Programmable Transport of C60 by Straining Graphene Substrate

M Vaezi and HN Pishkenari and MR Ejtehadi, LANGMUIR, 39, 4483-4494 (2023).

DOI: 10.1021/acs.langmuir.3c00180

Controlling the maneuverability of nanocars and molecular machines on the surface is essential for the targeted transportation of materials and energy at the nanoscale. Here, we evaluate the motion of fullerene, as the most popular candidate for use as a nanocar wheel, on the graphene nanoribbons with strain gradients based on molecular dynamics (MD), and theoretical approaches. The strain of the examined substrates linearly decreases by 20%, 16%, 12%, 8%, 4%, and 2%. MD calculations were performed with the open source LAMMPS solver. The essential physics of the interactions is captured by Lennard-Jones and Tersoff potentials. The motion of C60 on the graphene nanoribbon is simulated in canonical ensemble, which is implanted by using a Nose-Hoover thermostat. Since the potential energy of C60 is lower on the unstrained end of nanoribbons, this region is energetically more favorable for the molecule. As the strain gradient of the surface increases, the trajectories of the motion and the C60 velocity indicate more directed movements along the gradient of strain on the substrate. Based on the theoretical relations, it was shown that the driving force and diffusion coefficient of the C60 motion respectively find linear and quadratic growth with the increase of strain gradient, which is confirmed by MD simulations. To understand the effect of temperature, at each strain gradient of substrate, the simulations are repeated at the temperatures of 100, 200, 300, and 400 K. The large ratio of longitudinal speed to the transverse speed of fullerene at 100 and 200 K refers to the rectilinear motion of molecule at low temperatures. Using successive strain gradients on the graphene in perpendicular directions, we steered the motion of C60 to the desired target locations. The programmable transportation of nanomaterials on the surface has a significant role in different processes at the nanoscale, such as bottom-up assembly.

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