4.4 Article

High-Precision Density Measurements of Energetic Materials for Quality Assessment

Journal

PROPELLANTS EXPLOSIVES PYROTECHNICS
Volume 46, Issue 3, Pages 413-427

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/prep.202000272

Keywords

ANOVA; CL-20; Density; Gas pycnometry; HMX

Funding

  1. German Ministry of Defense

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This study used helium pycnometry to measure and analyze the density of CL-20/HMX cocrystals and phase-stabilized ammonium nitrate, developing a method to accurately assess the quality and significance of the data. By quantifying sources of error and utilizing confidence intervals, a repeatability of 0.015% was achieved, with the ability to differentiate between samples with a certainty of 0.05%.
Even though helium pycnometry is considered a very precise method of density determination, its use to analyse factors influencing crystal quality (e. g. solvent inclusions, amorphous states, crystal defects horizontal ellipsis ) is limited due to the unknown inherent accuracy of the method. Previous studies have attempted to identify the best possible accuracy of helium pycnometry. However, no robust method has been proposed to validate even the precision obtained. This means that the often occurring, seemingly random density deviations have never been satisfactorily explained. In this study the influencing factors on density measurements of the CL-20/HMX cocrystal and phase stabilised ammonium nitrate carried out with an AccuPyc 1340 TEC were quantified and a robust method of data analysis was developed to judge with certainty the quality and significance of the data obtained. This study shows that statistical tests such as the t-test and ANOVA cannot be utilised to differentiate between samples or repeat measurements, even though the density data points exhibit a normal distribution. By utilising confidence intervals and quantifying the three major sources of error (sampling error, change in barometric pressure during the measurement, and weight in error), a repeatability of 0.015 % was achieved and a method was developed that enables differentiation between samples with a certainty as good as 0.05 %.

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