Professor David Sivak was recently published in Physical Review E.

research

Study of energy efficiency in proteins leads to new design principle for electronics

November 07, 2016
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By Ian Bryce

Researchers are closer to understanding how microscopic protein machines harness and use energy thanks to a new study from Simon Fraser University physics professor David Sivak.

His research findings have led to a design principle that could make computers faster and more energy efficient.

Sivak says that, at the molecular level, objects are constantly buffeted around by frequent random forces—referred to as ‘noise’—from surrounding molecules. In his study, “Thermodynamic Geometry Of Minimum-Dissipation Driven Barrier Crossing,” he tested how molecular biological engines, such as proteins, use energy to best navigate noisy environments.

“While engineers understand in great detail how to make efficient human-sized machines, such as car engines that convert between chemical and mechanical energy, we are only beginning to learn the basic physical principles governing these biological microscopic machines,” says Sivak. “This study answers a central question in biological physics about how these microscopic machines can maximize their ‘miles per gallon.’”

Published in Physical Review E, Sivak and collaborator Gavin Crooks of Lawrence Berkeley National Laboratory, used theoretical and computational modeling to find that proteins use environmental noise to help overcome obstacles and reduce their energy usage. The findings have led Sivak and Crooks to a design principle for how proteins maximize their energy efficiency.

Sivak’s research may have far-reaching implications.

“The engineering principle we’ve identified can guide the design of computer memory storage and retrieval, artificial photosynthesis, and more specific drugs,” he says.

Designing more energy-efficient computer memory would reduce the amount of heat generated, he says, requiring less cooling and allowing systems to run at a higher speed.

Funding for this study was provided through grants from the Natural Sciences and Engineerings Research Council of Canada (NSERC), the United States Army Research Office. Compute Canada provided computational resources.