Characterizing the Autonomous Motions of Linear Catalytic Nanomotors Using Molecular Dynamics Simulations

This work explores the efficacy of different characterization methods of identification of self-propelled motions of nanomotors out of overwhelming thermal noises. Here a linear catalytic nanomotor swimming in a two-dimensional fluid is investigated using the molecular dynamics simulation method. A model fuel-catalyst reactive force field is designed to produce exothermic decomposition reactions of diatomic fuel molecules into monatomic product molecules, which can be accelerated by the presence of model catalysts. Steady states with constant chemical composition and temperature are achieved by Monte Carlo product-to-reactant conversion operations and a Nose-Hoover thermostat, respectively. The self-propelled autonomous motion of the nanomotor is characterized by the accumulated displacement along the propulsion direction and the mean square displacement analysis. Compared to a control system without catalysts, it is found that, the chemical propulsion affects the linear motion considerably, but has little effect on its overall diffusion behavior due to rotational Brownian motions with a very short relaxation time. However, by confining the rotational degree of freedom, the diffusion of the nanomotor is evidently accelerated by the chemical propulsion. Thus, to characterize the autonomous motion of linear nanomotors, one can either track the trajectory of each nanomotor individually or measure the confined diffusive behavior of nanomotors collectively. The latter method is more appealing to implement experimentally.