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Professor develops algorithm to understand electron dynamics in light-harvesting reactions

NSF grant funds quantum physics research

University of Houston

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IMAGE: Eric Bittner, Moores professor of Chemical Physics, received a 3-year $450K grant from the National Science Foundation to study electron transfer systems in light-harvesting bacterial chromophores. view more 

Credit: University of Houston College of Natural Sciences and Mathematics

The paradox in quantum mechanics is the way a particle, such as an electron, can appear to be in two places at once. This duality lies at the heart of quantum physics and may be the key to how nature harvests light, converting it to chemical energy.

"In quantum mechanics, there's a communication between the different possible locations that is entirely due to electron dynamics," said Eric Bittner, Moores Professor of Chemical Physics at the University of Houston.

Bittner studies this mechanism in the context of electron transfer systems, which are a class of materials used for light harvesting or energy conversion. His research is the recipient of a recent three-year, $450,000 grant from the National Science Foundation.

Light-Harvesting Reactions: Optimized Pathways

Along with collaborators at the University of Michigan, Bittner's research group will be examining electron transfer reactions in light-harvesting bacterial chromophores, which convert light energy to chemical energy.

Light-harvesting reactions work by energizing electrons, which will then get transferred from one complex to another, releasing energy at each step. This energy is harvested and stored through a series of reactions.

"Nature has figured out how to optimize these pathways after billions of years of evolution," Bittner said, "We want to discover what those pathways are."

Algorithm to Predict Electronic Coupling

They'll accomplish this with an algorithm, developed by Bittner's research group, which can predict the coupling between nuclear motions and electron movement. Results demonstrating the functionality of this algorithm were recently published in the journal Nature Communications.

"This is a predictive algorithm, one that makes a guess, refines the guess, then makes another guess, until it arrives at the optimal condition," Bittner said. "This algorithm is similar in principle to the intelligent search algorithms used by Netflix and Google."

In these electron transfer systems, the interaction between nuclear motions and electron dynamics can affect electron movement. Certain nuclear motions can have a dampening effect on electronic movement, while others will simply have no effect.

Bittner and collaborators will be using their algorithm to predict these pathways. Doing so is a lengthy process, one that requires thousands of calculations that will take a high-performance computer months to perform.

However, there are benefits.

"One of the advantages of the algorithm is that it does not need to rely upon previous assumptions to find an answer," Bittner said.

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