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.
Yogalakshmi et al. (Mon,) studied this question.