Skip to main navigation Skip to search Skip to main content

On connection number-based topological indices and entropy measures for triangular γ-graphyne network

  • Rongbing Huang
  • , Muhammad Farhan Hanif
  • , Muhammad Kamran Siddiqui*
  • , Mazhar Hussain
  • , Muhammad Faisal Hanif
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Triangular γ-graphyne has a special carbon–carbon bonding arrangement, which results in outstanding electrical characteristics. It is a potential material for semiconductors and conductors in nanoelectronic devices. The number of vertices at a distance of 2 from a vertex is known as the connection number (CN) of that vertex. In this paper, we computed Zagreb-type indices based on connection numbers. In order to give us a better knowledge of the structural properties of molecules or networks, these indices are calculated. Following the computation of these indices, we investigated their use in computing entropy, providing important new information about the thermodynamic characteristics and complexity of the understudied systems. We used Python language to find the Pearson correlation coefficient between indices and entropy and show its heat map.

Original languageEnglish
Pages (from-to)25029-25048
Number of pages20
JournalJournal of Supercomputing
Volume80
Issue number17
DOIs
StatePublished - Nov 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

Keywords

  • Connection number
  • Degree of vertex
  • Edge set
  • Pearson correlation
  • Shannon entropy
  • Triangular γ-graphyne network
  • Vertex set

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Information Systems
  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'On connection number-based topological indices and entropy measures for triangular γ-graphyne network'. Together they form a unique fingerprint.

Cite this