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Predicting the NO_3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors

机译:用理论分子描述符预测有机污染物的NO_3自由基对流层可降解性

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摘要

The rate constant for the nighttime degradation of 114 heterogeneous organic compounds, through reaction with nitrate radicals in the troposphere, is predicted here by quantitative structure-activity relationships modelling. The multiple linear regression approach is based on a variety of theoretical molecular descriptors, selected by the genetic algorithms-variable subset selection procedure. The proposed model, calculated on a limited subset of compounds selected by a D-optimal experimental design and checked for reliability and robustness, has good predictivity, verified by internal (Q_(LMO)~2 = 89.6%) and "external" validation (Q_(EXT)~2 = 95.7%). The model applicability domain was always verified by the leverage approach in order to propose reliable predicted data. The average root-mean square error for the prediction of log k_(NO3) was 0.57, similar to (and even smaller than) the typical experimental error range.
机译:通过定量的结构-活性关系模型,可以预测114种异质有机化合物通过与对流层中的硝酸根基反应在夜间降解的速率常数。多元线性回归方法基于通过遗传算法-可变子集选择程序选择的各种理论分子描述符。所提出的模型是通过D最佳实验设计选择的化合物的有限子集进行计算并检查其可靠性和鲁棒性的,具有良好的预测性,并通过内部(Q_(LMO)〜2 = 89.6%)和“外部”验证( Q_(EXT)〜2 = 95.7%)。始终通过杠杆方法验证模型的适用性,以提出可靠的预测数据。预测log k_(NO3)的平均均方根误差为0.57,类似于(甚至小于)典型的实验误差范围。

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