Experimental diffusivity of energetic compounds determined by peak parking

Area of Science:

• Analytical Chemistry
• Physical Chemistry
• Chemical Engineering

Background:

• Accurate diffusivity data is crucial for understanding chemical transport and reaction kinetics, especially for energetic materials.
• Existing computational methods for diffusivity estimation can be inaccurate for complex organic molecules and specific solvent systems.
• Experimental determination of diffusivity provides essential empirical data for validating and refining theoretical models.

Purpose of the Study:

• To experimentally determine the diffusion coefficients of several explosive and complex organic compounds.
• To validate a peak parking methodology using High Performance Liquid Chromatography (HPLC) for diffusivity measurements.
• To compare experimental diffusivity values with computationally estimated values and assess discrepancies.

Main Methods:

• Employed a peak parking methodology utilizing High Performance Liquid Chromatography (HPLC) with stop-flow capabilities.
• Measured diffusivity by analyzing band broadening caused by chemical diffusion within the HPLC column.
• Determined an obstruction factor by comparing benzene diffusion in methanol on a C18 column to published capillary column data.

Main Results:

• Experimentally derived diffusivities for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), 3-nitro-1,2,4-triazol-5-one (NTO), nitroguanidine (NQ), pyrimidine-2-carboxylic acid, and streptomycin were reported.
• Empirical diffusivities showed significant percent differences compared to computational estimates, averaging 142% (RDX), 174% (NTO), 27% (NQ), 85% (pyrimidine-2-carboxylic acid), and 33% (streptomycin).
• Observed discrepancies included NTO having higher experimental diffusivities and RDX and streptomycin having lower experimental diffusivities than computational predictions.

Conclusions:

• The peak parking method provides a viable experimental approach for determining diffusivities of complex organic and explosive compounds.
• The method is particularly useful for compounds not easily modeled computationally or for solvents lacking established association coefficients.
• Experimental data highlights limitations of current computational models for certain molecules and emphasizes the need for empirical validation.