biostudies-literatureMakki HEuropean Research Council5723-5732https://www.ebi.ac.uk/biostudies/studies/S-EPMC12089976biostudies-literatureUnknown12(15)The molecular design of semiconducting polymers (SCPs) has been largely guided by varying monomer combinations and sequences by leveraging a robust understanding of charge transport mechanisms. However, the connection between controllable structural features and resulting electronic disorder remains elusive, leaving design rules for next-generation SCPs undefined. Using high-throughput computational methods, we analyse 100+ state-of-the-art p- and n-type polymer models. This exhaustive dataset allows for deriving statistically significant design rules. Our analysis disentangles the impact of key structural features, examining existing hypotheses, and identifying new structure-property relationships. For instance, we show that polymer rigidity has minimal impact on charge transport, while the planarity persistence length, introduced here, is a superior structural characteristic. Additionally, the predictive power of machine learning models trained on our dataset highlights the potential of data-driven approaches to SCP design, laying the groundwork for accelerated discovery of materials with tailored electronic properties.Materials horizonsMapping the structure-function landscape of semiconducting polymers.PMC12089976101020369Makki HBurke CNielsen CBTroisi AfalseMapping the structure-function landscape of semiconducting polymers.The molecular design of semiconducting polymers (SCPs) has been largely guided by varying monomer combinations and sequences by leveraging a robust understanding of charge transport mechanisms. However, the connection between controllable structural features and resulting electronic disorder remains elusive, leaving design rules for next-generation SCPs undefined. Using high-throughput computational methods, we analyse 100+ state-of-the-art p- and n-type polymer models. This exhaustive dataset allows for deriving statistically significant design rules. Our analysis disentangles the impact of key structural features, examining existing hypotheses, and identifying new structure-property relationships. For instance, we show that polymer rigidity has minimal impact on charge transport, while the planarity persistence length, introduced here, is a superior structural characteristic. Additionally, the predictive power of machine learning models trained on our dataset highlights the potential of data-driven approaches to SCP design, laying the groundwork for accelerated discovery of materials with tailored electronic properties.2025-01-01T00:00:00Z2025 Jul2026-03-18T13:52:49.683Z2025-08-21T09:51:40.778ZS-EPMC120899764039059710.1039/d5mh00485c