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Related Experiment Videos

Rate processes with non-Markovian dynamical disorder.

Igor Goychuk1

  • 1Institute of Physics, University of Augsburg, Universitätsstrasse 1, D-86135 Augsburg, Germany. goychuk@physik.uni-ausburg.de

The Journal of Chemical Physics
|June 11, 2005
PubMed
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Dynamical disorder in electron transfer (ET) processes is studied using a non-Markovian jump process. Researchers found a transition from fast modulation to quasistatic disorder as conformational diffusion time increases.

Area of Science:

  • Physical Chemistry
  • Chemical Physics
  • Theoretical Chemistry

Background:

  • Electron transfer (ET) is fundamental in chemical and biological systems.
  • Dynamical disorder, arising from fluctuating transfer rates, significantly impacts ET processes.
  • Understanding these fluctuations is crucial for predicting reaction dynamics.

Purpose of the Study:

  • To investigate rate processes with dynamical disorder in electron transfer.
  • To analyze the effects of non-Markovian stochastic jump processes on ET dynamics.
  • To derive analytical expressions for relaxation and mean transfer time.

Main Methods:

  • Modeling unidirectional electron transfer with fluctuating rates.
  • Employing a non-Markovian stochastic jump process to describe conformational dynamics.

Related Experiment Videos

  • Deriving analytical expressions in the Laplace-transformed time domain.
  • Analyzing a two-state fluctuation model with substate diffusion.

    • Main Results:

    • Obtained tractable analytical expressions for donor population relaxation and mean transfer time.
    • Demonstrated a transition from fast modulation to quasistatic disorder with increasing conformational diffusion time.
    • Identified nontrivial conditions for this transition in non-Markovian models.

    Conclusions:

    • Conformational dynamics significantly influence electron transfer rates.
    • The transition from fast to slow modulation regimes is dependent on conformational diffusion and residence times.
    • Analytical models provide insights into complex rate processes with disorder.