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One-dimensional transport with dynamic disorder.

Valeri Barsegov1, Yonathan Shapir, Shaul Mukamel

  • 1Department of Chemistry, University of Rochester, Rochester, New York 14627-0216, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|August 26, 2003
PubMed
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This study examines quenching time in disordered donor-bridge-acceptor systems. Long power-law tails appear when kappaN is near 1, but vanish for smaller values, impacting system dynamics.

Area of Science:

  • Physics
  • Physical Chemistry
  • Condensed Matter Physics

Background:

  • Donor-bridge-acceptor systems are crucial for energy transfer studies.
  • Disorder and bath coupling significantly influence system dynamics.
  • Understanding quenching time is key to predicting energy transfer efficiency.

Purpose of the Study:

  • To investigate the mean quenching time distribution and its moments in a disordered 1D N-site donor-bridge-acceptor system.
  • To analyze the impact of bath coupling and hopping rates on quenching dynamics.
  • To compute particle position, velocity, and diffusion coefficient distributions.

Main Methods:

  • Theoretical modeling of a one-dimensional N-site donor-bridge-acceptor system.
  • Coupling all sites to a two-state jump bath.

Related Experiment Videos

  • Analysis of arbitrary disorder and bath jump rate to average hopping rate ratio (kappa).

    • Main Results:

    • Quenching time distribution exhibits long power-law tails when kappaN is approximately 1, disappearing for kappaN << 1.
    • Mean quenching time scales linearly with N in the absence of disorder or for small kappa.
    • A power-law scaling (N^1+gamma) is observed, with a crossover to linear scaling for large N.

    Conclusions:

    • The interplay between disorder and bath coupling critically determines quenching time distribution and scaling.
    • System dynamics exhibit self-averaging of hopping rates and dynamic disorder at longer timescales.
    • Particle transport properties like diffusion coefficient scale linearly with time for long observation periods.