摘要
根据硝基类炸药分子内氢键、分子结构、对称性、氧平衡OB100、活性指数F、"拥挤性"等分子结构描述符,采用逐步回归法以及支持向量回归对156个硝基炸药的撞击感度进行了建模研究,并利用8个检验样本进行了对比。结果表明,OB100和F均与lg H50呈现负相关,且同一碳原子上化学基团数越多,感度越高;引发键α-CH与α-OH会引起硝基类炸药H50的降低;炸药中单位质量氢键越多,炸药感度越低;SVR模型对训练样本的建模能力比多元线性回归模型强,对检验样本的预测准确率也比多元线性回归模型高。SVR模型能够相对准确地预测硝基类炸药的撞击感度,在设计/合成钝感高能炸药时可起理论指导作用。
Based on the molecular structural descriptors as follows： intra-molecular hydrogen bond,molecular structure,symmetry,oxygen balance,activity index,crowded degree and so on,the step wise regression（SWR） and support vector regression（SVR） approaches were proposed to model the relationship between the descriptors and the impact sensitivity for 156 nitro energetic compounds.The SWR and SVR models were further validated and compared by using 8 independent test samples.The results reveal that lgH50 exhibits a strong negative correlation with the oxygen balance（OB100） and the activity index（F）,the more the chemical groups linked with a carbon atom,the greater the impact sensitivity of the explosive;that the trigger bonds of α-CH or α-OH can cause H50 to decrease;and that the more the intra-molecular hydrogen bonds in unit mass of explosive,the lower the impact sensitivity.The modeling ability of the SVR approach surpasses that of the multiple linear regression（MLR） approach and its prediction accuracy is also superior to that of the MLR approach,which was validated by using the identical training set and test set.The above investigated results demonstrate that the SVR approach is an effective tool to predict the impact sensitivity of explosives and can provide an important theoretical guidance for the design/synthesis of insensitive high energetic explosive.
出处
《爆炸与冲击》
EI
CAS
CSCD
北大核心
2013年第1期79-84,共6页
Explosion and Shock Waves
基金
中央高校基本科研业务费专项项目(CDJXS10101107)
教育部新世纪优秀人才支持计划项目(NCET-07-0903)
教育部留学回国人员科研启动基金项目
重庆市自然科学基金项目(CSTC2006BB5240)
关键词
爆炸力学
撞击感度
支持向量回归
硝基类炸药
氢键
分子结构
引发键
回归分析
mechanics of explosion
impact sensitivity
support vector regression
nitro energetic compounds
intra-molecular hydrogen bond
molecular structure
trigger bond
regression analysis
