Crystal density predictions for nitramines based on quantum chemistry.

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Engineering

Background:

• Accurate prediction of crystalline densities is crucial for designing novel energetic materials.
• Existing computational methods vary in accuracy and efficiency for predicting material properties.

Purpose of the Study:

• To establish an efficient and accurate computational method for predicting crystalline densities of energetic materials.
• To evaluate the performance of different quantum chemical methods and basis sets for this prediction.

Main Methods:

• Employed density functional theory (DFT) with multiple basis sets (6-31G(**) to 6-311++G(**)) and semiempirical molecular orbital (MO) methods.
• Calculated molecular volumes and densities for a series of energetic nitramines (acyclic, monocyclic, polycyclic/cage).
• Compared calculated values against experimental data to establish linear correlations.

Main Results:

• Larger basis sets increased computational time, molecular volume, and decreased predicted density.
• Semiempirical MO methods systematically overestimated experimental densities.
• B3LYP/6-31G(**) demonstrated the highest accuracy and cost-effectiveness for predicting solid-state densities.

Conclusions:

• The B3LYP/6-31G(**) method provides an accurate and economical approach for predicting energetic material densities.
• This computational strategy can guide the molecular design and screening of novel high-energy-density materials (HEDMs).
• Understanding the impact of basis set size on computational cost and accuracy is essential.