(171g) Automated Analysis of Orientational Order from Images of Fibrillar Thin Films

Nanofibers are a ubiquitous structural motif in a variety of functional materials. In the field of organic electronics, Ï?-Ï?-stacking of conjugated polymers leads to fibrillar morphologies with a wide array of fiber packing behavior. Fiber orientation and alignment are known to influence the charge transport properties of devices such as organic field effect transistors. The solution processing methods used to create these devices give rise to large variations in these structural parameters â?? however, they are only observable with imaging techniques such as atomic force microscopy (AFM). To bring more rigorous quantification of orientation and alignment to these materials, a comprehensive image analysis tool is introduced to quantify the two-dimensional orientation and alignment of nanofibers from atomic force microscopy (AFM) images. It has been developed in MATLAB and packaged as a standalone application so that researchers with no computational expertise can produce publication-ready figures directly from their images. AFM frequently yields images with low contrast and moderate noise, making quantitative feature extraction a significant challenge. In this protocol, each image is analyzed in the context of an Orientation Map, in which nanofibers are thinned to single-pixel width and an orientation is extracted for each of these pixels. The Orientation Map is obtained through a five-step process: fiber smoothing by anisotropic diffusion filtering, contrast enhancement by top hat filtering, binarization by adaptive thresholding, skeletonization, and recovery of orientations from the result of diffusion filtering. Each step involves parameters that can be set using physical heuristics, which are examined in detail. This Orientation Map yields an orientation distribution and a plot of S_2D, an orientational order parameter, as a function of frame size. The image analysis procedure is used to quantify differences in P3HT nanofiber morphology induced by various solution processing recipes, as well as the effect of spin-coating when used to deposit solutions of nanofibers. All examples presented in this protocol can be reproduced from beginning to end using the available software, with visualizations produced at each stage of processing.