效方法是必不可少的。在这项研究中,通过使用定量结构性质关系(QSPR)方法建立了预测有机化合物AIT的模型。该模型是根据820种有机化合物建立的,这些化合物是从美国化学工程师学会支持的DIPPR数据库中收集的。该模型具有四个分子描述符:平均电拓扑状态,芳族比,可旋转键分数和原子中心片段。发现该模型的R值为0.900,平均误差百分比为6.0%,平均绝对误差约为36.0K。与文献中的其他作品相比,该模型是根据最大的模型建立的。数据集并给出令人满意的性能。与测量AIT的已知实验误差相比,所提出的模型还提供了AIT的合理估计。因此,提出的模型可以在合理的准确度范围内估算其AIT尚不可用的化合物的AIT。

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  • 作者

    Tsai, Fang-Yi;

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  • 年度 2014
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  • 原文格式 PDF
  • 正文语种 en
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