We introduce a mesoscopic model to predict the charge mobility of organic semiconductors characterized by a coexistence of crystalline and amorphous phases. First, we validate our scheme by reproducing the trends in charge mobility observed in thin films of poly(3-hexylthiophene) (P3HT) polymers. Next, we address the problem of predicting the morphologies that lead to the highest mobility. Our main finding is the identification of a region of the model's multidimensional parameter space, in which the charge mobility effectively depends on a single morphological feature: the average intercrystallite distance. This scaling behavior provides insight into the main physical mechanism limiting charge mobility in organic semiconductors. Our proposed framework can be adapted to study a wide class of polymeric systems and used to guide the manufacturing of new, high-performing organic semiconductor materials.

Predicting Charge Mobility of Organic Semiconductors with Complex Morphology / Segatta, Francesco; Lattanzi, Gianluca; Faccioli, Pietro. - In: MACROMOLECULES. - ISSN 0024-9297. - ELETTRONICO. - 51:21(2018), pp. 9060-9068. [10.1021/acs.macromol.8b01727]

Predicting Charge Mobility of Organic Semiconductors with Complex Morphology

Segatta, Francesco;Faccioli, Pietro
2018

Abstract

We introduce a mesoscopic model to predict the charge mobility of organic semiconductors characterized by a coexistence of crystalline and amorphous phases. First, we validate our scheme by reproducing the trends in charge mobility observed in thin films of poly(3-hexylthiophene) (P3HT) polymers. Next, we address the problem of predicting the morphologies that lead to the highest mobility. Our main finding is the identification of a region of the model's multidimensional parameter space, in which the charge mobility effectively depends on a single morphological feature: the average intercrystallite distance. This scaling behavior provides insight into the main physical mechanism limiting charge mobility in organic semiconductors. Our proposed framework can be adapted to study a wide class of polymeric systems and used to guide the manufacturing of new, high-performing organic semiconductor materials.
2018
Predicting Charge Mobility of Organic Semiconductors with Complex Morphology / Segatta, Francesco; Lattanzi, Gianluca; Faccioli, Pietro. - In: MACROMOLECULES. - ISSN 0024-9297. - ELETTRONICO. - 51:21(2018), pp. 9060-9068. [10.1021/acs.macromol.8b01727]
Segatta, Francesco; Lattanzi, Gianluca; Faccioli, Pietro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/657378
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