QSPR modeling of organic semiconductor building blocks using topological indices
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Hui Wang
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Khadeeja Firdous
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.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The author states no conflict of interest.
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Research funding: This research project is supported by Anhui Provincial Innovation Team (2024AH 010011), Key Scientific Research Project of Anhui Province (2024 AH 050611)
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Data availability: Not applicable.
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