Computer code to predict the heat of explosion of high energy materials

Area of Science:

• Computational chemistry
• Materials science
• Chemical engineering

Background:

• High energy materials (HEMs) require accurate thermodynamic parameter prediction for safety and performance.
• Existing methods for predicting heat of explosion often rely on experimental data.
• Computational approaches offer a pathway to predict HEM properties from molecular structure.

Purpose of the Study:

• To develop and validate a new computational approach for predicting the heat of explosion (ΔH(e)) of HEMs.
• To integrate this new algorithm into the LOTUSES software for practical application.
• To demonstrate the utility of this method for hazard assessment of energetic materials.

Main Methods:

• Utilizing a computational approach based on molecular structure to calculate thermochemical changes during HEM explosion.
• Developing a new algorithm requiring minimal input parameters.
• Incorporating the algorithm into LOTUSES (version 1.5) software.
• Performing linear regression analysis to compare computed and experimental values.

Main Results:

• The LOTUSES software predicts various HEM characteristics, including balanced explosion reactions and detonation velocity.
• The new computational method accurately predicts the heat of explosion (ΔH(e)) without experimental data.
• A high correlation coefficient (R²=0.9721) was achieved, indicating strong agreement between computed and experimental heat of explosion values.
• The linear regression equation y=0.9262x+101.45 describes the relationship between computed and experimental data.

Conclusions:

• The developed computational approach provides reliable predictions of HEM heat of explosion, comparable to experimental results.
• This computer-aided design is valuable for predicting HEM performance and designing novel energetic molecules.
• The LOTUSES software, with its new algorithm, facilitates rapid hazard assessment for energetic materials.