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<p>This paper delves into the intricate relationship between the hemihexaphyrazine (<i>HHP</i>) network and its connection to topological indices and the heat of formation. By analyzing a variety of topological indices, we utilize a curve fitting model to predict and clarify the heat of formation–a vital thermodynamic factor that impacts the stability and reactivity of <i>HHP</i>. Through a detailed correlation analysis, we uncover significant trends and relationships linking the heat of formation with topological indices like the Gutman, Randić, and Zagreb indices. We have found that the curve fitting model not only allows us to predict the results with high accuracy (the values of <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11696_2025_4304_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="21" /> </InlineMediaObject> <EquationSource Format="TEX">\(R^2\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>R</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation> are above 0.98 in some cases) but also helps us to get a better idea about the molecular interactions within the <i>HHP</i> network. The reverse redefined Zagreb indices have been found to be the most predictively reliable of the tested ones. In addition, enthalpy measures were calculated in relation to each index, as a way to understand the complexity of structure, and showed steadfast growth trends in line with the growth of a network. These analyses illustrate the accuracy with which thermodynamic properties have been reproduced using the model; it outlines the relevance that topological descriptors have received in computational chemistry so far. By analyzing these results, several insights were obtained into the energetic behavior of hemihexaphyrazine network and are pointed out with respect to which role graph theoretical approaches so far played for the development of material science and chemical engineering.</p>

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Investigating topological indices and heat of formation for hemihexaphyrazine using a curve fitting approach

  • 期刊论文

  • 发表日期：

    2025年8月25日

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  • Iqra Siddique,
  • Sarfraz Ahmad,
  • Muhammad Kamran Siddiqui

摘要

This paper delves into the intricate relationship between the hemihexaphyrazine (HHP) network and its connection to topological indices and the heat of formation. By analyzing a variety of topological indices, we utilize a curve fitting model to predict and clarify the heat of formation–a vital thermodynamic factor that impacts the stability and reactivity of HHP. Through a detailed correlation analysis, we uncover significant trends and relationships linking the heat of formation with topological indices like the Gutman, Randić, and Zagreb indices. We have found that the curve fitting model not only allows us to predict the results with high accuracy (the values of \(R^2\) R 2 are above 0.98 in some cases) but also helps us to get a better idea about the molecular interactions within the HHP network. The reverse redefined Zagreb indices have been found to be the most predictively reliable of the tested ones. In addition, enthalpy measures were calculated in relation to each index, as a way to understand the complexity of structure, and showed steadfast growth trends in line with the growth of a network. These analyses illustrate the accuracy with which thermodynamic properties have been reproduced using the model; it outlines the relevance that topological descriptors have received in computational chemistry so far. By analyzing these results, several insights were obtained into the energetic behavior of hemihexaphyrazine network and are pointed out with respect to which role graph theoretical approaches so far played for the development of material science and chemical engineering.