Depth prediction model of nano-grooves fabricated by AFM-based multi-passes scratching method

This paper proposes a nano-groove depth prediction model for the atomic force microscopy (AFM)-based multi-passes scratching method in which the AFM tip is considered as a cone with a spherical apex. The relationship between the normal load applied on the sample and the depth of the machined nano-groove is systematically investigated for the multi-passes scratching process. Nano-grooves are fabricated with several normal loads and two passes scratches on a 2A12 aluminum alloy surface to verify the developed models. Results show that the hardness may become larger near the machined region after one pass scratching test and a correction factor is introduced into the two passes scratching model which is as a function of the first pass machined depths of the nano-grooves. Based on the correction model, several nano-grooves with an expected depth are machined with different normal loads for each pass in the two passes scratching tests and the difference between the experiment results and the expected values is less than 10%. Actually, to machine a nano-groove with a desired depth, this method has the potential to distribute the appropriate normal load applied for each pass to reduce the tip wear and be used for nano-groove depth correction using the multi passes scratching technique.