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<p>This study explores how graph-based models can be used to predict key electronic properties of molecular structures, particularly benzenoid hydrocarbons as hexagonal systems. By focusing on temperature-related indices that reflect how atoms are connected within a molecule, the authors apply an optimization approach to identify the most optimal variants of these indices. The results show that these refined descriptors offer strong potential for accurately estimating total <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_17791_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">\(\pi\)</EquationSource> </InlineEquation>-electron energy. This work resolves two open questions in the field and supports the broader application of such indices in chemical property prediction and materials design.</p>

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Optimization model for predicting quantum theoretic characteristics of hexagonal systems using temperature dependent graph theoretic estimators

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月2日

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  • Yunji Huang,
  • Sakander Hayat,
  • Noorazam Tuah,
  • Asad Khan,
  • Yubin Zhong,
  • Mohammed J. F. Alenazi

摘要

This study explores how graph-based models can be used to predict key electronic properties of molecular structures, particularly benzenoid hydrocarbons as hexagonal systems. By focusing on temperature-related indices that reflect how atoms are connected within a molecule, the authors apply an optimization approach to identify the most optimal variants of these indices. The results show that these refined descriptors offer strong potential for accurately estimating total \(\pi\) -electron energy. This work resolves two open questions in the field and supports the broader application of such indices in chemical property prediction and materials design.