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Chemometric Modelling of Heat Release Capacity, Total Heat Release and Char Formation of Polymers to Assess Their Flammability Characteristics
Molecular Informatics ( IF 3.6 ) Pub Date : 2020-05-28 , DOI: 10.1002/minf.202000030
Pathan Mohsin Khan 1 , Kunal Roy 2
Affiliation  

The quantitative structure-property relationship (QSPR) approach has widely been used to predict several physicochemical properties of materials employing the information obtained from their chemical structures (numerical descriptors). In the present work, we have generated three individual QSPR models for three different endpoints for a large number of polymers in order to determine their fire retardant property such as heat release capacity, total heat release, and %Char, using the only two-dimensional descriptors with definite physicochemical meaning. Relevant subsets of descriptors were selected employing a genetic algorithm approach; subsequently, the selected descriptors were utilised for the identification of the best combination of the variables for the model generation, while the final models were developed employing the partial least squares (PLS) regression algorithm. The generated models were rigorously validated using various internationally accepted internal and external validation metrics. All the models showed promising statistical quality in terms of determination coefficient urn:x-wiley:18681743:media:minf202000030:minf202000030-math-0001 (0.802, 0.842 and 0.826), cross-validated leave-one-out Q2 (0.759, 0.810 and 0.752) and predictive R2pred or Q2ext (0.810, 0.900 and 0.847) for HRC (nTraining=62, nTest=28), THR (nTraining=64, nTest=21) and %char (nTraining=49, nTest=21) datasets, respectively. All the certified models were used for prediction of flammability characteristics of 37 external set compounds, and further, the quality of prediction was determined by using the PRI software tool. The final models of HRC, THR and %Char formation of polymers may be useful to predict the flammability characteristics of polymers quickly before their synthesis and used as a better alternative approach to the experimental testing of flammability of polymers.

中文翻译:

聚合物的放热能力、总放热和炭形成的化学计量学模型,以评估其可燃性特性

定量结构-性质关系 (QSPR) 方法已广泛用于利用从材料的化学结构(数值描述符)获得的信息来预测材料的几种物理化学性质。在目前的工作中,我们为大量聚合物的三个不同端点生成了三个单独的 QSPR 模型,以确定它们的阻燃性能,例如放热能力、总放热和 %Char,使用唯一的二维具有明确物理化学意义的描述符。使用遗传算法方法选择描述符的相关子集;随后,选定的描述符被用于识别模型生成的变量的最佳组合,而最终模型是使用偏最小二乘 (PLS) 回归算法开发的。使用各种国际公认的内部和外部验证指标对生成的模型进行了严格验证。所有模型在决定系数方面都显示出有希望的统计质量骨灰盒:x-wiley:18681743:媒体:minf202000030:minf202000030-math-0001(0.802、0.842 和 0.826)、交叉验证留一法 Q 2(0.759、0.810 和 0.752)和 HRC 的预测 R 2 pred或 Q 2 ext(0.810、0.900 和 0.847)(n训练=62,n测试=28),THR(n训练=64,n测试=21)和 %char(n训练=49,n测试=21)数据集,分别。所有经认证的模型均用于预测 37 种外置化合物的可燃性特征,并进一步使用 PRI 软件工具确定预测质量。聚合物的 HRC、THR 和 %Char 形成的最终模型可用于在聚合物合成之前快速预测聚合物的可燃性特征,并用作聚合物可燃性实验测试的更好替代方法。
更新日期:2020-05-28
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