微波食品加热
材料科学
铁电性
样品(材料)
介电常数
显微镜
光学
表面粗糙度
微波成像
显微镜
电介质
光电子学
计算机科学
物理
复合材料
热力学
电信
作者
Gianluca Fabi,Christopher Hardly Joseph,Eleonora Pavoni,Xiaopeng Wang,Richard Al Hadi,James C. M. Hwang,Antonio Morini,Marco Farina
标识
DOI:10.1109/tmtt.2021.3060756
摘要
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.
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