RESUMO
Thin films, papers, or foils produced from graphene-based materials have been the focus of considerable research interest in recent years. They have a range of applications including energy storage, selective filtration of liquids, and gas storage. For all of these applications, the critical attribute of the films is their pore volume. However, there remains a considerable challenge around characterizing the accessible microscopic surface area of the materials in their intended state of application. In this work, an image-processing-based approach is presented for estimating the lower threshold of specific surface area for graphene-based films that have a typical multilayered structure. Canny edge detection is used together with tortuosity measurements to infer sheet areas from layer edges. The method serves as a simple independent characterization technique. Specific surface area values predicted for a range of similar films vary by less than 4× the reported values, which vary by >1.1×103 in range.
