Due to the high experimental cost and the danger in conducting tests, there is a lack of information on the minimum ignition energy (MIE) of organic substances in the literature. On the other hand, MIE is essential information for the proper selection of explosion-proof equipment. Therefore, for application purposes, the MIE prediction model is needed. In this study, based on goodness-of-fit, robustness, predictive capability, and applicability domain (AD), ten quantitative structure-activity relationship (QSAR) models of MIE with different numbers of molecular descriptors were evaluated. A nine-descriptor model was found to have the best performance. The goodness-of-fit performance (R²), robustness (Q²_Loo), and predictive capability (Q²) of the proposed model are 0.926, 0.601, and 0.794, respectively. The average absolute error (AAE) of training data and test data is 0.080 mJ and 0.225 mJ, respectively. Compared with the existing QSAR models in the literature, this model has better performance. In addition, the AD of the proposed model is clearly discussed, which is the required element for considering the QSAR model for regulatory application purposes.

由于高昂的实验成本和进行测试的危险，文献中缺乏有关有机物质的最小点燃能（MIE）的信息。另一方面，MIE是正确选择防爆设备的重要信息。因此，出于应用目的，需要MIE预测模型。在这项研究中，基于拟合优度，鲁棒性，预测能力和适用性域（AD），评估了十种具有不同数量的分子描述符的MIE定量构效关系（QSAR）模型。发现具有九个描述符的模型具有最佳性能。拟合优度（R ²），鲁棒性（Q ² _Loo）和预测能力（Q ²建议模型的）分别为0.926、0.601和0.794。训练数据和测试数据的平均绝对误差（AAE）分别为0.080 mJ和0.225 mJ。与文献中现有的QSAR模型相比，该模型具有更好的性能。此外，将清晰讨论所提议模型的AD，这是出于监管应用目的考虑QSAR模型的必要元素。