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Analyzing boron oxide networks through Shannon entropy and Pearson correlation coefficient.

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|November 3, 2024
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This study reveals strong positive correlations between topological indices (Van and S) and entropy in boron oxide networks. These findings aid in understanding chemical compound characteristics and statistical analysis.

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Area of Science:

  • Chemical Graph Theory
  • Computational Chemistry
  • Materials Science

Background:

  • Chemical graph theory provides numerical measures (topological indices) to understand chemical compound properties.
  • Boron oxide's topological properties are increasingly studied using graph theory.

Purpose of the Study:

  • To analyze correlations between topological indices (Van and S) and entropy in boron oxide.
  • To establish a basis for future statistical investigations into chemical network properties.

Main Methods:

  • Pearson correlation analysis was performed on boron oxide data.
  • Heatmaps were used to visualize correlations between entropy values and calculated topological indices.

Main Results:

  • A significant positive correlation was found between the Van and S indices and entropy values.
  • The heatmap visually confirmed strong linear correlations, indicating relationships between these metrics.

Conclusions:

  • The study demonstrates a clear link between specific topological indices and entropy in boron oxide.
  • Dimensionality reduction is suggested for highly correlated variables to prevent redundancy in future analyses.