Abstract Quantitative structure-property relationship analysis, based on topological descriptors, is a significant statistical approach to assess the physical and chemical properties of compounds without requiring costly and time-consuming laboratory tests. Some graph invariants have been used in literature to distinguish the development of entropy measurements from the molecular graph of a chemical compound. Graph entropies have developed as an information-theoretic technique for analysing the structural information of a molecular graph. The feasible applications of graph entropy measures in various areas of science and mathematics have caught the attention of researchers. Therefore, this research work concentrates on the computation of some novel neighborhood degree sum-based entropy measures of silicon carbide networks namely Si<InlineEquation ID="IEq1"> <EquationSource Format="TEX">$_{2}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>2</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>C<InlineEquation ID="IEq2"> <EquationSource Format="TEX">$_{3}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>3</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>-I[p, q], Si<InlineEquation ID="IEq3"> <EquationSource Format="TEX">$_{2}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>2</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>C<InlineEquation ID="IEq4"> <EquationSource Format="TEX">$_{3}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>3</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>-II[p, q] and Si<InlineEquation ID="IEq5"> <EquationSource Format="TEX">$_{2}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>2</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>C<InlineEquation ID="IEq6"> <EquationSource Format="TEX">$_{3}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>3</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>-III[p, q]. Further, we demonstrate the graphical representations of the entropy measures and compute their numerical values of the above-mentioned chemical structures comparison among the considered entropy measures. Additionally, using cubic regression models, the QSPR analysis is performed to establish the correlation between the entropy measures and the cohesive energy of the considered silicon carbide networks. Neighborhood entropy measures establish a significant correlation with the cohesive energies of the networks. Graphic abstract

Neighborhood degree sum-based entropy measures of some silicon carbide networks

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发表日期：

2025年12月18日

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Virendra Kumar,
Shibsankar Das,
Jayjit Barman

摘要

Abstract

Quantitative structure-property relationship analysis, based on topological descriptors, is a significant statistical approach to assess the physical and chemical properties of compounds without requiring costly and time-consuming laboratory tests. Some graph invariants have been used in literature to distinguish the development of entropy measurements from the molecular graph of a chemical compound. Graph entropies have developed as an information-theoretic technique for analysing the structural information of a molecular graph. The feasible applications of graph entropy measures in various areas of science and mathematics have caught the attention of researchers. Therefore, this research work concentrates on the computation of some novel neighborhood degree sum-based entropy measures of silicon carbide networks namely Si $_{2}$ $_{2}$ C $_{3}$ $_{3}$ -I[p, q], Si $_{2}$ $_{2}$ C $_{3}$ $_{3}$ -II[p, q] and Si $_{2}$ $_{2}$ C $_{3}$ $_{3}$ -III[p, q]. Further, we demonstrate the graphical representations of the entropy measures and compute their numerical values of the above-mentioned chemical structures comparison among the considered entropy measures. Additionally, using cubic regression models, the QSPR analysis is performed to establish the correlation between the entropy measures and the cohesive energy of the considered silicon carbide networks. Neighborhood entropy measures establish a significant correlation with the cohesive energies of the networks.

Graphic abstract