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Combinatorial Chemistry & High Throughput Screening

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ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

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Research Article

Polynomials of Degree-Based Indices of Metal-Organic Networks

Author(s): Ali Ahmad*, Muhammad Ahsan Asim and Muhammad Faisal Nadeem

Volume 25, Issue 3, 2022

Published on: 29 December, 2020

Page: [510 - 518] Pages: 9

DOI: 10.2174/1386207323666201229152828

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Abstract

Aim and Objective: Metal-organic network (MON) is a special class of molecular compounds comprising groups of metal ions and carbon-based ligand. These chemical compounds are examined employing one, two- or three-dimensional formation of porous ore and subfamilies of polymers. Metal-organic networks are frequently utilized in catalysis for the parting & distilling of different gases and by means of conducting solid or super-capacitor. In various scenarios, the compounds are observed to maintain a balance in the procedure of deletion or diluter of the molecule and can be rebuilt with another molecular compound. The physical solidity and mechanical characteristics of the metal-organic network have attained great attention due to the above-mentioned properties. This study was undertaken to find the polynomials of MON.

Methods: Topological descriptor is a numerical number that is utilized to predict the natural correlation amongst the Physico-chemical properties of the molecular structures in their elementary networks

Results: After partitioning the vertices based on their degrees, we calculate different degree-based topological polynomials for two distinct metal-organic networks with an escalating number of layers containing both metals and carbon-based ligand vertices.

Conclusion: In the analysis of the metal-organic network, topological descriptors and their polynomials play an important part in modern chemistry. An analysis between the various calculated forms of the polynomials and topological descriptors through the numeric values and their graphs are also presented

Keywords: Topological polynomials, degree-based index, metal-organic networks, chemical compounds, quantitative structures activity relationship, quantitative structures property relationship.

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