基于几何二次和二次几何指数的碳化硅网络熵测度

IF 2.8 3区 材料科学 Q3 CHEMISTRY, PHYSICAL
Silicon Pub Date : 2024-10-25 DOI:10.1007/s12633-024-03173-8
Shibsankar Das, Virendra Kumar, Jayjit Barman
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引用次数: 0

摘要

在化学图论中,拓扑指数是与分子化合物结构相关的数值。利用这些指标构建定量构效关系(QSPR)和定量构效关系(QSAR)分析并量化分子拓扑结构的不同特征。m -多项式提供了一种方便的方法来管理涉及各种指标的复杂计算,并提供了一种一致的方法来推导基于度的多个拓扑指标。图熵度量用于度量图的结构信息含量、无序度和复杂性。在本文中,我们在各自m多项式的帮助下研究了碳化硅网络的几何二次(GQ)和二次几何(QG)指标,即\(\text {Si}_{2}\text {C}_{3} \textit{-I}[p,q]\), \(\text {Si}_{2}\text {C}_{3} \textit{-II}[p,q]\)和\(\text {Si}_{2}\text {C}_{3} \textit{-III}[p,q]\)。接下来,我们提出了基于GQ-QG指标的熵测度思想,并计算了上述网络的熵测度表达式。此外,还对GQ-QG指数和相关熵测度进行了图形表示和数值计算,以评估它们的行为。这些指标和熵测度有助于预测所考虑的碳化硅网络的物理化学性质和理解其结构行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric-Quadratic and Quadratic-Geometric Indices-based Entropy Measures of Silicon Carbide Networks

In chemical graph theory, topological indices are numerical quantities associated with the structure of molecular compounds. These indices are utilized in the construction of quantitative structure-property relationships (QSPR) and quantitative structure-activity relationships (QSAR) analysis and quantify the different features of the molecular topology. M-polynomial gives a handy method for managing complex computations involving various indices and offers a consistent methodology to derive multiple degree-based topological indices. Graph entropy measures are employed to measure the structural information content, disorder and complexity of a graph. In this article, we examine the geometric-quadratic (GQ) and quadratic-geometric (QG) indices for silicon carbide networks, namely \(\text {Si}_{2}\text {C}_{3} \textit{-I}[p,q]\), \(\text {Si}_{2}\text {C}_{3} \textit{-II}[p,q]\) and \(\text {Si}_{2}\text {C}_{3} \textit{-III}[p,q]\) with the help of their respective M-polynomials. Next, we propose the idea of the GQ-QG indices-based entropy measure and compute their expressions for the above-said networks. Furthermore, the graphical representation and numerical computation of the GQ-QG indices and associated entropy measures are performed to assess their behavior. These indices and entropy measures may be helpful in predicting the physico-chemical properties and understanding the structural behavior of the considered silicon carbide networks.

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来源期刊
Silicon
Silicon CHEMISTRY, PHYSICAL-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
5.90
自引率
20.60%
发文量
685
审稿时长
>12 weeks
期刊介绍: The journal Silicon is intended to serve all those involved in studying the role of silicon as an enabling element in materials science. There are no restrictions on disciplinary boundaries provided the focus is on silicon-based materials or adds significantly to the understanding of such materials. Accordingly, such contributions are welcome in the areas of inorganic and organic chemistry, physics, biology, engineering, nanoscience, environmental science, electronics and optoelectronics, and modeling and theory. Relevant silicon-based materials include, but are not limited to, semiconductors, polymers, composites, ceramics, glasses, coatings, resins, composites, small molecules, and thin films.
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