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Analyzing Topological Indices and Heat of Formation for Copper(II) Fluoride Network via Curve Fitting Models

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

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

One of the most important fields in current materials research is the examination of materials through the prism of topological indices. An extensive statistical investigation of topological indices relevant to the characterization of copper(II) fluoride is presented in this paper. Our goal is to use the well-understood structural features of copper(II) fluoride, a chemical that is well known for its crystalline qualities, to uncover a variety of properties inherent in its network. This work makes use of the structural information available for copper(II) fluoride. After a thorough computational investigation, a rigorous statistical analysis is conducted to determine the distributions and correlations between heat of formation and the different topological indices. The findings reveal significant patterns and trends in the copper(II) fluoride network structure, providing insights into the underlying principles governing its material behavior.

Original languageEnglish
Article number2327235
JournalApplied Artificial Intelligence
Volume38
Issue number1
DOIs
StatePublished - 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

ASJC Scopus subject areas

  • Artificial Intelligence

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