Optimization of exciton trapping in energy transfer processes.

J Phys Chem A

Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Published: December 2009

AI Article Synopsis

  • The paper discusses how to achieve the highest energy transfer efficiency in multilevel systems by using analytical solutions and intuitive kinetic network models.
  • It introduces a mapping method that distinguishes between thermal hopping and coherent transfer, helping visualize connections in quantum networks.
  • The findings suggest ways to optimize environmental effects and manipulate efficiency through quantum phase, providing insights applicable to light harvesting systems and large-scale computing.

Article Abstract

In this paper, we establish optimal conditions for maximal energy transfer efficiency using solutions for multilevel systems and interpret these analytical solutions with more intuitive kinetic networks resulting from a systematic mapping procedure. The mapping procedure defines an effective hopping rate as the leading order picture and nonlocal kinetic couplings as the quantum correction, hence leading to a rigorous separation of thermal hopping and coherent transfer useful for visualizing pathway connectivity and interference in quantum networks. As a result of these calculations, the dissipative effects of the surrounding environments can be optimized to yield the maximal efficiency, and modulation of the efficiency can be achieved using the cumulative quantum phase along any closed loops. The optimal coupling of the system and its environments is interpreted with the generic mechanisms: (i) balancing localized trapping and delocalized coherence, (ii) reducing the effective detuning via homogeneous line-broadening, (iii) suppressing the destructive interference in nonlinear network configurations, and (iv) controlling phase modulation in closed loop configurations. Though these results are obtained for simple model systems, the physics thus derived provides insights into the working of light harvesting systems, and the approaches thus developed apply to large-scale computation.

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http://dx.doi.org/10.1021/jp9032589DOI Listing

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