Unlocking the potential of information flow: Maximizing free-energy transduction in a model of an autonomous rotary molecular motor

Mathis Grelier, David A. Sivak, and Jannik Ehrich
Phys. Rev. E 109, 034115 – Published 11 March 2024

Abstract

Molecular motors fulfill critical functions within all living beings. Understanding their underlying working principles is therefore of great interest. Here we develop a simple model inspired by the two-component biomolecular motor FoF1 ATP synthase. We analyze its energetics and characterize information flows between the machine's components. At maximum output power we find that information transduction plays a minor role for free-energy transduction. However, when the two components are coupled to different environments (e.g., when in contact with heat baths at different temperatures), we show that information flow becomes a resource worth exploiting to maximize free-energy transduction. Our findings suggest that real-world powerful and efficient information engines could be found in machines whose components are subjected to fluctuations of different strength, since in this situation the benefit gained from using information for work extraction can outweigh the costs of information generation.

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  • Received 13 April 2023
  • Accepted 30 January 2024

DOI:https://doi.org/10.1103/PhysRevE.109.034115

©2024 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsPhysics of Living Systems

Authors & Affiliations

Mathis Grelier1,2,*, David A. Sivak1,†, and Jannik Ehrich1,‡

  • 1Department of Physics, Simon Fraser University, Burnaby, BC, V5A 1S6 Canada
  • 2PULS Group, Department of Physics, FAU Erlangen-Nürnberg, IZNF, 91058 Erlangen, Germany

  • *mathis.grelier@fau.de
  • dsivak@sfu.ca
  • jehrich@sfu.ca

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Issue

Vol. 109, Iss. 3 — March 2024

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