Statistical optimization of supercritical carbon dioxide antisolvent process for preparation of HMX nanoparticles

Abstract

Taguchi robust design was employed as a statistical optimization method to optimize parameters of SAS process in order to prepare HMX nanoparticles. The current application of the Taguchi statistical optimization was highly efficient in optimizing of experimental variables which are effective in HMX particle size produced by the SAS technique. The effect of operation conditions such as: pressure, temperature, HMX concentration, solution flow rate, solvent identification, and flow rate of CO2 on the size of micronized HMX particles under various levels was investigated. The effects of these variables on the particle size of produced HMX were quantitatively evaluated by the analysis of variance (ANOVA). The results showed that the size of HMX particles prepared by SAS technique could be tuned effectively by controlling the main parameters under their optimum level. Finally, the optimum conditions for preparation of HMX nanoparticles via SAS method were proposed. The results of ANOVA showed that 3.5mol/l HMX concentration, 3ml/min solution flow rate, cyclohexanone as solvent, and 70ml/min flow rate of CO2 are optimum conditions for producing HMX nanoparticles. Experimental observations showed that under optimum conditions of SAS process, the particle size of produced HMX is about 56nm.