O.K. Kwon, J.W. Kang
Semyung University,
Korea
Keywords: molecular dynamics, graphene graphene nanoflake, oscillator
Summary:
Recently graphene has also been highlighted as an ideal lubricant for microelectromechanical systems (MEMSs) and nanoelectromechanical systems (NEMSs), where ‘traditional’ lubricants no longer function normally. Atomic-scale graphene can be fabricated using micro-mechanical chop crack, thermal expansion, and extension growth techniques. Monolayer graphene is considered a suitable material for investigating two-dimensional quantization phenomena, such as temperature-trigger plasma, quantization absorption spectrum, and the fractional quantum Hall effect. Additionally, the hexagonal symmetric structure of graphene makes it a candidate material for nano devices. In 2008, Zheng et al. reported a self-retracting motion of graphite flakes sheared from SiO2-covered graphite islands. They explained the phenomenon observed using models that included van der Waals forces, electrostatic force, and shear strengths, and discussed the potential applications in NEMSs with a wide range of mechanical frequencies, from megahertz and gigahertz. Such an experimentally observed self-retracting motion of graphite resulted in the idea of an oscillator based on the telescopic oscillation of graphene layers. A nanorelay based on the telescopic motion of graphene layers was also proposed. Here, we investigated the translational and rotational motions of a square graphene nanoflake with retracting motions by performing classical molecular dynamics simulations. Our results show that the kinetic energy of the translational motion was exchanged into the kinetic energy of the rotational motion. Thus, square graphene nanoflake oscillators have very low quality factors in translational motions. We discuss that square graphene nanoflakes have great potential to be a core component in nanoelectromechanical systems by detecting their motions with ultrahigh sensitivity to facilitate the development of sensor, memory, and quantum computing.