Structural Analysis and Topological Characterization of Sudoku Nanosheet

Author:

Zaman Shahid1ORCID,Jalani Mehwish1,Ullah Asad2ORCID,Saeedi Ghulamullah3ORCID

Affiliation:

1. Department of Mathematics, University of Sialkot, Sialkot 51310, Pakistan

2. Department of Mathematical Sciences, Karakoram International University Gilgit, Gilgit-Baltistan 15100, Pakistan

3. Department of Mathematics, Polytechnical University of Kabul, Kabul, Afghanistan

Abstract

The physical and biological properties of chemical compounds are modelled using chemical graph theory. The geometric structure of chemical compounds can be modelled using a variety of topological indices derived from graph theory. The chemical structures, physicochemical characteristics, and biological activities are predicted by the topological indices using the real numbers derived from the molecular compound. The topological index’s first use was to identify the physical characteristics of alkenes. A topological index is a molecular structure descriptor calculated from a chemical compound’s molecular graph describing its topology. When applied to a chemical compound’s molecular structure, it tells the theoretical properties. The chemical structure is studied as a graph, where elements are denoted as vertices, and chemical bonds are called edges. In this study, we have computed some novel topological indices named as modified neighborhood version of the forgotten topological index F N , the neighborhood version of the first multiplicative Zagreb M 1 , the neighborhood version of the second Zagreb index M 2 , the neighborhood version of hyper-Zagreb index HM N , the Sambor topological index SO G , and the Sambor reduced topological index SO red G for the Sudoku nanosheet and derived formulas for them. Based on the derived formulas, the numerical results of the understudy nanosheet’s physical and chemical properties are investigated. Our computed results are undoubtedly helpful in understanding the topology of the understudy nanosheet. These computed indices have the best correlation with acentric factor and entropy; therefore, they are effective in QSPRs and QSARs analysis with complete accuracy.

Publisher

Hindawi Limited

Subject

General Mathematics

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