Morphology Prediction Methods and Their Applications in Energetic Crystals

Crystal morphology can significantly impact rheological, machining, and loading properties of materials and additionally the energy and safety of energetic materials. With the development of computation technology and the increasing requirement of shape-tailored energetic crystals, a high-efficiency morphology prediction method is highly desired. Thus, a timely summary of existing crystal morphology prediction models at the microscopic level and their applications to energetic compounds is implemented in this article to set a basis for comparing their advantages and disadvantages and establishing more accurate ones. In general, these models take into account more structural and thermodynamic factors with fewer or even no kinetic factors, resulting in more or less deviation from experimental observation. Therefore, more accurate morphology prediction models are expected to be constructed in the future, in terms of both macroscopic crystallization conditions and microscopic structures as well as big data.