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Design and Optimization of Nanomaterials for Sensing Applications


Nanomaterials, materials with one or more of their dimensions on the nanoscale, have emerged as an important field in the development of next-generation sensing systems. Their high surface-to-volume ratio makes them useful for sensing, but also makes them sensitive to processing defects and inherent material defects. To develop and optimize these systems, it is thus necessary to characterize these defects to understand their origin and how to work around them. Scanning probe microscopy (SPM) techniques like atomic force microscopy (AFM) and scanning tunneling microscopy (STM) are important characterization methods which can measure nanoscale topography and electronic structure. These methods are appealing in nanomaterial systems because they are non-damaging and provide local, high-resolution data, and so are capable of detecting nanoscale features such as single defect sites. There are difficulties, however, in the interpretation of SPM data. For instance, AFM-based methods are prone to experimental artifacts due to long-range interactions, such as capacitive crosstalk in Kelvin probe force microscopy (KPFM), and artifacts due to the finite size of the probe tip, such as incorrect surface tracking at steep topographical features. Mechanical characterization (via force spectroscopy) of nanomaterials with significant nanoscale variations, such as tethered lipid bilayer membranes (tLBMs), is also difficult since variations in the bulk system’s mechanical behavior must be distinguished from local fluctuations. Additionally, interpretation of STM data is non-trivial due to local variations in electron density in addition to topographical variations.

In this thesis we overcome some limitations of SPM methods by supplementing them with additional surface analytical methods as well as computational methods, and we characterize several nanomaterial systems. Current-carrying vapor-liquid-solid Si nanowires (useful for interdigitated-electrode-based sensors) are characterized using finite-element-method (FEM)-supplemented KPFM to retrieve useful information about processing defects, contact resistance, and the primary charge carriers. Next, a tLBM system’s stiffness and the stiffness’ dependence on tethering molecule concentration is measured using statistical analysis of thousands of AFM force spectra, demonstrating a biosensor-compatible system with a controllable bulk rigidity. Finally, we utilize surface analytical techniques to inform the development of a novel three-dimensional graphene system for sensing applications.

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