# Granular Motor in the Non-Brownian Limit

## TL;DR

This paper experimentally investigates a granular rotor's behavior across different temperature regimes, revealing limitations of existing models at low temperatures and proposing an extended model that accurately describes the rotor's angular velocity distribution.

## Contribution

The authors extend existing models to account for non-constant deceleration due to external friction, achieving accurate descriptions across all temperature regimes.

## Key findings

- At high granular temperatures, the rotor exhibits Brownian motion behavior.
- At low temperatures, collisions are rare and external friction dominates, causing the rotor to mostly rest.
- The extended model accurately predicts the angular velocity distribution across all temperature regimes.

## Abstract

In this work we experimentally study a granular rotor which is similar to the famous Smoluchowski-Feynman device and which consists of a rotor with four vanes immersed in a granular gas. Each side of the vanes can be composed of two different materials, creating a rotational asymmetry and turning the rotor into a ratchet. When the granular temperature is high, the rotor is in movement all the time, and its angular velocity distribution is well described by the Brownian Limit discussed in previous works. When the granular temperature is lowered considerably we enter the so-called Single Kick Limit, where collisions occur rarely and the unavoidable external friction causes the rotor to be at rest for most of the time. We find that the existing models are not capable of adequately describing the experimentally observed distribution in this limit. We trace back this discrepancy to the non-constancy of the deceleration due to external friction and show that incorporating this effect into the existing models leads to full agreement with our experiments. Subsequently, we extend this model to describe the angular velocity distribution of the rotor for any temperature of the gas, and obtain a very good agreement between the model and experimental data.