Mapping self-assembled dots and line arrays by image analysis for quantification of defect density and alignment

Bottom-up alternative lithographic masks from directed self-assembly systems have been extending the limits of critical dimensions in a cost-effective manner although great challenges in controlling defectivity remain open. Particularly, defectivity and dimensional metrology are two main challenges in lithography due to the increasing miniaturisation of circuits. To gain insights about the percentage of alignment, defectivity and order quantification, directed self-assembly block copolymer fingerprints were investigated via an image analysis methodology. Here we present the analysis of hexagonal phase of polystyrene-b-polydimethylsiloxane (PS-b-PDMS) forming linear patterns in topological substrates. From our methodology, we have performed dimensional metrology estimating pitch size and error, and the linewidth of the lines was estimated. In parallel, the methodology allowed us identification and quantification of typical defects observable in self-assembly, such as turning points, disclination or branching points, break or lone points and end points. The methodology presented here yields high volume statistical data useful for advancing dimensional metrology and defect analysis of self- and directed assembly systems.