Data evaluation for surface-sensitive label-free methods to obtain real-time kinetic and structural information of thin films: A practical review with related software packages.

Interfacial layers are important in a wide range of applications in biomedicine, biosensing, analytical chemistry and the maritime industries. Given the growing number of applications, analysis of such layers and understanding their behavior is becoming crucial. Label-free surface sensitive methods are excellent for monitoring the formation kinetics, structure and its evolution of thin layers, even at the nanoscale. In this paper, we review existing and commercially available label-free techniques and demonstrate how the experimentally obtained data can be utilized to extract kinetic and structural information during and after formation, and any subsequent adsorption/desorption processes. We outline techniques, some traditional and some novel, based on the principles of optical and mechanical transduction. Our special focus is the current possibilities of combining label-free methods, which is a powerful approach to extend the range of detected and deduced parameters. We summarize the most important theoretical considerations for obtaining reliable information from measurements taking place in liquid environments and, hence, with layers in a hydrated state. A thorough treamtmaent of the various kinetic and structural quantities obtained from evaluation of the raw label-free data are provided. Such quantities include layer thickness, refractive index, optical anisotropy (and molecular orientation derived therefrom), degree of hydration, viscoelasticity, as well as association and dissociation rate constants and occupied area of subsequently adsorbed species. To demonstrate the effect of variations in model conditions on the observed data, simulations of kinetic curves at various model settings are also included. Based on our own extensive experience with optical waveguide lightmode spectroscopy (OWLS) and the quartz crystal microbalance (QCM), we have developed dedicated software packages for data analysis, which are made available to the scientific community alongside this paper.