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<p>Zeolites are microporous crystalline aluminosilicate materials with diverse applications in adsorption, catalysis, and separation. PWN-type zeolite, with its cubic framework and 8-membered ring channels, is a structurally distinct class of three-dimensional frameworks. In this paper, we describe the PWN structure using chemical graph theory and derive hybrid degree-based topological indices along with their corresponding entropy measures. These indices are then employed to establish regression energy models that relate topological indices to various energy components of PWN, yielding strong correlations and demonstrating the predictive power of the proposed descriptors. The models effectively capture the structural complexity of zeolites and predict their physicochemical properties, thereby addressing a gap in the study of three-dimensional frameworks.</p>

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Topological entropy indices and energy prediction modeling of zeolite PWN

  • 期刊论文

  • 发表日期：

    2025年11月4日

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  • J. Celin Fiona,
  • Daniel Paul,
  • Micheal Arockiaraj,
  • Parvez Ali,
  • C. I. Arokiya Doss

摘要

Zeolites are microporous crystalline aluminosilicate materials with diverse applications in adsorption, catalysis, and separation. PWN-type zeolite, with its cubic framework and 8-membered ring channels, is a structurally distinct class of three-dimensional frameworks. In this paper, we describe the PWN structure using chemical graph theory and derive hybrid degree-based topological indices along with their corresponding entropy measures. These indices are then employed to establish regression energy models that relate topological indices to various energy components of PWN, yielding strong correlations and demonstrating the predictive power of the proposed descriptors. The models effectively capture the structural complexity of zeolites and predict their physicochemical properties, thereby addressing a gap in the study of three-dimensional frameworks.