Systematic quantitative characterisation of surface nanostructures by scanning probe microscopy of thin-films

In this article, we present a new methodology to characterise surface nanostructures of thin films. The methodology focuses on isolating nanostructures and extracting quantitative information, such as their shape and size, based on atomic force microscopy (AFM) data. We start by compensating the AFM data for some specific classes of measurement artefacts. After that, the methodology employs two distinct approaches. The first, which we call the overlay approach, proceeds by systematically processing the raster data that constitute the scanning probe image in both vertical and horizontal directions. The second approach, based on fuzzy logic, relies on a fuzzy inference engine to classify the surface points. Once classified, these points are clustered into surface structures. We have applied both approaches to characterise organic semiconductor thin films of pentacene on different substrates. In this article, we present results employing both approaches to pentacene films deposited on mica. Using only the overlay approach, we have compared the pentacene film characteristics grown on different substrates. These results are discussed and compared along with the challenges of the two approaches.