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Computer vision distortion correction of scanning probe microscopy images

Since its inception, scanning probe microscopy (SPM) has established itself as the tool of choice for probing surfaces and functionalities at the nanoscale. Although recent developments in the instrumentation have greatly improved the metrological aspects of SPM, it is still plagued by the drifts an...

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Autores principales: Gaponenko, Iaroslav, Tückmantel, Philippe, Ziegler, Benedikt, Rapin, Guillaume, Chhikara, Manisha, Paruch, Patrycja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429659/
https://www.ncbi.nlm.nih.gov/pubmed/28386115
http://dx.doi.org/10.1038/s41598-017-00765-w
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author Gaponenko, Iaroslav
Tückmantel, Philippe
Ziegler, Benedikt
Rapin, Guillaume
Chhikara, Manisha
Paruch, Patrycja
author_facet Gaponenko, Iaroslav
Tückmantel, Philippe
Ziegler, Benedikt
Rapin, Guillaume
Chhikara, Manisha
Paruch, Patrycja
author_sort Gaponenko, Iaroslav
collection PubMed
description Since its inception, scanning probe microscopy (SPM) has established itself as the tool of choice for probing surfaces and functionalities at the nanoscale. Although recent developments in the instrumentation have greatly improved the metrological aspects of SPM, it is still plagued by the drifts and nonlinearities of the piezoelectric actuators underlying the precise nanoscale motion. In this work, we present an innovative computer-vision-based distortion correction algorithm for offline processing of functional SPM measurements, allowing two images to be directly overlaid with minimal error – thus correlating position with time evolution and local functionality. To demonstrate its versatility, the algorithm is applied to two very different systems. First, we show the tracking of polarisation switching in an epitaxial Pb(Zr(0.2)Ti(0.8))O(3) thin film during high-speed continuous scanning under applied tip bias. Thanks to the precise time-location-polarisation correlation we can extract the regions of domain nucleation and track the motion of domain walls until the merging of the latter in avalanche-like events. Secondly, the morphology of surface folds and wrinkles in graphene deposited on a PET substrate is probed as a function of applied strain, allowing the relaxation of individual wrinkles to be tracked.
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spelling pubmed-54296592017-05-15 Computer vision distortion correction of scanning probe microscopy images Gaponenko, Iaroslav Tückmantel, Philippe Ziegler, Benedikt Rapin, Guillaume Chhikara, Manisha Paruch, Patrycja Sci Rep Article Since its inception, scanning probe microscopy (SPM) has established itself as the tool of choice for probing surfaces and functionalities at the nanoscale. Although recent developments in the instrumentation have greatly improved the metrological aspects of SPM, it is still plagued by the drifts and nonlinearities of the piezoelectric actuators underlying the precise nanoscale motion. In this work, we present an innovative computer-vision-based distortion correction algorithm for offline processing of functional SPM measurements, allowing two images to be directly overlaid with minimal error – thus correlating position with time evolution and local functionality. To demonstrate its versatility, the algorithm is applied to two very different systems. First, we show the tracking of polarisation switching in an epitaxial Pb(Zr(0.2)Ti(0.8))O(3) thin film during high-speed continuous scanning under applied tip bias. Thanks to the precise time-location-polarisation correlation we can extract the regions of domain nucleation and track the motion of domain walls until the merging of the latter in avalanche-like events. Secondly, the morphology of surface folds and wrinkles in graphene deposited on a PET substrate is probed as a function of applied strain, allowing the relaxation of individual wrinkles to be tracked. Nature Publishing Group UK 2017-04-06 /pmc/articles/PMC5429659/ /pubmed/28386115 http://dx.doi.org/10.1038/s41598-017-00765-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gaponenko, Iaroslav
Tückmantel, Philippe
Ziegler, Benedikt
Rapin, Guillaume
Chhikara, Manisha
Paruch, Patrycja
Computer vision distortion correction of scanning probe microscopy images
title Computer vision distortion correction of scanning probe microscopy images
title_full Computer vision distortion correction of scanning probe microscopy images
title_fullStr Computer vision distortion correction of scanning probe microscopy images
title_full_unstemmed Computer vision distortion correction of scanning probe microscopy images
title_short Computer vision distortion correction of scanning probe microscopy images
title_sort computer vision distortion correction of scanning probe microscopy images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429659/
https://www.ncbi.nlm.nih.gov/pubmed/28386115
http://dx.doi.org/10.1038/s41598-017-00765-w
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