2015
DOI: 10.1021/acs.jpcc.5b02405
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Efficient Exciton Diffusion and Resonance-Energy Transfer in Multilayered Organic Epitaxial Nanofibers

Abstract: Multilayered epitaxial nanofibers are exemplary model systems for the study of exciton dynamics and lasing in organic materials because of their well-defined morphology, high luminescence efficiencies, and color tunability. We use temperature-dependent continuous wave and picosecond photoluminescence (PL) spectroscopy to quantify exciton diffusion and resonance-energy transfer (RET) processes in multilayered nanofibers consisting of alternating layers of para-hexaphenyl (p6P) and α-sexithiophene (6T) serving a… Show more

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Cited by 12 publications
(18 citation statements)
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“…The model begins by reproducing the system's morphology used in the experimental study, 4 that is, 10 alternating layers of P6P and 6T. This is done by creating a matrix whose first column corresponds to the 6T monolayer followed by a number L of columns representing the number of P6P monolayers that compose the actual P6P layer (Fig.…”
Section: The Kinetic Monte Carlo Modelmentioning
confidence: 99%
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“…The model begins by reproducing the system's morphology used in the experimental study, 4 that is, 10 alternating layers of P6P and 6T. This is done by creating a matrix whose first column corresponds to the 6T monolayer followed by a number L of columns representing the number of P6P monolayers that compose the actual P6P layer (Fig.…”
Section: The Kinetic Monte Carlo Modelmentioning
confidence: 99%
“…In order to obtain the best values for the five parameters, we took advantage of the results of time-resolved photoluminescence measurements performed at several different temperatures. 4 In the genetic algorithm, the five parameters of the model (L, ρ ex , P6P d/R F , 6T d/R F , P XX ) are the genes. We evaluate the "fitness" of our simulations quantitatively by calculating the root mean squared deviation between the simulated curve and the experimental one.…”
Section: The Genetic Algorithmmentioning
confidence: 99%
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