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<p>Recent advances in porous, nanoscale two-dimensional materials have highlighted their exceptional potential in various scientific fields, including energy storage, gas capture, and molecular transport. Among these materials, metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) have garnered considerable interest due to their tunable porosity, large surface areas, and ability to form hybrid structures with enhanced functionalities. In this study, we systematically analyze the structural properties of these frameworks through topological indices derived from M-polynomials. The indices considered include Zagreb, Randic, symmetric division, forgotten, harmonic, inverse sum, and both third and fifth symmetric division indices. We apply this framework to two n-dimensional hexatriphenylene-based networks, one metal–organic and the other covalent, and perform a comparative analysis of the resulting M-polynomial-based indices to reveal their structural characteristics and offer insights into their chemical behavior.</p>

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M-polynomials characterization n-dimensional of triphenylene-based metal and covalent organic frameworks

  • 期刊论文

  • 发表日期：

    2025年8月17日

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  • Ali N. A. Koam,
  • Abdulaziz Mutlaq Alotaibi,
  • Ali Ahmad,
  • Muhammad Faisal Nadeem,
  • Ibtisam Masmali

摘要

Recent advances in porous, nanoscale two-dimensional materials have highlighted their exceptional potential in various scientific fields, including energy storage, gas capture, and molecular transport. Among these materials, metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) have garnered considerable interest due to their tunable porosity, large surface areas, and ability to form hybrid structures with enhanced functionalities. In this study, we systematically analyze the structural properties of these frameworks through topological indices derived from M-polynomials. The indices considered include Zagreb, Randic, symmetric division, forgotten, harmonic, inverse sum, and both third and fifth symmetric division indices. We apply this framework to two n-dimensional hexatriphenylene-based networks, one metal–organic and the other covalent, and perform a comparative analysis of the resulting M-polynomial-based indices to reveal their structural characteristics and offer insights into their chemical behavior.