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<p>The study analyzes iron disulfide networks with the inclusion of graph theory and chemical graph theory, zeroing in on reverse topological indices and simplifying their complicated relationships. Graph theory is a section of abstract mathematics that deals with structures of graphs and the interrelationships between them; graphs are conceptualized as vertices or points and edges, which correspond to connections. Chemical graph theory extends this concept into molecular structure, whereby atoms are reduced to vertices and chemical bonds to edges. It discusses reverse topological indices concerning iron disulfide networks and outlines the fact that these are relevant in statistical modeling, molecular topology, and chemical reactivity. Advanced concepts reported herein will allow better understanding from the viewpoint of solid-state chemistry and materials science, and insight into reactivity patterns, and structural behavior through sophisticated mathematical models and computational approaches.</p>

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On statistical evaluation of reverse degree-based topological indices for iron disulfide network

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • Rashad Ismail,
  • Muhammad Farhan Hanif,
  • Saba Hanif,
  • Muhammad Faisal Nadeem,
  • Muhammad Faisal Hanif,
  • Muhammad Kamran Siddiqui

摘要

The study analyzes iron disulfide networks with the inclusion of graph theory and chemical graph theory, zeroing in on reverse topological indices and simplifying their complicated relationships. Graph theory is a section of abstract mathematics that deals with structures of graphs and the interrelationships between them; graphs are conceptualized as vertices or points and edges, which correspond to connections. Chemical graph theory extends this concept into molecular structure, whereby atoms are reduced to vertices and chemical bonds to edges. It discusses reverse topological indices concerning iron disulfide networks and outlines the fact that these are relevant in statistical modeling, molecular topology, and chemical reactivity. Advanced concepts reported herein will allow better understanding from the viewpoint of solid-state chemistry and materials science, and insight into reactivity patterns, and structural behavior through sophisticated mathematical models and computational approaches.