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On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models

Rhodium (III) chloride is a metallic compound characterized by its shiny and silvery-white appearance. It possesses high reflectivity and exhibits excellent resistance to corrosion. This makes it a popular choice for applications such as plating materials in jewelry and other decorative items, impar...

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Autores principales: Hussain, Mazhar, Siddiqui, Muhammad Kamran, Hanif, Muhammad Farhan, Mahmood, Hasan, Saddique, Zohaib, Asefa Fufa, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616341/
https://www.ncbi.nlm.nih.gov/pubmed/37916098
http://dx.doi.org/10.1016/j.heliyon.2023.e20935
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author Hussain, Mazhar
Siddiqui, Muhammad Kamran
Hanif, Muhammad Farhan
Mahmood, Hasan
Saddique, Zohaib
Asefa Fufa, Samuel
author_facet Hussain, Mazhar
Siddiqui, Muhammad Kamran
Hanif, Muhammad Farhan
Mahmood, Hasan
Saddique, Zohaib
Asefa Fufa, Samuel
author_sort Hussain, Mazhar
collection PubMed
description Rhodium (III) chloride is a metallic compound characterized by its shiny and silvery-white appearance. It possesses high reflectivity and exhibits excellent resistance to corrosion. This makes it a popular choice for applications such as plating materials in jewelry and other decorative items, imparting a lustrous and reflective surface to the coated objects. Topological indices are numerical parameters employed to characterize the topology of a molecular structure. These indices are derived from the connectivity of atoms within the molecule and serve as predictors for various molecular properties, including reactivity, stability, and solubility. On the other hand, the Shannon entropy of a graph finds extensive applications in network science. It is utilized in the analysis of diverse networks, such as social networks, biological networks, and transportation networks. The Shannon entropy allows for the characterization of a network's topology and structure, aiding in the identification of crucial nodes or structures that play significant roles in network functionality and stability. In this paper, our primary objective is to compute different K-Banhatti indices and employ them to evaluate the entropy measure of Rhodium (III) chloride [Formula: see text]. Additionally, we conducted an examination through linear regression analysis involving various indices and entropies associated with Rhodium chloride. Moreover, we established a correlation between degree-based Banhatti indices and entropies via the line fit method.
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spelling pubmed-106163412023-11-01 On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models Hussain, Mazhar Siddiqui, Muhammad Kamran Hanif, Muhammad Farhan Mahmood, Hasan Saddique, Zohaib Asefa Fufa, Samuel Heliyon Research Article Rhodium (III) chloride is a metallic compound characterized by its shiny and silvery-white appearance. It possesses high reflectivity and exhibits excellent resistance to corrosion. This makes it a popular choice for applications such as plating materials in jewelry and other decorative items, imparting a lustrous and reflective surface to the coated objects. Topological indices are numerical parameters employed to characterize the topology of a molecular structure. These indices are derived from the connectivity of atoms within the molecule and serve as predictors for various molecular properties, including reactivity, stability, and solubility. On the other hand, the Shannon entropy of a graph finds extensive applications in network science. It is utilized in the analysis of diverse networks, such as social networks, biological networks, and transportation networks. The Shannon entropy allows for the characterization of a network's topology and structure, aiding in the identification of crucial nodes or structures that play significant roles in network functionality and stability. In this paper, our primary objective is to compute different K-Banhatti indices and employ them to evaluate the entropy measure of Rhodium (III) chloride [Formula: see text]. Additionally, we conducted an examination through linear regression analysis involving various indices and entropies associated with Rhodium chloride. Moreover, we established a correlation between degree-based Banhatti indices and entropies via the line fit method. Elsevier 2023-10-16 /pmc/articles/PMC10616341/ /pubmed/37916098 http://dx.doi.org/10.1016/j.heliyon.2023.e20935 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Hussain, Mazhar
Siddiqui, Muhammad Kamran
Hanif, Muhammad Farhan
Mahmood, Hasan
Saddique, Zohaib
Asefa Fufa, Samuel
On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title_full On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title_fullStr On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title_full_unstemmed On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title_short On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models
title_sort on k-banhatti indices and entropy measure for rhodium (iii) chloride via linear regression models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616341/
https://www.ncbi.nlm.nih.gov/pubmed/37916098
http://dx.doi.org/10.1016/j.heliyon.2023.e20935
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