Computing Molecular Topological Descriptors of Polymeric Networks Modeled by Sierpinski Networks

Iqbal, Muhamamd Azhar; Imran, Muhammad; Siddiqui, Muhammad Kamran; Zaighum, Muhammad Asad

doi:10.1080/10406638.2020.1783331

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…In [46], the authors discussed some matrical aspects of these networks. Recently, the authors computed various versions of degree-based topological indices of some variants of these networks using direct approach [47]. But connectivity polynomials such as the M-polynomial and generalized Zagreb Index have not been computed for this network.…”

Section: Definitionmentioning

confidence: 99%

Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Fan¹,

Munir

Hussain

et al. 2021

Complexity

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Sierpinski networks are networks of fractal nature having several applications in computer science, music, chemistry, and mathematics. These networks are commonly used in chaos, fractals, recursive sequences, and complex systems. In this article, we compute various connectivity polynomials such as M -polynomial, Zagreb polynomials, and forgotten polynomial of generalized Sierpinski networks S k n and recover some well-known degree-based topological indices from these. We also compute the most general Zagreb index known as α , β -Zagreb index and several other general indices of similar nature for this network. Our results are the natural generalizations of already available results for particular classes of such type of networks.

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Section: Definitionmentioning

confidence: 99%

Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Fan¹,

Munir

Hussain

et al. 2021

Complexity

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“…For specific complex networks various degree based topological indices have been analyzed by [18]. Various Zagreb indices have been studied for a Sierpiński triangle networks by [19]. Various authors [11,20,21] have been discussed the entropy of fractal-type networks, topological properties of Sierpiński network, and the fractal dimension of Sierpiński triangle network respectively.…”

Section: Introductionmentioning

confidence: 99%

Computing Certain Topological Indices of Silicate Triangle Fractal Network Modeled by the Sierpiński Triangle Network

2024

Contemp. Math.

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The study of Sierpiński triangle network and extended Sierpiński graph is quite interesting in the field of fractal networks. In nature, fractal networks (FN) and silicate structure networks (Sio4) play vital roles and in architecture to analyze the dimension of the above-mentioned FN and Sio4 networks it is necessary to identify the number of copies of the network. In this paper, we introduced a silicate triangle fractal network (Sin) which is a planar fractal and it is created using a related sequence of graphs named (Sin)n≥0, where n is the nth level of silicate triangle fractal network. We analyze the topological indices (TI) of the silicate triangle fractal network Sin graph and compare the calculated topological indices to the number of copies of silicate structure (Sio4) in each iteration of Sin for a sequence of a graph.

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Molecular Structural Descriptors of Donut Benzenoid Systems

Julietraja¹,

Venugopal²,

Prabhu

et al. 2021

Polycyclic Aromatic Compounds

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Computing Molecular Topological Descriptors of Polymeric Networks Modeled by Sierpinski Networks

Cited by 3 publications

References 23 publications

Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Computing Certain Topological Indices of Silicate Triangle Fractal Network Modeled by the Sierpiński Triangle Network

Molecular Structural Descriptors of Donut Benzenoid Systems

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