Abstract
AbstractThe entropy-based procedures from the configuration of chemical graphs and multifaceted networks, several graph properties have been utilized. For computing, the organizational evidence of organic graphs and multifaceted networks, the graph entropies have converted the information-theoretic magnitudes. The graph entropy portion has attracted the research community due to its potential application in chemistry. In this paper, our input is to reconnoiter graph entropies constructed on innovative information function, which is the quantity of different degree vertices along with the quantity of edges between innumerable degree vertices.”In this study, we explore two dissimilar curricula of carbon nanosheets that composed by C4and C8denoted by T1C4C8(S)[m, n] and T2C4C8(R)[m, n]. Additionally, we calculate entropies of these configurations by creating a connection of degree-based topological indices with the advantage of evidence occupation.
Highlights
Our input is to reconnoiter graph entropies constructed on innovative information function, which is the quantity of different degree vertices along with the quantity of edges between innumerable degree vertices.”In this study, we explore two dissimilar curricula of carbon nanosheets that composed by C4 and C8 denoted by T1C4C8(S)[m, n] and T2C4C8(R)[m, n]
A branch of mathematical chemistry that uses the tools of graph theory to develop the organic phenomenon mathematically is called chemical graph theory (Ali et al, 2019)
A arithmetic value that is calculated arithmetically by using the molecular graph is characterized as a topological index
Summary
A branch of mathematical chemistry that uses the tools of graph theory to develop the organic phenomenon mathematically is called chemical graph theory (Ali et al, 2019). The basic idea of entropy was introduced in the following statement: “The entropy of a possible dissemination is known as a quota of the unpredictability of evidence content or a portion of the uncertainty of a coordination” (Shannon, 2001), which was developed for evaluating the mechanical evidence of graphs and chemical networks. Afterward, it has been used significantly in graphs and chemical networks. For more details about these indices see: Akhter et al (2016), Ali et al (2019), Liu et al (2020a, 2020b), Raza (2020a, 2020b), Raza and Ali (2020), and Raza and Sukaiti (2020)
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