Maria Cadena.pdf (56.43 MB)
Observing and Reconstructing Subsurface Nanoscale Features Using Dynamic Atomic Force Microscopy
thesis
posted on 2019-01-03, 19:18 authored by Maria Jose J. Cadena VinuezaMaria Jose J. Cadena VinuezaThe atomic force microscope (AFM), traditionally known as a nanoscale instrument for surface topography imaging and compositional contrast, has a unique ability to investigate buried, subsurface objects in non-destructive ways with very low energy. The underlying principle is the detection of interactions between the AFM probe and the sample subsurface in the presence of an external wave or eld. The AFM is a newcomer to the fi eld of subsurface imaging, in comparison to other available highresolution techniques like transmission or scanning electron microscopy. Nevertheless,
AFM offers signi cant advantages for subsurface imaging, such as the operation over a wide range of environments, a broad material compatibility, and the ability to investigate
local material properties. These make the AFM an essential subsurface characterization tool for materials/devices that cannot be studied otherwise.
This thesis develops a comprehensive qualitative and quantitative framework underpinning the subsurface imaging capability of the AFM. We focus on the detection of either electrostatic force interactions or local mechanical properties, using 2nd-harmonic Kelvin probe force microscopy (KPFM) and contact-resonance AFM (CRAFM),
respectively. In 2nd-harmonic KPFM we exploit resonance-enhanced detection to boost the subsurface contrast with higher force sensitivity. In CR-AFM we use the dual AC resonance tracking (DART) technique, in which the excitation frequencies are near one of the contact resonance frequencies. Both techniques take advantage of the maximized response of the cantilever at resonance which improves the signal to noise ratio. These enable high-resolution subsurface mapping on a variety of polymer
composites.
A relevant challenge is the ability to reconstruct the properties of the subsurface objects from the experimental observables. We propose a method based on surrogate
modelling that relies on computer experiments using nite element models. The latter are valuable due to the lack of analytical solutions that satisfy the complexity of the geometry of the probe-sample system and sample heterogeneity. We believe this work is of notable interest because offers one of few approaches for the non-destructive characterization of buried features with sub-micron dimensions.
History
Degree Type
- Doctor of Philosophy
Department
- Mechanical Engineering
Campus location
- West Lafayette
