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

TL;DR

This study investigates how physical parameters like temperature, reorganization energy, and noise correlations influence energy transfer efficiency in light-harvesting systems, using advanced models to identify optimal conditions for maximal efficiency.

Contribution

It introduces the use of the generalized Bloch-Redfield approach to accurately model exciton dynamics and optimize energy transfer in light-harvesting complexes.

Findings

Maximal ETE occurs at intermediate dephasing rates.

Optimal conditions vary with physical parameters like temperature and reorganization energy.

Certain regimes show monotonic ETE changes, limiting optimization.

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.