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共价有机框架的Marta变体的拓扑熵表征与图能量预测的比较研究

A comparative study of topological entropy characterization and graph energy prediction for Marta variants of covalent organic frameworks.

作者信息

Raza Zahid, Arockiaraj Micheal, Maaran Aravindan, Shalini Arul Jeya

机构信息

Department of Mathematics, College of Sciences, University of Sharjah, Sharjah, United Arab Emirates.

Department of Mathematics, Loyola College, Chennai, India.

出版信息

Front Chem. 2024 Dec 20;12:1511678. doi: 10.3389/fchem.2024.1511678. eCollection 2024.

DOI:10.3389/fchem.2024.1511678
PMID:39758156
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11696151/
Abstract

Covalent organic frameworks are a novel class of porous polymers, notable for their crystalline structure, intricate frameworks, defined pore sizes, and capacity for structural design, synthetic control, and functional customization. This paper provides a comprehensive analysis of graph entropies and hybrid topological descriptors, derived from geometric, harmonic, and Zagreb indices. These descriptors are applied to study two variations of Marta covalent organic frameworks based on contorted hexabenzocoronenes. We also conduct a comparative analysis using scaled entropies, offering refined tools for assessing the intrinsic topologies of these networks. Additionally, these hybrid descriptors are used to develop statistical models for predicting graph energy in higher-dimensional Marta-COFs.

摘要

共价有机框架是一类新型的多孔聚合物，以其晶体结构、复杂框架、确定的孔径以及结构设计、合成控制和功能定制能力而闻名。本文对源自几何、调和和 Zagreb 指数的图熵和混合拓扑描述符进行了全面分析。这些描述符被用于研究基于扭曲六苯并蔻的两种变体马尔塔共价有机框架。我们还使用缩放熵进行了比较分析，提供了用于评估这些网络内在拓扑的精细工具。此外，这些混合描述符被用于开发统计模型，以预测高维马尔塔 - 共价有机框架中的图能量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/c9c96539be88/fchem-12-1511678-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/d83d410b5921/fchem-12-1511678-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/464adbd4f3bd/fchem-12-1511678-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/8cc592335f00/fchem-12-1511678-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/a55e9f8992ab/fchem-12-1511678-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/0068940d3cd3/fchem-12-1511678-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/c9c96539be88/fchem-12-1511678-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/d83d410b5921/fchem-12-1511678-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/464adbd4f3bd/fchem-12-1511678-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/8cc592335f00/fchem-12-1511678-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/a55e9f8992ab/fchem-12-1511678-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/0068940d3cd3/fchem-12-1511678-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80af/11696151/c9c96539be88/fchem-12-1511678-g006.jpg

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