Open AccessExciton Diffusion in Organic Nanofibers: A Monte Carlo Study on the Effects of Temperature and Dimensionality
Author(s) -
Leonardo Evaristo de Sousa,
Demétrio A. da Silva Filho,
Rafael T. de Sousa,
Pedro Henrique de Oliveira Neto
Publication year - 2018
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/s41598-018-32232-5
Subject(s) - exciton , diffusion , kinetic monte carlo , monte carlo method , curse of dimensionality , materials science , chemical physics , singlet state , intermolecular force , molecular physics , statistical physics , condensed matter physics , chemistry , physics , excited state , thermodynamics , atomic physics , computer science , quantum mechanics , molecule , mathematics , statistics , machine learning
Organic nanofibers have found various applications in optoelectronic devices. In such devices, exciton diffusion is a major aspect concerning their efficiency. In the case of singlet excitons, Förster transfer is the mechanism responsible for this process. Temperature and morphology are factors known to influence exciton diffusion but are not explicitly considered in the expressions for the Förster rate. In this work, we employ a Kinetic Monte Carlo (KMC) model to investigate singlet exciton diffusion in para-hexaphenyl (P6P) and α -sexithiophene (6T) nanofibers. Building from previous experimental and theoretical studies that managed to obtain temperature dependent values for Förster radii, exciton average lifetimes and intermolecular distances, our model is able to indicate how these parameters translate into diffusion coefficients and diffusion lengths. Our results indicate that these features strongly depend on the coordination number in the material. Furthermore, we show how all these features influence the emitted light color in systems composed of alternating layers of P6P and 6T. Finally, we present evidence that the distribution of exciton displacements may result in overestimation of diffusion lengths in experimental setups.