2024
DOI: 10.1016/j.commatsci.2024.112944
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Predictive potential of eigenvalues-based graphical indices for determining thermodynamic properties of polycyclic aromatic hydrocarbons with applications to polyacenes

Sakander Hayat,
Hilalina Mahadi,
Seham J.F. Alanazi
et al.
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Cited by 10 publications
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“…Additionally, recent advancements in QSPR models for chemical/physical characteristics in biomolecular networks as well as nano-structures have been discussed in [44][45][46][47][48]. For the predictive potential of graphical indices for thermodynamic properties of benzenoid hydrocarbons, we refer the reader to [49][50][51][52]. For the structure-property modeling of different chemical properties of a specific set of test molecules, the reader is referred to [53][54][55].…”
Section: Application Of γ In Qspr Modelsmentioning
confidence: 99%
“…Additionally, recent advancements in QSPR models for chemical/physical characteristics in biomolecular networks as well as nano-structures have been discussed in [44][45][46][47][48]. For the predictive potential of graphical indices for thermodynamic properties of benzenoid hydrocarbons, we refer the reader to [49][50][51][52]. For the structure-property modeling of different chemical properties of a specific set of test molecules, the reader is referred to [53][54][55].…”
Section: Application Of γ In Qspr Modelsmentioning
confidence: 99%