Nonisotropic Excitation Energy Transport in Organized Molecular Systems:  Monte Carlo Simulation-Based Analysis of Fluorescence and Fluorescence Anisotropy Decay

Abstract

An improved application is presented of the Monte Carlo method including simultaneous parameter fitting to analyze the experimental time-resolved fluorescence and fluorescence anisotropy decay of two organized molecular systems exhibiting a number of different, nonisotropic energy transfer processes. Using physical models and parameter fitting for these systems, the Monte Carlo simulations yield a final set of parameters, which characterize the energy transfer processes in the investigated systems. The advantages of such a simulation-based analysis for global parametric fitting are discussed. Using this approach energy transfer processes have been analyzed for two porphyrin model systems, i.e., spin-coated films of zinc tetra-(octylphenyl)-porphyrins (ZnTOPP) and the tetramer of zinc mono(4-pyridyl)triphenylporphyrin (ZnM(4-Py)TrPP). For the ZnTOPP film energy transfer rate constants of ∼1 × 10 12 s -1 and ∼80 × 10 9 s -1 have been found, and are assigned to intra-and interstack transfer, respectively. For the tetramers, the transfer rate constants of 38 × 10 9 and 5 × 10 9 s -1 correspond to energy transfer to nearest and next nearest neighbor molecules, respectively. The results are in agreement with a Förster type energy transfer mechanism.

Electronic Excitation Energy Migration in a Photonic Dye–Zeolite Antenna

“…[43,44]. Starting from an initially excited donor, the excitation energy randomly walks along and across chains of donors, that is, in the parallel (k) and perpendicular (c) directions to the c axis of the zeolite L crystal, until the event of donor radiative emission or falling into a trap (a luminescent acceptor trap or a nonluminescent trap, Q) happens.…”

“…[49±52] The multiexponential time-domain representation of the experimental fluorescence behavior was analyzed by means of MC simulation (blocks 8 ± 10), [43,44] yielding the rate constants for EnT (block 11). The quality of the MC simulation and parameter fits was estimated using the statistical c 2 test, the plot of the weighted residuals, and the plot of the autocorrelation function of the weighted residuals.…”

“…In our numerical experiments, we used the statistical c 2 criterion and its weighting factors, since it is one of the best tests for fluorescence decay fitting using MC simulations. [43,44,54,55] In this case, the c 2 equation takes the form of Equation (20)…”

“…Assuming Poisson statistics of an MC-simulated decay, [43] the weighting factors of the simulated decay can be approximated by Equation (21) …”

“…[56] It is impractical, however, to apply this, since it would result in a dramatic increase of processing time. In previous work [43,44] we used the less time-consuming, but also less accurate, asymptotic standard errors. [57] Here, we applied the MC confidence interval evaluation method, [54,58] which is more time-consuming, but still not extensive, and considerably reduces the risk of landing in local minima.…”