Jianshu Cao of the Massachusetts Institute of Technology is supported by an award from the Chemical Theory, Models and Computational Methods program in the Chemistry Division to computationally investigate how efficient and robust coherent energy transfer arises in photosynthesis and how structure-function relations observed in light-harvesting systems can help the design of artificial energy devices. The steps involved in the current project will involve (1) characterizing quantum coherence in light-harvesting systems, (2) using the stochastic wave-function method to realistically explore spatial-temporal correlations in the presence of disorder and noise, and (3) applying optimal design theory to maximizing energy transfer and thus exploring the importance of connectivity and symmetry in donor-acceptor arrays. Understanding the microscopic mechanisms of energy transfer in photosynthetic systems is of larger significance since it is reasonable to expect that coherent transfer within collaborative protein environments may become a pervasive theme in the future. This work will, in addition to providing cutting-edge training for students and postdocs, be incorporated in the MIT curriculum, public-access MIT OpenCourseWare and public lectures on photosynthesis and basic energy sciences.
Photosynthesis in plants starts with the absorption of light by proteins in chlorophyll-containing photosynthetic reaction centers. The absorbed energy is rapidly transferred elsewhere in the complex protein environment by transfer of electrons to be stored as chemical energy. A mystery of much interest is how the electron transfer events occur in such a way as to avoid randomizing the energy before storage occurs. These ultrafast events are increasingly able to be studied by new laser-based experiments, but modeling the proteins by classical ball-and-spring models cannot reproduce the coordinated, or coherent, energy transfer. Coherence is usually regarded as requiring a description by quantum mechanics, and the PI is therefore developing quantum mechanical approaches to understanding the microscopic mechanisms underlying extremely efficient energy transfer in photosynthesis. The fact that nature has found a way to establish this collaboration in complicated protein environments raises the hope, to be explored in this project, that we can learn to control and optimize energy transfer efficiency for application in future man-made light-harvesting devices.
