Efficiency of autonomous soft nano-machines at maximum power

TL;DR

This paper analyzes the efficiency at maximum power of nano-sized artificial and biological machines, revealing that it can surpass traditional bounds and categorizing machines into distinct classes based on their efficiency behavior.

Contribution

It introduces a classification of nano-machines based on their efficiency at maximum power and explores conditions under which efficiency exceeds classical limits.

Findings

Efficiency at maximum power can approach the thermodynamic limit 1.

Machines are categorized into three classes: 'strong and efficient', 'strong and inefficient', and 'balanced'.

Weakly coupled multicyclic machines lack universal efficiency bounds even in linear response.

Abstract

We consider nano-sized artificial or biological machines working in steady state enforced by imposing non-equilibrium concentrations of solutes or by applying external forces, torques or electric fields. For unicyclic and strongly coupled multicyclic machines, efficiency at maximum power is not bounded by the linear response value 1/2. For strong driving, it can even approach the thermodynamic limit 1. Quite generally, such machines fall in three different classes characterized, respectively, as "strong and efficient", "strong and inefficient", and "balanced". For weakly coupled multicyclic machines, efficiency at maximum power has lost any universality even in the linear response regime.