interestingly, we predicted this based on solely macroscopic principles:

"Based on the diameters of the input gear and output gear, and assuming an equal density of gear teeth, we can estimate a ttheoretical mechanical advantage (and so [...] a torque multiplication) of ∼6."
doi.org/10.1016/j.ch...

Thanks for the kind words Dean, and for your input in review

Much of the maths is based off work by @deanast.bsky.social. We hope that the plug-and-play nature of the interactive plot lowers the barrier to entry for those (like myself) who are more synthetically inclined.

Motor makers can input the values from their own designs to generate performance outcomes, or experiment with which changes will produce the best outcomes.

Finally, we highlight areas in which artifical machines lag behind their biological counterparts. In doing so, we propose avenues that might be fruitful for future research.

We contextualise the physical background with real examples - biological and artificial - so that it is now possible to compare and contrast a machine's performance. We end the paper with a Top Trumps of biological and artificial motors, comparing directionality, speed, stall force, efficiency, etc.

We often discuss how future artificial nanomachines might be useful. Excitingly, the tools now exist for us to live up to our words. We hope that papers like ours will act as guides to the important mechanistic, physical, and structural considerations underlying task performance.