Efficient energy transfer in light-harvesting systems, I: optimal temperature, reorganization energy and spatial–temporal correlations

Jianlan Wu, Fan Liu, Young T. Shen, Jianshu Cao, R. Silbey

New Journal of Physics · 2010 · 213 citations · 42 references

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TL;DR

Understanding the mechanisms of efficient and robust energy transfer in light‑harvesting systems provides new insights for the optimal design of artificial systems. The study uses the FMO protein complex and phycocyanin 645 to investigate how physical parameters affect energy transfer efficiency and stability. The authors employ a generalized Bloch‑Redfield equation approach, supplemented by the Haken‑Strobl model, to model exciton dynamics and assess energy transfer efficiency across temperature, reorganization energy, and noise correlations. Maximal energy transfer efficiency is achieved at an intermediate dephasing rate and under various physical conditions, but in certain reorganization energy regimes the efficiency varies monotonically with temperature or spatial correlation, precluding optimization with respect to these variables.

Abstract

Understanding the mechanisms of efficient and robust energy transfer in light-harvesting systems provides new insights for the optimal design of artificial systems. In this paper, we use the Fenna-Matthews-Olson (FMO) protein complex and phycocyanin 645 (PC 645) to explore the general dependence on physical parameters that help maximize the efficiency and maintain its stability. With the Haken-Strobl model, the maximal energy transfer efficiency (ETE) is achieved under an intermediate optimal value of dephasing rate. To avoid the infinite temperature assumption in the Haken-Strobl model and the failure of the Redfield equation in predicting the Forster rate behavior, we use the generalized Bloch-Redfield (GBR) equation approach to correctly describe dissipative exciton dynamics and find that maximal ETE can be achieved under various physical conditions, including temperature, reorganization energy, and spatial-temporal correlations in noise. We also identify regimes of reorganization energy where the ETE changes monotonically with temperature or spatial correlation and therefore cannot be optimized with respect to these two variables.

References

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