Organic and ionic compounds containing energetic groups have wide applications in industries because they can release their stored chemical energy upon external stimuli. Many different methods have been developed in recent years for reliable prediction of the densities of these compounds at room temperature because their detonation performance depends strongly on density. This work reviews the best available predictive models for important classes of energetic organic and ionic compounds that reduce the high costs of synthesis and development of the new proposed compounds. The advantages and limitations of different methods are discussed and compared for different kinds of neutral and ionic energetic compounds. Among different approaches, quantum‐chemical methods based on molecular surface electrostatic potential (MESP) and quantitative structure‐property relationship (QSPR) approaches are attractive for scientists and industries in recent years because they can be applied for a wide range of various types of compounds. For 25 neutral energetic organic compounds and 11 energetic ionic compounds where the percentages of deviations of the outputs of quantum‐chemical MESP‐based methods are large, it is shown that the outputs of the best available QSPR methods, which were embedded in new computer code (EMDB_1.0), are more accurate.

中文翻译：

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在室温下可靠预测有机化合物以及含能基的离子液体和盐的密度的最新研究的评估

含有高能基团的有机和离子化合物在工业上具有广泛的用途，因为它们可以在外部刺激下释放其储存的化学能。近年来，已经开发出许多不同的方法来可靠地预测这些化合物在室温下的密度，因为它们的爆炸性能在很大程度上取决于密度。这项工作回顾了重要的高能有机和离子化合物类别的最佳可用预测模型，这些模型可降低合成和开发新化合物的高成本。对不同类型的中性和离子性高能化合物进行了讨论并比较了不同方法的优缺点。在不同的方法中，近年来，基于分子表面静电势（MESP）和定量结构-性质关系（QSPR）方法的量子化学方法因其可用于各种类型的化合物而吸引了科学家和工业界的注意。对于25种中性高能有机化合物和11种高能离子化合物，其中基于量子化学MESP方法的输出偏差百分比很大，这表明，最佳的QSPR方法的输出已嵌入新的计算机代码中（EMDB_1.0），则更为准确。