Feature-oriented scanning methodology for probe microscopy and nanotechnology

A real-time scanning algorithm is suggested which uses features of the surface as reference points at relative movements. Generally defined hill- or pit-like topography elements are taken as the features. The operation of the algorithm is based upon local recognition of the features and their connection to each other. The permissible class of surfaces includes ordered, partially ordered, or disordered surfaces if their features have comparable extents in the scan plane. The method allows one to exclude the negative influence of thermodrift, creep, and hysteresis over the performance of a scanning probe microscope. Owing to the possibility of carrying out an unlimited number of averages, the precision of measurements can be considerably increased. The distinctive feature of the method is its ability of topography reconstruction when the ultimate details are smaller than those detectable by a conventional microscope scan. The suggested approach eliminates the restrictions on scan size. Nonlinearity, nonorthogonality, cross coupling of manipulators as well as the Abbe offset error are corrected with the use of scan-space-distributed calibration coefficients which are determined automatically in the course of measuring a standard surface by the given method. The ways of precise probe positioning by local surface features within the fine manipulator field and the coarse manipulator field, automatic probe return into the operational zone after sample dismounting, automatic determination of exact relative position of the probes in multiprobe instruments, as well as automatic successive application of the whole set of probes to the same object on the surface are proposed. The possibility of performing accurately localized low-noise spectroscopy is demonstrated. The developed methodology is applicable for any scanning probe devices.