AI Article Synopsis

  • Understanding the stability of chemical bonds in energetic compounds is crucial for their design and safety, especially focusing on nitro groups that impact thermal and mechanical stability.
  • The intrinsic bond strength index (IBSI) offers a cost-effective and accurate way to predict bond stability and thermal properties, achieving high correlation with experimental data comparable to more complex quantum chemistry methods.
  • The study uses various DFT methods and software to analyze bond connections and steric hindrance, successfully applying IBSI to predict thermal decomposition temperatures of multiple energetic compounds.

Article Abstract

Context: The in-depth understanding about the stability of chemical bonds in energetic compounds plays a central role for molecular design and safety-related evaluations. Most energetic compounds contain nitro as explosophores, and nitro cleavage is fundamental for thermal and mechanical stability. However, the quantum chemistry approach to accurately predict energy and temperature properties related to bond stability is challenging, due to the tradeoff between computational costs and deviations. Herein, the bond orders are proposed as accurate and computational-cost efficient descriptors for predicting the chemical bond stability and thermal-resistant properties. The intrinsic bond strength index (IBSI) demonstrates the best prediction for experimental homolytic bond dissociation energies (R > 0.996), which is on par with the results from high-precision quantum chemistry methods. The effects from bond connectivity and steric hindrance hierarchy were analyzed to reveal underlying mechanisms. Additionally, the IBSI descriptors are successfully applied to predict the thermal decomposition temperatures of 24 heat-resistant energetic compounds (R = 0.995), thus validating the effectiveness for the prediction and interpretation of chemical bond stability in energetic compounds via a physical organic approach.

Methods: All DFT calculations were performed with Gaussian 09 software. To investigate the dependence of the method on functionals and basis sets, 9 DFT methods were considered (B3LYP/6-31G(d,p), B3LYP/6-311G(d,p), B3LYP/def2-TZVP, M062X/6-31G(d,p), M062X/6-311G(d,p), M062X/def2-TZVP, ωB97XD/6-31G(d,p), ωB97XD/6-311G(d,p), and ωB97XD/def2-TZVP). The bond order descriptors LBO and IBSI are obtained through the bond order analysis module in the Multiwfn software.

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Source
http://dx.doi.org/10.1007/s00894-024-05877-5DOI Listing

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