Date

1-1-2020

Document Type

Dissertation

Degree

Doctor of Philosophy

Department

Electrical Engineering

First Adviser

James C. Hwang

Abstract

The electromagnetic properties of a live biological system are extremely important to many medical applications. While information about electromagnetic properties of tissues are available in the literature, little or no data are available for a single cell or subcellular structures. Microwave biological/cell detection has been demonstrated to be useful and promising in many medical applications due to its internal properties such as non-invasive, fast and label-free. However, the spatial work dimension, therefore the resolution, of the state-of-the-art electrical measurement and detection techniques is limited. To further bring the spatial resolution of the electrical characterization technique down to the sub-cellular level or even nanometer level, scanning microwave microscopy (SMM) is one of the most promising approaches.

In this work, we mainly developed quantitative characterization by SMM. Analytical model, full-wave simulation and experimental results are all covered. The results on both a dry cell and a live cell in its physiological buffer are discussed. The challenges for quantitative SMM of soft matter in liquid were overcome by both experimental control and characterizing the whole probe-sample interaction through multiscale finite-element full-wave electromagnetic simulation. 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.

Other progress such as the invention of an inverted scanning microwave microscope and broadband scanning microwave microscope are also briefly discussed. Non-invasive, quantitative, broadband and high spatial resolution characterization of different types of samples can be improved with further development of SMM.

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