Power-efficiency constraint for chemical motors

Chemical gradients provide the primordial energy for biological functions by driving the mechanical movement of microscopic engines. Their thermodynamic properties remain elusive, especially concerning the dynamic change in energy demand in biological systems. In this article, we derive a constraint relation between the output power and the conversion efficiency for a chemically fueled steady-state rotary motor analogous to the F_{0} motor of ATPase. We find that the efficiency at maximum power is half of the maximum quasistatic efficiency. These findings shall aid in the understanding of natural chemical engines and inspire the manual design and control of chemically fueled microscale engines.

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Publication Details

Journal
Physical review. E
Published
2025-02-11
DOI
https://doi.org/10.1103/physreve.111.024404
Citations
3
Primary Topic
Advanced Thermodynamics and Statistical Mechanics
Type
article
Field-Weighted Citation Impact
3.97

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article

Power-efficiency constraint for chemical motors

Ruo-Xun Zhai, Hui Dong
3 citations
Physical review. E
Advanced Thermodynamics and Statistical Mechanics
3.97
article

Power-efficiency constraint for chemical motors

Ruo-Xun Zhai, Hui Dong
article en
3 citations

Abstract

Chemical gradients provide the primordial energy for biological functions by driving the mechanical movement of microscopic engines. Their thermodynamic properties remain elusive, especially concerning the dynamic change in energy demand in biological systems. In this article, we derive a constraint relation between the output power and the conversion efficiency for a chemically fueled steady-state rotary motor analogous to the F_{0} motor of ATPase. We find that the efficiency at maximum power is half of the maximum quasistatic efficiency. These findings shall aid in the understanding of natural chemical engines and inspire the manual design and control of chemically fueled microscale engines.

Physical review. EVol. 111(2)
China Academy of Engineering Physics (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 8%
Advanced Thermodynamics and Statistical Mechanics
3.97
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