Quartz tuning fork based three-dimensional topography imaging for sidewall with blind features

Abstract

Atomic force microscopy has a tremendous number of applications in a wide variety of fields, particularly in the semiconductor area for the 3D-stacked device. Imaging three-dimensional (3D) structures with blind features has progressively become a critical technique. Recently, a 3D-atomic force microscopy (AFM) technique has been proposed to image 3D features, especially those having sharp apices, like silicon pillars. However, the scanning strategy has drawbacks, such as long scanning time, and unstable operation, based on the premature algorithm. Herein, an improved 3D-AFM algorithm is reported that overcomes the aforementioned problems by an intelligent 3D scanning algorithm that incorporates sidewall history tracking, troubleshooting for sharp sidewall and sticking, and reactive direction adjustment. The proposed algorithm enables the 3D imagery of ZnO nano-rods and silicon nano-pillars to be achieved by using a high aspect-ratio multiwall carbon nanotube-based AFM probe, without time-consuming disorientation. This study establishes a method to construct a 3D image of arbitrary shape in reduced scanning time. © 2019 Elsevier B.V.