A Fractal Approach to Assess the Risks of Nitroamine Explosives

Abstract

To the best of our knowledge, this work represents the first thermal conductivity theory for fractal energetic particle groups to combine fractal and hot-spot theories. We considered the influence of the fractal dimensions of particles on their thermal conductivity and even on the sensitivity of the explosive. Based on this theory, two types of nitroamine explosives (hexahydro-1,3,5-trinitro-1,3,5-triazine [RDX] and hexanitrohexaazaisowurtzitane [HNIW]) with different sizes, size distributions, and microscale morphologies were prepared using wet milling, solvent/nonsolvent, and ridding methods. The dependence of the explosive sensitivity on the fractal characteristics of the particles was investigated. Specifically, the size distributions and scanning electron microscopy (SEM) images of the samples were used to obtain the fractal dimension (D) and surface fractal dimension (Ds), respectively, by using a least-squares method and fractal image processing software (FIPS). The mechanical sensitivity and thermal stability of the samples were characterized using mechanical sensitivity tests and differential scanning calorimetry (DSC) and were further compared with the previous results upon the investigation about HMX (octahydro-1.3.5.7-tetranitro-1,3,5,7-tetrazocine). The results indicate that the sensitivity of nitroamine explosives largely depends on the fractal dimensions of the particles. Specifically, the sample with a higher D value is more insensitive to impact action, whereas the sample with a higher Ds value is more sensitive to friction action. In addition, the sample with both higher D and Ds values has less heat release and a slower rate of thermal decomposition. All of the above observations can be attributed to the alternation of the formation of hot spots that was controlled by heat mass and thermal conductivity due to the increase of D and Ds values caused by changes in parameters such as fine particle content, specific surface area, porosity content, surface protruding points, and surface roughness. Therefore, the data in these studies were used to develop a thermal conductivity theory for fractal energetic particle groups that could be applied to the prediction of the sensitivity of energetic materials.