Modelling quenching mechanisms of disordered molecular systems in the presence of molecular aggregates. Issue 3 (5th January 2022)

• Record Type: Journal Article
• Authors: Fanciullo, Giacomo; Conti, Irene; Didier, Pascal; Klymchenko, Andrey; Léonard, Jérémie; Garavelli, Marco; Rivalta, Ivan
• Is Part Of: Physical chemistry chemical physics. Volume 24:Issue 3(2021)
• Page Start: 1787
• Page End: 1794
• Publication Date: 2022-01-05
• Subjects: Chemistry, Physical and theoretical -- Periodicals; 541.3
• DOI: 10.1039/d1cp04260b
• Languages: English
• ISSNs: 1463-9076

Abstract

Abstract : A macroscopic model of exciton density decays in disordered molecular systems, including contributions from molecular aggregate quenchers, is proposed. The model can be applied to ultrafast decays of dyes and for global fitting of experimental data. Abstract : Exciton density dynamics recorded in time-resolved spectroscopic measurements is a useful tool to recover information on energy transfer (ET) processes that can occur at different timescales, up to the ultrafast regime. Macroscopic models of exciton density decays, involving both direct Förster-like ET and diffusion mechanisms for exciton–exciton annihilation, are largely used to fit time-resolved experimental data but generally neglect contributions from molecular aggregates that can work as quenching species. In this work, we introduce a macroscopic model that includes contributions from molecular aggregate quenchers in a disordered molecular system. As an exemplifying case, we considered a homogenous distribution of rhodamine B dyes embedded in organic nanoparticles to set the initial parameters of the proposed model. The influence of such model parameters is systematically analysed, showing that the presence of molecular aggregate quenchers can be monitored by evaluating the exciton density long time decays. We showed that the proposed model can be applied to molecular systems with ultrafast decays, and we anticipated that it could be used in future studies for global fitting of experimental data with potential support from first-principles simulations.