Semiconducting polymers consisting of conjugated heterocyclic chains are one of the most frequently studied classes of organic materials for next-generation organic field-effect transistors (OFETs), organic light-emitting diodes (OLEDs), and flexible photovoltaic materials. Despite their widespread importance, the conventional approach to developing new semiconducting polymers for these applications is still dominated by heuristic experimental guesswork by synthetic chemists. This experimental approach has had significant success in the past, but is ultimately time-consuming and costly due to the nearly limitless number of promising candidate materials. In this talk, I will present our application of high-throughput predictive computational approaches for rationally guiding experimental efforts for designing new semiconducting polymers [1-2]. In particular, we show that the use of first-principles calculations can dramatically reduce the number of promising synthetic targets for experimental design and gives a rational understanding of how different chemical functional groups modulate electronic properties to ultimately guide the organic synthesis. From our computational screening methodology, we observe that a unique pattern of aromatic/quinoidal effects naturally arises, which directly controls the band gap and mobility of these conjugated systems. Finally, based on our first-principles calculations, we draw attention to a vinylene-linked, benzannulated pyrrole polymer as a low-band-gap material with extremely interesting electronic properties.<br/><br/>[1] B.M. Wong and J.G. Cordaro, J. Phys. Chem. C, 115, 18333 (2011).<br/>[2] J.D. Azoulay, Z. A. Koretz, B.M. Wong, and G.C. Bazan, Macromolecules, 46, 1337 (2013).

High-throughput computational design of semiconducting polymers: Predictions and rational guidance from DFT calculations

249th National Meeting (2015)

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