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作为高能材料的氮杂芳基戊唑:一项计算研究。

Azolylpentazoles as high-energy materials: a computational study.

作者信息

Hammerl Anton, Klapötke Thomas M, Schwerdtfeger Peter

机构信息

Department of Chemistry, University of Auckland, Private Bag 92019, Auckland, New Zealand.

出版信息

Chemistry. 2003 Nov 21;9(22):5511-9. doi: 10.1002/chem.200305125.

DOI:10.1002/chem.200305125
PMID:14639634
Abstract

The structures of highly energetic substituted pentazole compounds and their decomposition to give dinitrogen and the corresponding azide were investigated by ab initio quantum chemical methods. The substituents include azolyl groups (five-membered aromatic rings with different numbers of nitrogen atoms), CH(3), CN, and F. The decomposition pathway was followed for several substituted azolyl- and phenylpentazoles and compared to the known experimental and theoretical results. The NMR parameters of most of the as-yet unknown pentazole compounds were predicted. The activation energy for the decomposition increases, while the decomposition energy of the substituted pentazole decreases with greater electron-donating character of the substituent of the pentazole. Thus, anionic pentazoles are more stable than neutral pentazoles. Methylpentazole is predicted to be among the most stable pentazoles, even though it does not contain an aromatic system.

摘要

采用从头算量子化学方法研究了高能取代五唑化合物的结构及其分解生成氮气和相应叠氮化物的过程。取代基包括唑基(含不同氮原子数的五元芳环)、CH(3)、CN和F。跟踪了几种取代唑基和苯基五唑的分解途径,并与已知的实验和理论结果进行了比较。预测了大多数尚未知晓的五唑化合物的核磁共振参数。随着五唑取代基给电子能力的增强,分解的活化能增加,而取代五唑的分解能降低。因此,阴离子五唑比中性五唑更稳定。尽管甲基五唑不含有芳香体系,但预计它是最稳定的五唑之一。

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Angew Chem Int Ed Engl. 2020 Jul 20;59(30):12315-12320. doi: 10.1002/anie.202003010. Epub 2020 Apr 30.
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Applying machine learning techniques to predict the properties of energetic materials.应用机器学习技术预测含能材料的性能。
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