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<p>The molecular structure of a compound can be numerically characterized using a parameter known as a <i>topological index</i>, which helps analyze its graph-theoretical properties. These indices are widely used to predict the physico-chemical properties of compounds in quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) studies. In addition, graph entropy has emerged as an information-theoretic tool for capturing the structural insights of molecular graphs. In this study, QSPR analysis is performed to investigate the relationship between Nirmala indices-based molecular descriptors (including Nirmala indices and their associated entropy measures) and the thermodynamic properties, namely relative energy and cohesive energy, of silicon carbide networks <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(Si_{2}C_{3} \textit{-II}[\phi ,\psi ]\)</EquationSource> </InlineEquation> and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(Si_{2}C_{3} \textit{-III}[\phi ,\psi ]\)</EquationSource> </InlineEquation>. Polynomial regression models are employed to establish these correlations. Further, the results based on the Nirmala indices are compared with those obtained using the Randić <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\((R_{-1/2})\)</EquationSource> </InlineEquation> and Sombor <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\((\textit{SO})\)</EquationSource> </InlineEquation> indices for both silicon carbide networks. The results indicate that the Nirmala indices exhibit a strong correlation with the considered energies and provide significant predictions for the studied networks.</p>

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QSPR Analysis of Thermodynamic Properties of Silicon Carbide Networks via Nirmala Indices-Based Entropy Measures

  • 期刊论文

  • 发表日期：

    2026年5月25日

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  • Virendra Kumar,
  • Shibsankar Das

摘要

The molecular structure of a compound can be numerically characterized using a parameter known as a topological index, which helps analyze its graph-theoretical properties. These indices are widely used to predict the physico-chemical properties of compounds in quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) studies. In addition, graph entropy has emerged as an information-theoretic tool for capturing the structural insights of molecular graphs. In this study, QSPR analysis is performed to investigate the relationship between Nirmala indices-based molecular descriptors (including Nirmala indices and their associated entropy measures) and the thermodynamic properties, namely relative energy and cohesive energy, of silicon carbide networks \(Si_{2}C_{3} \textit{-II}[\phi ,\psi ]\) and \(Si_{2}C_{3} \textit{-III}[\phi ,\psi ]\) . Polynomial regression models are employed to establish these correlations. Further, the results based on the Nirmala indices are compared with those obtained using the Randić \((R_{-1/2})\) and Sombor \((\textit{SO})\) indices for both silicon carbide networks. The results indicate that the Nirmala indices exhibit a strong correlation with the considered energies and provide significant predictions for the studied networks.