An adaptive non-raster scanning method in Atomic Force Microscopy for simple sample shapes

Kaiqiang Zhang, Toshiaki Hatano, Thang Nguyen Tien, Guido Herrmann, Edwards Christopher, Stuart C Burgess, Mervyn J Miles

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)


It is a significant challenge to reduce the scanning time in atomic force microscopy while retaining imaging quality. In this paper, a novel non-raster scanning method for high-speed imaging is presented. The method proposed here is developed for a specimen with the simple shape of a cell. The image is obtained by scanning the boundary of the specimen at successively increasing heights, creating a set of contours. The scanning speed is increased by employing a combined prediction algorithm, using a weighted prediction from the contours scanned earlier, and from the currently scanned contour. In addition, an adaptive change in the height step after each contour scan is suggested. A rigorous simulation test bed recreates the x–y specimen stage dynamics and the cantilever height control dynamics, so that a detailed parametric comparison of the scanning algorithms is possible. The data from different scanning algorithms are compared after the application of an image interpolation algorithm (the Delaunay interpolation algorithm), which can also run on-line.

Original languageEnglish
Article number035401
Number of pages12
JournalMeasurement Science and Technology
Issue number3
Early online date16 Feb 2015
Publication statusPublished - Mar 2015


Dive into the research topics of 'An adaptive non-raster scanning method in Atomic Force Microscopy for simple sample shapes'. Together they form a unique fingerprint.

Cite this