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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. [ABSTRACT FROM AUTHOR]

This article reports the first quantitative characterization by scanning microwave microscopy (SMM) of a live cell in its physiological buffer. The challenges for quantitative SMM of soft matter in liquid were overcome mainly by characterizing the probe–sample interaction through multiscale finite-element full-wave electromagnetic simulation of not only the probe tip but also the probe body and holder. Using quantitative SMM, the relative permittivity of the center of a live L6 cell on the top of its nucleus was determined to be ($32\pm 6)-j(20 \pm 4)$ , which was in general agreement with the literature and simple estimation. Moreover, taking advantage of the noninvasiveness and subsurface sensitivity of SMM, it was used to monitor the physiological condition of the cell for hours. The results showed that the gradual shrinking of the cell footprint did not impact cell vitality significantly. These results implied that SMM could be a valuable technique for label-free noninvasive characterization of subcellular structures in a live cell, as well as its physio-pathological conditions. [ABSTRACT FROM AUTHOR]