Variety, the spice of life and essential for robustness in excitation energy transfer in light-harvesting complexes

2020 ◽  
Vol 221 ◽  
pp. 59-76 ◽  
Author(s):  
Sue Ann Oh ◽  
David F. Coker ◽  
David A. W. Hutchinson
Keyword(s):  
Energy Transfer ◽  
Excitation Energy ◽  
Recent Work ◽  
Energy Transport ◽  
Light Harvesting ◽  
Excitation Energy Transfer ◽  
Light Harvesting Complexes ◽  
Protein Scaffold ◽  
Site Variation

We review our recent work showing how important the site-to-site variation in coupling between chloroplasts in FMO and their protein scaffold environment is for energy transport in FMO and investigate the role of vibronic modes in this transport.

scholarly journals Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics

2021 ◽  
Author(s):  
Arif Ullah ◽  
Pavlo O. Dral
Keyword(s):  
Artificial Intelligence ◽  
Energy Transfer ◽  
Excitation Energy ◽  
Quantum Dynamics ◽  
Light Harvesting ◽  
Computational Cost ◽  
Excitation Energy Transfer ◽  
Reorganization Energy ◽  
Quantum Effects ◽  
Light Harvesting Complexes

Exploring excitation energy transfer (EET) in light-harvesting complexes (LHCs) is essential for understanding the natural processes and design of highly-efficient photovoltaic devices. LHCs are open systems, where quantum effects may play a crucial role for almost perfect utilization of solar energy. Simulation of energy transfer with inclusion of quantum effects can be done within the framework of dissipative quantum dynamics (QD), which are computationally expensive. Thus, artificial intelligence (AI) offers itself as a tool for reducing the computational cost. We suggest AI-QD approach using AI to directly predict QD as a function of time and other parameters such as temperature, reorganization energy, etc., completely circumventing the need of recursive step-wise dynamics propagation in contrast to the traditional QD and alternative, recursive AI-based QD approaches. Our trajectory-learning AI-QD approach is able to predict the correct asymptotic behavior of QD at infinite time. We demonstrate AI-QD on seven-sites Fenna–Matthews–Olson (FMO) complex.

scholarly journals Strategies to enhance the excitation energy-transfer efficiency in a light-harvesting system using the intra-molecular charge transfer character of carotenoids

2017 ◽  
Vol 198 ◽  
pp. 59-71 ◽  
Author(s):  
Nao Yukihira ◽  
Yuko Sugai ◽  
Masazumi Fujiwara ◽  
Daisuke Kosumi ◽  
Masahiko Iha ◽  
...  
Keyword(s):  
Energy Transfer ◽  
Charge Transfer ◽  
Excitation Energy ◽  
Brown Algae ◽  
Light Harvesting ◽  
Excitation Energy Transfer ◽  
Light Harvesting Complexes ◽  
Light Harvesting Complex ◽  
Molecular Charge ◽  
Intra Molecular Charge Transfer

Fucoxanthin is a carotenoid that is mainly found in light-harvesting complexes from brown algae and diatoms. Due to the presence of a carbonyl group attached to polyene chains in polar environments, excitation produces an excited intra-molecular charge transfer. This intra-molecular charge transfer state plays a key role in the highly efficient (∼95%) energy-transfer from fucoxanthin to chlorophyllain the light-harvesting complexes from brown algae. In purple bacterial light-harvesting systems the efficiency of excitation energy-transfer from carotenoids to bacteriochlorophylls depends on the extent of conjugation of the carotenoids. In this study we were successful, for the first time, in incorporating fucoxanthin into a light-harvesting complex 1 from the purple photosynthetic bacterium,Rhodospirillum rubrumG9+ (a carotenoidless strain). Femtosecond pump-probe spectroscopy was applied to this reconstituted light-harvesting complex in order to determine the efficiency of excitation energy-transfer from fucoxanthin to bacteriochlorophyllawhen they are bound to the light-harvesting 1 apo-proteins.

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