Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 26207990.
- Also identified by DOI 10.1371/journal.pone.0133088 and PMC identifier 4514826.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Line patterns produced by lamellae- and cylinder-forming block copolymer (BCP) thin films are of widespread interest for their potential to enable nanoscale patterning over large areas. In order for such patterning methods to effectively integrate with current technologies, the resulting patterns need to have low defect densities, and be produced in a short timescale. To understand whether a given polymer or annealing method might potentially meet such challenges, it is necessary to examine the evolution of defects. Unfortunately, few tools are readily available to researchers, particularly those engaged in the synthesis and design of new polymeric systems with the potential for patterning, to measure defects in such line patterns. To this end, we present an image analysis tool, which we have developed and made available, to measure the characteristics of such patterns in an automated fashion. Additionally we apply the tool to six cylinder-forming polystyrene-block-poly(2-vinylpyridine) polymers thermally annealed to explore the relationship between the size of each polymer and measured characteristics including line period, line-width, defect density, line-edge roughness (LER), line-width roughness (LWR), and correlation length. Finally, we explore the line-edge roughness, line-width roughness, defect density, and correlation length as a function of the image area sampled to determine each in a more rigorous fashion.
Medical subject headings
- Membranes, Artificial
- Nanostructures
- Pattern Recognition, Automated
- Polymers
- Polystyrenes
- Polyvinyls
- Pyridines