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Characterization of chain alignment at buried interfaces using Mueller matrix spectroscopy

Published online by Cambridge University Press:  30 March 2020

Bryan H. Smith
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA16802, USA
Renxuan Xie
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA16802, USA
Wonho Lee
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA16802, USA
Dipendra Adhikari
Department of Physics and Astronomy, The University of Toledo, Toledo, OH43606, USA Wright Center for Photovoltaics Innovation and Commercialization, The University of Toledo, Toledo, OH43606, USA
Nikolas J. Podraza
Department of Physics and Astronomy, The University of Toledo, Toledo, OH43606, USA Wright Center for Photovoltaics Innovation and Commercialization, The University of Toledo, Toledo, OH43606, USA
Enrique D. Gomez*
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA16802, USA Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA16802, USA Materials Research Institute, The Pennsylvania State University, University Park, PA16802, USA
Address all correspondence to Enrique D. Gomez at
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The stiffness of conjugated polymers should lead to chain alignment near buried interfaces, even if the polymer film is nominally amorphous. Although simulations predict that this alignment layer is approximately 1.5 times the persistence length, chain alignment at buried interfaces of amorphous polymers has not been experimentally measured. Using Mueller matrix spectroscopy, the optical response of regiorandom poly(3-hexylthiophene-2,5-diyl) (P3HT) was modeled in order to extract the aligned layer thickness. By approximating the optical properties of the aligned layer as that of regioregular P3HT, the data can be effectively modeled. When the film is thicker than 150 nm, optical properties are best described with a 4-nm aligned layer, which is quantitatively consistent with previous predictions.

Research Letters
Copyright © Materials Research Society 2020

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