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Polymer coatings on periodic nanostructures have facilitated advanced applications in various fields. The performance of these structures is intimately linked to their nanoscale characteristics. Smart polymer coatings responsive to environmental stimuli such as temperature, pH level, and ionic strength have found important uses in these applications. Therefore, to optimize their performance and improve their design, precise characterization techniques are essential for understanding the nanoscale properties of polymer coating, especially in response to stimuli and interactions with the surrounding medium. Due to their layered compositions, applying non-destructive measurement methods by X-ray/neutron scattering is optimal. These approaches offer unique insights into the structure, dynamics, and kinetics of polymeric coatings and interfaces. The caveat is that scattering methods require non-trivial data modeling, particularly in the case of periodic structures, which result in strong correlations between scattered beams. The dynamical theory (DT) model offers an exact model for interpreting off-specular signals from periodically structured surfaces and has been validated on substrates measured by neutron scattering. In this dissertation, we improved the model using a computational optimization approach that simultaneously fits specular and off-specular scattering signals and efficiently retrieves the three-dimensional sample profile with high precision. In addition, we extended this to the case of X-ray scattering. We applied this approach to characterize polymer brushes for nanofluidic applications and protein binding to modulated lipid membranes. This approach opens new possibilities in developing soft matter nanostructured substrates with desired properties for various applications. / Doctor of Philosophy / Polymer coatings on nanopatterned surfaces have recently facilitated advanced applications in various fields, particularly biotechnology. For example, multichannel surfaces coated with polymer can serve as nanofluidic devices for precise control of fluid flow in drug screening and detection of specific biomolecules. Moreover, polymer-coated nanopatterned surfaces, which possess similar properties to the extracellular matrix, provide excellent substrates for biological studies. The performance of these systems is closely tied to their nanoscale features, such as the thickness and conformation of the polymer layers. Therefore, high-resolution non-invasive nanoscale characterization techniques are essential for investigating these coatings to optimize their performance and enhance their design. X-ray/neutron scattering offers a non-destructive measurement method with unique capabilities in the nanoscale characterization of polymer coatings. However, scattering methods require non-trivial data modeling, particularly in the case of layered coatings on patterned surfaces. To tackle this challenge, we improved a dynamical theory (DT) model that allows for precise modeling of neutron and X-ray scattering signals from such systems. Using a computational optimization approach, the model enables efficient retrieval of the three-dimensional sample profile with high accuracy. We applied this approach to characterize polymer brushes for nanofluidic applications and protein binding to modulated lipid membranes. This methodology opens up new avenues for developing customizable, nanostructured substrates made from soft materials that possess tailored properties for a wide range of uses.

My doctoral research has focused on the development of surface plasmon resonance (SPR) reflectance imaging technique to detect near-field transport properties such as concentration, temperature, and salinity in micro/nano fluidic phenomena in label-free, real-time, and full-field manner. A label-free visualization technique based on surface plasmon resonance (SPR) reflectance sensing is presented for real-time and full-field mapping of microscale concentration and temperature fields. The key idea is that the SPR reflectance sensitivity varies with the refractive index of the near-wall region of the test mixture fluid. The Fresnel equation, based on Kretschmann’s theory, correlates the SPR reflectance with the refractive index of the test medium, and then, the refractive index correlates with the mixture concentration or temperature. The basic operation principle is summarized and the laboratory-developed SPR imaging/analyzing system is described with the measurement sensitivity, uncertainties and detection limitations of the implemented SPR reflectance imaging. Total five proposed uses of SPR reflectance imaging technique are presented: (1) micromixing concentration field development of ethanol penetrating into water contained in a micro-channel, (2) full-field detection of the near-wall salinity profiles for convective/diffusion of saline droplet into water, (3) full-field and real-time surface plasmon resonance imaging thermometry, (4) correlation of near-field refractive index of nanofluids with surface plasmon resonance reflectance, and (5) unveiling hidden complex cavities formed during nanocrystalline self-assembly.