Near-field scanning probe microwave microscopy (NSSM) offers great potential to facilitate characterization, development, and modeling of novel materials. Based on measured microwave images at multiple frequencies and amplitudes (along with simultaneous optical,direct current,and Atomic Force measurements), one can study material and device physics at different lateral and depth scales. We focus on research and development of statistical methods to enable and/or optimize NSSM measurement science and metrology for characterization of materials and devices. Experimental applications include: studies of dopants and defects in nanowires and semiconductors; characterization of wavelength-dependent conductivity and localized depletion regions in photovoltaics; cellular imaging and DNA studies of biological materials.
Statistical efforts focus on extracting information from NSSM images contaminated by additive noise and artifacts. We developed robust implementations of local likelihood and local regression methods to level images, remove scan-dependent artifacts, and denoise images. Our methods smooth out additive noise while preserving edge-like features in images and remove artifacts that vary from scan line to scan line in a way such that the influence of possible outliers are downweighted. Due to capacitive coupling, microwave reflection coefficient images depend on both material properties and topographic variations. Accounting for this interaction is a key on-going research problem. Our methods are applicable to other raster and scanning probe imaging modalities including: laser microscopy, scanning coherent anti-Stokes Raman microscopy, Raman spectroscopy, luminescence imaging, fluorescent imaging and single molecule spectroscopy, photo acoustic molecular imaging, nonlinear sum frequency generation imaging, and aberration-corrected scanning transmission electron microscopy.
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