QSPR Analysis of Degree-Eccentricity Based Degcity Indices for Benzenoid Hydrocarbons

Authors

  • Sudhakar K B Department of Mathematics, Government Science College, Hassan-573 201, India
  • Guruprasad P S Department of Mathematics, Government First Grade College, K.G.F.-563122, India
  • M A Sriraj Department of Mathematics, Vidyavardhaka College of Engineering, Mysuru-570 002, India

DOI:

https://doi.org/10.14419/c7q76p92

Published

14-06-2026

Keywords:

Benzenoid Hydrocarbons; Degcity Indices; QSPR analysis; Topological Indices.

Abstract

This study examines the effectiveness of degree–eccentricity-based degcity indices in the QSPR analysis of benzenoid hydrocarbons. These indices incorporate both vertex degree and eccentricity to capture structural features of molecular graphs. Experimental physicochemical properties such as boiling point, molecular weight, and critical parameters are analyzed using linear regression models. The results indicate that the fourth degcity index shows the strongest predictive performance, while the first, second, and sixth indices also provide good correlations. Comparison with standard topological indices shows strong agreement, particularly with eccentricity-based measures. Overall, degcity indices demonstrate high predictive accuracy and strong discriminating capability for molecular structures.

References

[1] J. R. Dias, Handbook of Polycyclic Hydrocarbons, Part A: Benzenoid Hydrocarbons, Elsevier, (1986).

[2] S. Fajtlowicz, “On conjectures of Graffiti-II”, Congressus Numerantium, Vol.60, (1987), pp.187–197.

[3] B. Furtula and I. Gutman, “A forgotten topological index”, Journal of Mathematical Chemistry, Vol.53, No.4, (2015), pp.1184–1190.

[4] I. Gutman and S. J. Cyvin, Introduction to the Theory of Benzenoid Hydrocarbons, Springer Science & Business Media, (2012).

[5] I. Gutman and N. Trinajstic, “Graph theory and molecular orbitals. Total ´ π-electron energy of alternant hydrocarbons”, Chemical Physics Letters,

Vol.17, (1972), pp.535–538.

[6] S. Hayat, “Distance-based graphical indices for predicting thermodynamic properties of benzenoid hydrocarbons with applications”, Computational

Materials Science, Vol.230, (2023), pp.112492.

[7] R. B. Jummannaver, S. D. Shindhe and B. Deshpande, “Modeling physico-chemical properties of benzenoid hydrocarbons using topological indices of

molecular graphs”, Advances and Applications in Mathematical Sciences, Vol.20, No.10, (2021), pp.2299–2311.

[8] R. Kanabur and V. Shigehalli, “QSPR analysis of degree-based topological indices with physical properties of benzenoid hydrocarbons”, General

Letters in Mathematics, Vol.2, No.3, (2017), pp.150–169.

[9] E. V. Konstantinova, “The discrimination ability of some topological and information distance indices for graphs of unbranched hexagonal systems”,

Journal of Chemical Information and Computer Sciences, Vol.36, No.1, (1996), pp.54–57.

[10] G. Kuriachan and A. Parthiban, “Prediction of π-electronic energy and physical properties of benzenoid hydrocarbons using domination degree based

entropies”, Scientific Reports, Vol.15, No.1, (2025), pp.11359.

[11] V. Lokesha, Suvarna and K. Zeba Yasmeen, “QSPR analysis of certain degree based topological indices of benzenoid hydrocarbons”, Journal of Xi’an

University of Architecture and Technology, Vol.XIII, No.3, (2021), pp.372–379.

[12] S. Mondal, A. Dey, N. De and A. Pal, “QSPR analysis of some novel neighbourhood degree-based topological descriptors”, Complex & Intelligent

Systems, Vol.7, No.2, (2021), pp.977–996.

[13] M. Randic, “Comparative regression analysis. Regressions based on a single descriptor”, ´ Croatica Chemica Acta, Vol.66, No.2, (1993), pp.289–312.

[14] P. Sarkar, A. Pal and S. Mondal, “On some exponential structure descriptors and their applications to benzenoid hydrocarbons”, International Journal of

Quantum Chemistry, Vol.125, No.11, (2025), pp.e70061.

[15] V. Sharma, R. Goswami and A. Madan, “Eccentric connectivity index: A novel highly discriminating topological descriptor for structure-property and

structure-activity studies”, Journal of Chemical Information and Computer Sciences, Vol.37, No.2, (1997), pp.273–282.

[16] K. B. Sudhakara, P. S. Guruprasad and M. A. Sriraj, “Prediction potential of degcity indices for physico-chemical properties of polycyclic aromatic

hydrocarbons: A QSPR study”, Biointerface Research in Applied Chemistry, Vol.13, No.6, (2023), pp.599.

[17] D. Vukicevi ˇ c and B. Furtula, “Topological index based on the ratios of geometrical and arithmetical means of end-vertex degrees of edges”, ´ Journal of

Mathematical Chemistry, Vol.46, No.4, (2009), pp.1369–1376.

[18] D. Vukicevi ˇ c and A. Graovac, “Note on the comparison of the first and second normalized Zagreb eccentricity indices”, ´ Acta Chimica Slovenica, Vol.57,

(2010), pp.524–528.

[19] B. Zhou and N. Trinajstic, “On a novel connectivity index”, ´ Journal of Mathematical Chemistry, Vol.46, No.4, (2009), pp.1252–1270

How to Cite

K B, S., P S, G., & Sriraj, M. A. (2026). QSPR Analysis of Degree-Eccentricity Based Degcity Indices for Benzenoid Hydrocarbons. International Journal of Scientific World, 12(1), 22-31. https://doi.org/10.14419/c7q76p92

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