An Experimental Study to Guide AFM-Based TBN of Nanochannels

Abstract

Tip-based nanomanufacturing (TBN) approach generally involves the use of nanoscale tool tips in various nanomanufacturing processes such as machining, patterning, and assembling. AFM-based TBN has been applied to fabricate various micro/nanodevices. In AFM-based TBN process, the AFM tip is used as a tool for material removal or surface modification of nanoscale materials. To fabricate a desirable nanostructure, the AFM-based TBN parameters, i.e. applied load, tip speed, feed rate, scratching direction, tip geometry, tip radius, and number of scratching cycles, must be carefully chosen. These parameters have major effects on the depth, width, chip formation, and surface roughness of the machined surface. In order to control AFM-based TBN process efficiently, there is a need to conduct a more focused study of the effects of these different parameters on the process performance and outcome. This is achieved by experimentally validating a MD simulation model of AFM-based nanomachining, and using it to conduct parametric studies to guide AFM-based TBN. In this work, a 3D MD model with a larger domain size was developed and used to gain a unique insight into the AFM-based TBN process. The parametric studies conducted using both MD model simulations and AFM experiments are presented. In addition, AFM-based TBN is used with photolithography to fabricate a nanofluidic device for medical application.