This article computes topological indices of chain silicate structures, suggesting insights for QSPR models using statistical techniques and machine learning.
In recent years, the integration of topological indices into Quantitative Structure Property Relationship (QSPR) models has become increasingly prominent. These models leverage statistical techniques and machine learning algorithms to predict molecular properties based on topological descriptors, offering valuable insights for rational drug design, environmental risk assessment, and material properties optimization. In this article, we compute various topological indices of the chain silicate and ortho chain silicate structures. Also the computed indices are plotted in graphs and compared visually.
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Nagarajan et al. (2025) studied this question.
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