论三角形 $$\gamma$$ -graphyne 网络基于连接数的拓扑指数和熵量

Rongbing Huang, Muhammad Farhan Hanif, Muhammad Kamran Siddiqui, Mazhar Hussain, Muhammad Faisal Hanif
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引用次数: 0

摘要

三角形石墨烯具有特殊的碳-碳键排列,因而具有出色的电气特性。它是纳米电子器件中一种潜在的半导体和导体材料。与顶点距离为 2 的顶点数称为该顶点的连接数(CN)。在本文中,我们计算了基于连接数的萨格勒布型指数。为了让我们更好地了解分子或网络的结构特性,我们计算了这些指数。在计算出这些指数后,我们研究了它们在计算熵中的应用,从而提供了有关未被充分研究的系统的热力学特性和复杂性的重要新信息。我们使用 Python 语言找到了指数与熵之间的皮尔逊相关系数,并展示了其热图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On connection number-based topological indices and entropy measures for triangular $$\gamma$$ -graphyne network

Triangular \(\gamma\)-graphyne has a special carbon–carbon bonding arrangement, which results in outstanding electrical characteristics. It is a potential material for semiconductors and conductors in nanoelectronic devices. The number of vertices at a distance of 2 from a vertex is known as the connection number (CN) of that vertex. In this paper, we computed Zagreb-type indices based on connection numbers. In order to give us a better knowledge of the structural properties of molecules or networks, these indices are calculated. Following the computation of these indices, we investigated their use in computing entropy, providing important new information about the thermodynamic characteristics and complexity of the understudied systems. We used Python language to find the Pearson correlation coefficient between indices and entropy and show its heat map.

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