Environment-assisted quantum walks in photosynthetic energy transfer.

J Chem Phys

Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford St., Cambridge, Massachusetts 02138, USA.

Published: November 2008

Energy transfer within photosynthetic systems can display quantum effects such as delocalized excitonic transport. Recently, direct evidence of long-lived coherence has been experimentally demonstrated for the dynamics of the Fenna-Matthews-Olson (FMO) protein complex [Engel et al., Nature (London) 446, 782 (2007)]. However, the relevance of quantum dynamical processes to the exciton transfer efficiency is to a large extent unknown. Here, we develop a theoretical framework for studying the role of quantum interference effects in energy transfer dynamics of molecular arrays interacting with a thermal bath within the Lindblad formalism. To this end, we generalize continuous-time quantum walks to nonunitary and temperature-dependent dynamics in Liouville space derived from a microscopic Hamiltonian. Different physical effects of coherence and decoherence processes are explored via a universal measure for the energy transfer efficiency and its susceptibility. In particular, we demonstrate that for the FMO complex, an effective interplay between the free Hamiltonian evolution and the thermal fluctuations in the environment leads to a substantial increase in energy transfer efficiency from about 70% to 99%.

Download full-text PDF

Source
http://dx.doi.org/10.1063/1.3002335DOI Listing

Publication Analysis

Top Keywords

energy transfer
20
transfer efficiency
12
quantum walks
8
transfer
6
energy
5
environment-assisted quantum
4
walks photosynthetic
4
photosynthetic energy
4
transfer energy
4
transfer photosynthetic
4

Similar Publications

Rational regulation of interface structure in photocatalysts is a promising strategy to improve the photocatalytic performance of carbon dioxide (CO) reduction. However, it remains a challenge to modulate the interface structure of multi-component heterojunctions. Herein, a strategy integrating heterojunction with facet engineering is developed to modulate the interface structure of metal-organic frameworks (MOF)-based heterojunctions.

View Article and Find Full Text PDF

Characterisation and anaerobic digestion of fat, oil and grease (FOG) waste from wastewater treatment plants.

J Environ Manage

January 2025

Department of Civil, Environmental and Architectural Engineering, University of Padova, Via Marzolo 9, 35131, Padova, Italy.

The materials removed in the oil separation units of wastewater treatment plants can be referred to as fat, oil and grease (FOG) waste. FOG waste accumulation in treatment plants can cause clogging of pipes, production of excessive scums and foams, and negatively affect air/liquid oxygen transfer. While conventional disposal routes of this material can be limited by its water and organic content, FOG can represent a source of bio-energy other than bio-diesel production.

View Article and Find Full Text PDF

Residence time of particles in indoor surface networks.

J Hazard Mater

January 2025

Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, PR China; Faculty of Architecture, The University of Hong Kong, Hong Kong, PR China. Electronic address:

Infectious microbes can spread rapidly from fomites (contaminated surfaces) via hand touch, with prolonged residence time on surfaces increasing transmission risk by extending exposure periods and/or involving more susceptible individuals. Existing studies have focused on decreasing microbial contamination, but not on the need for rapid removal from surface systems. This study introduces residence time as the time that a microbe spends within the surface system.

View Article and Find Full Text PDF

Photoassisted lithium-sulfur (Li-S) batteries offer a promising approach to enhance the catalytic transformation kinetics of polysulfide. However, the development is greatly hindered by inadequate photo absorption and severe photoexcited carriers recombination. Herein, a photonic crystal sulfide heterojunction structure is designed as a bifunctional electrode scaffold for photoassisted Li-S batteries.

View Article and Find Full Text PDF

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.

J Chem Inf Model

January 2025

Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.

Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!