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On analysis of entropy measure via logarithmic regression model and Pearson correlation for Tri-s-triazine

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

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Due to its high chemical and thermal stability, tri-s-triazine(g−C3N4) is a potential nanomaterial used in water purification and catalysis. Tri-s-triazine is released into the environment as a contaminant since it is occasionally utilized as a precursor or byproduct in industrial processes. Based on its chemical structure, we compute the new Zagreb-type indices to learn more about its connection and bonding patterns. We may construct the entropy measure using these indices to assess the material's stability and forecast its behavior under various circumstances. We establish mathematical links between the Zagreb-type indices and entropy by performing logarithmic regression, which helps optimize its use in particular applications. Also, we use the Pearson correlation coefficient.

Original languageEnglish
Article number112994
JournalComputational Materials Science
Volume240
DOIs
StatePublished - May 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 Elsevier B.V.

Keywords

  • 05C10
  • 05C90
  • Pearson correlation coefficient
  • Regression models
  • Shannon entropy
  • Tri-s-triazine

ASJC Scopus subject areas

  • General Computer Science
  • General Chemistry
  • General Materials Science
  • Mechanics of Materials
  • General Physics and Astronomy
  • Computational Mathematics

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