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Control and Optimization of Energy Flow in Complex Molecular Networks

Periodic Reporting for period 1 - COMPLEX (Control and Optimization of Energy Flow in Complex Molecular Networks)

Reporting period: 2016-04-01 to 2018-03-31

The production of sustainable energy that generates a clear and net greenhouse gas saving is one of the main objectives of the EU. Nature has already provided us with the most efficient energy infrastructures known, since photosynthesis provides virtually all the energy sustaining the biosphere. A deeper understanding of photosynthetic systems, and how energy transfers within their different sub-units, would show us the way to efficient energy flow, opening the path to the (nano-)fabrication of highly efficient solar cells and energy transmission networks.

Researchers from different disciplines including Biology, Chemistry, Physics and Engineering are striving to understand this process and emulate in artificial devices the light harvesting, initial conversion of optical to electrical energy, energy flow and electrical to chemical energy conversion process of natural photosynthesis.

The photosynthetic apparatus in biological organisms features a complex network ranging from tens to up to thousands of interconnected chlorophylls. After the initial conversion of light into electronic excitations (excitons), the exciton transverses a multi-connected potential-energy landscape on its way from the antenna to the reaction center, where in a next step chemical reactions are triggered.

With the advent of laser technologies and faster computing processors and algorithms, advanced spectroscopic experiments and quantum-chemical calculations have been developed. Questions that need to be answered include the role of quantum coherence and vibrational environmental states in the energy transport and the theoretical modelling of spectroscopic experiments.

The COMPLEX project focuses on the understanding and modelling of energy transfer in photosynthetic complexes. We have developed and identified novel numerical methods to model and understand the energy transport in complex networks. We have validated the computational tools for a direct comparison of model-based predictions with experimental spectral data of photosynthetic complexes.
We have worked with the Hierarchical Equations of Motion (HEOM) formalism which provides an exact quantum mechanical description of the energy flow in photosynthetic systems that includes the effects of environmental vibrational noise and electronic transmission on equal footing. We have solved the dynamic equations governing the energy flow using massive parallel programming and graphics processing units.

We have analysed the role of the vibrational degrees of freedom to the energy transmission in green sulfur bacteria, the time dependent effects due to light-matter interaction in charge transfer dynamics and discussed different pathways for the energy transfer in the PSI large photosynthetic system.

We have reproduced spectroscopic experiments including transient absorption spectra, linear absorption, fluorescence, linear and circular dichroism and 2D electronic spectra for a polarized laser sequence.

We have studied different complex photosynthetic systems: the reaction center transfer dynamics for a simplified trimer system, the paradigmatic Fenna Mathew Olson pigment-protein complex, the whole photosynthetic apparatus of green sulfur bacteria (see fig. 1) and the large photosynthetic complex Photo System I.

In addition, we have explored the use of innovative numerical methods such as machine learning to map correlations between systems’ parameters and spectra images.

The results of the project have been published in 5 peer-reviewed scientific papers. In addition, the Fellow has participated in 10 dissemination and communication activities.
Compared to the state of the art in the research field, there are several innovations in our project:
1. Inclusion of vibrational modes and electronic excitations on the same footing using HEOM to model the energy flow in large photosynthetic molecules of ~ 100 sites. This is one order of magnitude bigger than previous quantum dynamic studies which have concentrated in small complexes of ~10 sites.
2. Use of a time-dependent laser sequence to model transient absorption spectra. There are currently no other results available for HEOM with time dependent Hamiltonians.
3. Accurate modelling of spectroscopic experimental results for different systems and experimental settings.
4. New fast algorithms for highly parallel supercomputers.
5. Use of novel tools such as machine learning to understand spectroscopic experiments of light harvesting complexes

Wider impact in applications of efficient green energy devices is expected from the contributions of this project to the understanding of the energy flow in large photosynthetic molecules.
Fig 1. Energy flow in the photosynthetic apparatus of Green Sulfur Bacteria.