Near-field scanning microwave microscopy (SMM) employs microwave radiation to image and characterize samples down to the atomic scale, including soft biological structures or inorganic materials, such as ferroelectric films. However, SMM generally also senses sample topography; hypersensitivity to topography becomes problematic with additional parasitic contributions and may partially or completely mask nontopographic sample features in the data, such as contrast in electrical conductivity or permittivity. This work proposes a simple and effective procedure to remove unwanted parasitic effects from SMM images. Differently from existing procedures, the method is applicable either in postprocessing or in real time, i.e., during the scanning operation. This allows the immediate visualization of nontopographic sample features in the instrument screen. As a proof of concept, hafnium zirconium oxide (HfZrO) ferroelectric film with high surface roughness is studied; unwanted contributions were removed from SMM data, providing a clear map of the sample ferroelectric structure that was originally hidden.
Real-Time Removal of Topographic Artifacts in Scanning Microwave Microscopy / Fabi, G.; Joseph, C. H.; Pavoni, E.; Wang, X.; Hadi, R. A.; Hwang, J. C. M.; Morini, A.; Farina, M.. - In: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. - ISSN 0018-9480. - (2021), pp. 1-1. [10.1109/TMTT.2021.3060756]
Real-Time Removal of Topographic Artifacts in Scanning Microwave Microscopy
Fabi G.;Joseph C. H.;Pavoni E.;Morini A.;Farina M.
2021-01-01
Abstract
Near-field scanning microwave microscopy (SMM) employs microwave radiation to image and characterize samples down to the atomic scale, including soft biological structures or inorganic materials, such as ferroelectric films. However, SMM generally also senses sample topography; hypersensitivity to topography becomes problematic with additional parasitic contributions and may partially or completely mask nontopographic sample features in the data, such as contrast in electrical conductivity or permittivity. This work proposes a simple and effective procedure to remove unwanted parasitic effects from SMM images. Differently from existing procedures, the method is applicable either in postprocessing or in real time, i.e., during the scanning operation. This allows the immediate visualization of nontopographic sample features in the instrument screen. As a proof of concept, hafnium zirconium oxide (HfZrO) ferroelectric film with high surface roughness is studied; unwanted contributions were removed from SMM data, providing a clear map of the sample ferroelectric structure that was originally hidden.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
