Electronic excitation transfer in chains modulated by conformational dynamic disorder

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Abstract
Electronic excitations along sites that undergo spatial and temporal fluctuations due to conformational chain motion have been studied in the picture of the stochastic master equation by means of the dynamic Monte Carlo (DMC) and the cumulant expansion (CE) approach. An incoherent site-to-site hopping which is adiabatic relative to the changes of conformational site coordinates has been assumed. The elementary act of conformational change has been considered to be fast, whereas the electronic transfer during the time period of the conformational event has been assumed to be negligibly small. The time evolution of electronic intersite coupling is thus controlled by chromophore sites that, in particular, correspond to the conformational minima of the potential energy landscape. The generalized equations of motion adapted for both the DMC and the CE analysis have been reduced to formulate donor site excitation probabilities 〈Piexc(t)〉 and donor excitation survival functions 〈PD(t)〉 for a simplified chain. In this polymer model, (i) specific nearest-neighbor electronic coupling occurs with two distinct transfer rates W1 and W2 corresponding to two different spatial arrangements of the pendant sites in the pair and (ii) transitions between two definite conformational states occur both in the correlated and in the uncorrelated regime. For short chains and a moderate number of sites in the rotational dyads the whole range from the dynamic to the static limit in the interplay between excitation transfer and correlated conformational motion has been calculated by the DMC method. By means of the cumulant technique well-behaved solutions could be obtained only in the fast conformational transition regime which allows a direct comparison with the DMC results. For longer chains up to 100 sites, in the limit case of uncorrelated conformational motion, preliminary cumulant approaches have been given which, for very rapid conformational rates, agree well with the dynamic effective medium approximation (DEMA) solutions.