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Issue 56, 2016
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Controlling nanoflake motion using stiffness gradients on hexagonal boron nitride

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Abstract

Durotaxis has been emerging as a novel technique for manipulating directional motion of nanoscale particles. Two-dimensional materials with low surface friction, such as hexagonal boron nitride (hBN), are well-suited to serve as a platform for solid–solid transportations or manipulations. Here we employ molecular dynamics simulations to explore the feasibility of utilizing a stiffness gradient on a large hBN substrate to control the motion of a small hBN or graphene nanoflake on it. Our attempts to systematically investigate the mechanism of durotaxis-induced transportation are centered on the fundamental driving mechanism of the motion and the quantitative effect of significant parameters such as stiffness gradient, substrate temperature, and material of the nanoflake on its motion. Simulation results have demonstrated that, while the stiffness gradient plays a pivotal role in the evolution of the motion of the nanoflake on the substrate surface, the temperature of the substrate greatly influences the behavior of the nanoflake as well. There is no significant difference in directional motion between hBN and graphene nanoflakes on the hBN substrate. An interesting relation between the effective driving force and the stiffness gradient has been quantitatively captured by employing steered molecular dynamics. These findings will provide fundamental insights into the motion of nanodevices on a solid surface due to durotaxis, and will offer a novel view for manipulating directional motion of nanoscale particles on a solid surface.

Graphical abstract: Controlling nanoflake motion using stiffness gradients on hexagonal boron nitride

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Publication details

The article was received on 20 Feb 2016, accepted on 19 May 2016 and first published on 20 May 2016


Article type: Paper
DOI: 10.1039/C6RA04535A
Citation: RSC Adv., 2016,6, 51205-51210
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    Controlling nanoflake motion using stiffness gradients on hexagonal boron nitride

    M. Becton and X. Wang, RSC Adv., 2016, 6, 51205
    DOI: 10.1039/C6RA04535A

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