QSPR modeling of organic semiconductor building blocks using topological indices

Abstract Topological indices are numerical descriptors that capture key structural information of molecular graphs, enabling the quantitative prediction of chemical properties. This study employs five degree-based topological indices to develop quantitative structure property relationship (QSPR) models for twenty fundamental building blocks of organic semiconductors. Strong correlations are established between these indices and critical physicochemical properties including melting point, boiling point, and molecular mass using linear, quadratic, and logarithmic regression approaches. Molecular mass and boiling point are found to be particularly well predicted, with correlation coefficients exceeding 0.99 in multiple models. The results are validated against experimental data, confirming the practical utility of the proposed models. These findings underscore the value of topological indices as efficient computational tools for the high-throughput screening and rational design of organic semiconductor materials.