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八面体和二十面体网络不规则分子描述符的计算度量。

Computational measures of irregularity molecular descriptors of octahedral and icosahedral networks.

作者信息

Zhang Xiujun, Ur Rehman Hafiz Mutee, Munir M Mobeen

机构信息

School of Computer Science, Chengdu University, Chengdu, China.

Department of Mathematics, Division of Science and Technology, University of Education Lahore, Lahore, Pakistan.

出版信息

Front Chem. 2025 Jan 17;12:1485184. doi: 10.3389/fchem.2024.1485184. eCollection 2024.

Abstract

Irregularity measures tend to describe the complexity of networks. Chemical graph theory is a branch of mathematical chemistry that has a significant impact on the development of the chemical sciences. The study of irregularity indices has recently become one of the most active research areas in chemical graph theory. Irregularity indices help us to examine many chemical and biological properties of chemical structures under study. In this article, we study the irregularity indices of the octahedral and icosahedral networks. These networks are used in crystallography, where the topology and structural aspects are carrying some important facts to determine the properties of large structures theoretically. Our results play an important role in pharmacy, drug design, and many other applied areas. We also compared our results graphically to conclude the irregularity with a change in the parameter of structures.

摘要

不规则性度量倾向于描述网络的复杂性。化学图论是数学化学的一个分支,对化学科学的发展有重大影响。不规则性指标的研究最近已成为化学图论中最活跃的研究领域之一。不规则性指标有助于我们研究正在研究的化学结构的许多化学和生物学性质。在本文中,我们研究八面体和二十面体网络的不规则性指标。这些网络用于晶体学,其中拓扑和结构方面承载着一些重要事实,以便从理论上确定大型结构的性质。我们的结果在药学、药物设计和许多其他应用领域中发挥着重要作用。我们还通过图形比较了我们的结果,以得出结构参数变化时的不规则性结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed9c/11782199/69fe4da41fec/fchem-12-1485184-g001.jpg

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