Feature-oriented scanning methodology for probe microscopy and nanotechnology

Abstract

A real-time scanning algorithm is suggested which uses features of the surface as referencepoints at relative movements. Generally defined hill- or pit-like topography elements aretaken as the features. The operation of the algorithm is based upon local recognition of thefeatures and their connection to each other. The permissible class of surfaces includesordered, partially ordered, or disordered surfaces if their features have comparable extentsin 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 tothe possibility of carrying out an unlimited number of averages, the precisionof measurements can be considerably increased. The distinctive feature of themethod is its ability of topography reconstruction when the ultimate details aresmaller than those detectable by a conventional microscope scan. The suggestedapproach eliminates the restrictions on scan size. Nonlinearity, nonorthogonality,cross coupling of manipulators as well as the Abbé offset error are corrected withthe use of scan-space-distributed calibration coefficients which are determinedautomatically in the course of measuring a standard surface by the given method.The ways of precise probe positioning by local surface features within the finemanipulator field and the coarse manipulator field, automatic probe return into theoperational zone after sample dismounting, automatic determination of exactrelative position of the probes in multiprobe instruments, as well as automaticsuccessive application of the whole set of probes to the same object on the surface areproposed. The possibility of performing accurately localized low-noise spectroscopy isdemonstrated. The developed methodology is applicable for any scanning probe devices.