A DFT analysis on the superlubricity performance of structural superlubricity micro/nano-component on silicon-based surface

Abstract

Friction and wear are important factors which limit the development of Micro-electromechanical Systems (MEMS). Therefore, the research and preparation of wear-resistant micro and nano-functional structures in the field of MEMS has profound importance. Structural superlubricity micro/nano-components (the atomic layers are in incommensurate contact, which means that the friction and wear rate is nearly zero when the layers slide) are expected to be the basic micro and nano functional structures for fabricating ultra wear-resistant MEMS. At present, there is a lack of research on the properties of structural superlubricity micro/nano-components on the surface of silicon, which is known to be the most mainstream base material for MEMS. In this paper, the electronic properties and the atomic-scale friction of the silicon-based surface structural superlubricity micro/nano-components are simulated using first-principles calculations based on the Density functional theory (DFT). By analyzing the silicon-based surface structural superlubricity micro/nano-component with adhesion performances and superlubricity characteristics. The calculation shows that the binding energy value of its lower graphene layer is larger than that of the upper layer during the slip process, and it is found that the friction force of the silicon-based structure can reach the range of 10−3 nN and the average friction coefficient can reach the range of 10−3 in the incommensurate state. Throughout the sliding process, electrostatic repulsion plays an important role in the tribological properties. The larger the electrostatic repulsion, the smoother the potential energy fluctuation, indicating less friction, while the analysis of the charge mechanism further justifies the conclusion.