GFD analysis for BRE zeolite graph through reverse degree and reverse neighborhood degree based topological descriptors

Zeolites are minerals that are hydrated aluminosilicate and have a consistent pore structure. The zeolite family will be enhanced by the topological descriptors of molecular structures, which will also minimize the high labor costs involved in generating novel structures and lessen the environmental problems related to the industrial mass production of zeolites. The synthesis of the Brewsterite zeolite (BRE zeolite) framework was created by its significant physicochemical properties. The complex structure of BRE zeolite is characterized by reverse based topological descriptors, which can assist researchers in creating new methods for examining the structure. By employing the Renyi entropy and Generalized Fractal Dimensions (GFD) method based on reverse degree and reverse neighborhood degree based topological descriptors, BRE helps prototype and understand the elemental transformations of zeolites and their inherent self-similarity and complexity properties. Additionally, we have examined the accuracy of linear regression and cubic regression models between the acquired reverse degree and reverse neighborhood degree type Renyi entropy and generalized fractal dimensions of BRE zeolite. Therefore, to investigate the properties of large-format BRE zeolite, the expected linear and cubic correlation analysis reveals a significant correlation between Renyi entropy and GFD.

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Journal
Scientific Reports
Published
2026-04-06
DOI
https://doi.org/10.1038/s41598-026-45013-2
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

GFD analysis for BRE zeolite graph through reverse degree and reverse neighborhood degree based topological descriptors

Vladimír Kulish, Nabilah Abughazalah, G. Muhiuddin, K. Yogalakshmi et al.
Scientific Reports
Geochemistry and Geologic Mapping
article

GFD analysis for BRE zeolite graph through reverse degree and reverse neighborhood degree based topological descriptors

Vladimír Kulish, Nabilah Abughazalah, G. Muhiuddin, K. Yogalakshmi, D. Easwaramoorthy
article en

Abstract

Zeolites are minerals that are hydrated aluminosilicate and have a consistent pore structure. The zeolite family will be enhanced by the topological descriptors of molecular structures, which will also minimize the high labor costs involved in generating novel structures and lessen the environmental problems related to the industrial mass production of zeolites. The synthesis of the Brewsterite zeolite (BRE zeolite) framework was created by its significant physicochemical properties. The complex structure of BRE zeolite is characterized by reverse based topological descriptors, which can assist researchers in creating new methods for examining the structure. By employing the Renyi entropy and Generalized Fractal Dimensions (GFD) method based on reverse degree and reverse neighborhood degree based topological descriptors, BRE helps prototype and understand the elemental transformations of zeolites and their inherent self-similarity and complexity properties. Additionally, we have examined the accuracy of linear regression and cubic regression models between the acquired reverse degree and reverse neighborhood degree type Renyi entropy and generalized fractal dimensions of BRE zeolite. Therefore, to investigate the properties of large-format BRE zeolite, the expected linear and cubic correlation analysis reveals a significant correlation between Renyi entropy and GFD.

Scientific ReportsVol. 16(1)
Princess Nourah bint Abdulrahman University (SA), Jain University (IN), Sewanee: The University of the South (US), University of South Bohemia in České Budějovice (CZ), University of Tabuk (SA), Vellore Institute of Technology University (IN)
Openalex Percentile: Top 30%
Geochemistry and Geologic Mapping
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GFD analysis for BRE zeolite graph through reverse degree and reverse neighborhood degree based topological descriptors — Vladimír Kulish, Nabilah Abughazalah, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS