QSRP Studies of Chemical Compunds Using Topological Indices

Title

QSRP Studies of Chemical Compunds Using Topological Indices

Creator

Anjusha, Asok

Contributor

Joseph, Varghese

Description

In this study, we explore the intersection of graph theory and chemistry, focusing on how graph theory s principles can model molecular structures and predict their physiochemical properties. Specifcally, it applies topological indices (mathematical descriptors) derived from the graph-theoretic representation of molecules to establish quantitative structure-property relationships (QSPR) for octane isomers and polychlorobiphenyls. The investigation encompasses 30 topological indices, including the Harary, Wiener, Zagreb, and connectivity indices, and assesses their correlation with key physiochemical properties. Through rigorous analysis, the study successfully develops QSPR models capable of predicting properties like BP, HVAP, DHVAP, HFORM, AcenFac, TSA, and RRT signifcantly advancing newlinethe predictive accuracy of chemical properties. The study of inverse problems about topological indices and QSPR is a testament to the interdisciplinary nature of modern scientifc research, bridging gaps between mathematics, chemistry, and computer science. Inverse problems in graph theory newlinehold a special place due to their capacity to address fundamental questions about the structure and behavior of graphs based on given properties. They are often more complex and challenging than direct problems. The study of inverse problems in our research contributes to the theoretical foundations of chemical graph theory by characterizing trees and unicyclic graphs with specifc topological indices and oand#64256;ering novel insights into the inverse problem for Zagreb indices. The newlineinclusion of Python programs for calculating various topological indices further bridges theoretical chemistry with practical application, highlighting the thesis s newlineaim to enhance both the efciency and accuracy of predicting chemical compound properties. This work not only demonstrates the profound impact of graph theory on chemical informatics but also opens new avenues for research in the feld.

Source

Author's Submission

Date

2024-01-01

Publisher

Christ(Deemed to be University)

Subject

Mathematics and Statistics

Rights

Open Access

Relation

61000336

Format

PDF

Language

English

Type

PhD

Identifier

http://hdl.handle.net/10603/574689