<p>In this article, we present the concept of extended Seidel energy by employing a generalized extended matrix to study various molecular properties, including the Kovats retention index, boiling point, enthalpy of formation, entropy, acentric factor, and octanol-water partition coefficient. Our research broadens the scope of energy matrices in graph theory, with a particular emphasis on Sombor energy, reduced Sombor energy, average Sombor energy, Banhatti Sombor energy and reduced Banhatti Sombor energy. We examined the correlation of these graph-based energy descriptors with the thermodynamic properties of Benzenoid hydrocarbons (BHC), uncovering strong relationships between these indices and different molecular attributes. These results provide valuable insights into the predictive potential of graph energies in modeling the thermodynamic behavior of polycyclic aromatic hydrocarbons.</p>

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Investigating Seidel energies and thermodynamic properties of benzenoid hydrocarbons through regression models

  • Rashad Ismail,
  • Hafiz Muhammad Bilal,
  • Kiran Naz,
  • Sarfraz Ahmad,
  • Muhammad Kamran Siddiqui,
  • Mustafa Ahmed Ali

摘要

In this article, we present the concept of extended Seidel energy by employing a generalized extended matrix to study various molecular properties, including the Kovats retention index, boiling point, enthalpy of formation, entropy, acentric factor, and octanol-water partition coefficient. Our research broadens the scope of energy matrices in graph theory, with a particular emphasis on Sombor energy, reduced Sombor energy, average Sombor energy, Banhatti Sombor energy and reduced Banhatti Sombor energy. We examined the correlation of these graph-based energy descriptors with the thermodynamic properties of Benzenoid hydrocarbons (BHC), uncovering strong relationships between these indices and different molecular attributes. These results provide valuable insights into the predictive potential of graph energies in modeling the thermodynamic behavior of polycyclic aromatic hydrocarbons.