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Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns
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 ne...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514826/ https://www.ncbi.nlm.nih.gov/pubmed/26207990 http://dx.doi.org/10.1371/journal.pone.0133088 |
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author | Murphy, Jeffrey N. Harris, Kenneth D. Buriak, Jillian M. |
author_facet | Murphy, Jeffrey N. Harris, Kenneth D. Buriak, Jillian M. |
author_sort | Murphy, Jeffrey N. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4514826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45148262015-07-29 Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns Murphy, Jeffrey N. Harris, Kenneth D. Buriak, Jillian M. PLoS One Research Article 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. Public Library of Science 2015-07-24 /pmc/articles/PMC4514826/ /pubmed/26207990 http://dx.doi.org/10.1371/journal.pone.0133088 Text en © 2015 Murphy et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Murphy, Jeffrey N. Harris, Kenneth D. Buriak, Jillian M. Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title | Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title_full | Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title_fullStr | Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title_full_unstemmed | Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title_short | Automated Defect and Correlation Length Analysis of Block Copolymer Thin Film Nanopatterns |
title_sort | automated defect and correlation length analysis of block copolymer thin film nanopatterns |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514826/ https://www.ncbi.nlm.nih.gov/pubmed/26207990 http://dx.doi.org/10.1371/journal.pone.0133088 |
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