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Investigation on Blind Tip Reconstruction Errors Caused by Sample Features

Precision measurements of a nanoscale sample surface using an atomic force microscope (AFM) require a precise quantitative knowledge of the 3D tip shape. Blind tip reconstruction (BTR), established by Villarrubia, gives an outer bound with larger errors if the tip characterizer is not appropriate. I...

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Autores principales: Wan, Jiahuan, Xu, Linyan, Wu, Sen, Hu, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299057/
https://www.ncbi.nlm.nih.gov/pubmed/25490584
http://dx.doi.org/10.3390/s141223159
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author Wan, Jiahuan
Xu, Linyan
Wu, Sen
Hu, Xiaodong
author_facet Wan, Jiahuan
Xu, Linyan
Wu, Sen
Hu, Xiaodong
author_sort Wan, Jiahuan
collection PubMed
description Precision measurements of a nanoscale sample surface using an atomic force microscope (AFM) require a precise quantitative knowledge of the 3D tip shape. Blind tip reconstruction (BTR), established by Villarrubia, gives an outer bound with larger errors if the tip characterizer is not appropriate. In order to explore the errors of BTR, a series of simulation experiments based on a conical model were carried out. The results show that, to reconstruct the tip precisely, the cone angle of the tip characterizer must be smaller than that of the tip. Furthermore, the errors decrease as a function of the tip cone angle and increase linearly with the sample radius of curvature, irrespective of the tip radius of curvature. In particular, for sharp (20 nm radius) and blunt (80 nm radius) tips, the radius of curvature of the tip characterizer must be smaller than 5 nm. Based on these simulation results, a local error model of BTR was established. The maximum deviation between the errors derived from the model and the simulated experiments is 1.22 nm. Compared with the lateral resolution used in the above simulated experiments (4 nm/pixel), it is valid to ignore the deviations and consider the local error model of BTR is indeed in quantitative agreement with the simulation results. Finally, two simulated ideal structures are proposed here, together with their corresponding real samples. The simulation results show they are suitable for BTR.
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spelling pubmed-42990572015-01-26 Investigation on Blind Tip Reconstruction Errors Caused by Sample Features Wan, Jiahuan Xu, Linyan Wu, Sen Hu, Xiaodong Sensors (Basel) Article Precision measurements of a nanoscale sample surface using an atomic force microscope (AFM) require a precise quantitative knowledge of the 3D tip shape. Blind tip reconstruction (BTR), established by Villarrubia, gives an outer bound with larger errors if the tip characterizer is not appropriate. In order to explore the errors of BTR, a series of simulation experiments based on a conical model were carried out. The results show that, to reconstruct the tip precisely, the cone angle of the tip characterizer must be smaller than that of the tip. Furthermore, the errors decrease as a function of the tip cone angle and increase linearly with the sample radius of curvature, irrespective of the tip radius of curvature. In particular, for sharp (20 nm radius) and blunt (80 nm radius) tips, the radius of curvature of the tip characterizer must be smaller than 5 nm. Based on these simulation results, a local error model of BTR was established. The maximum deviation between the errors derived from the model and the simulated experiments is 1.22 nm. Compared with the lateral resolution used in the above simulated experiments (4 nm/pixel), it is valid to ignore the deviations and consider the local error model of BTR is indeed in quantitative agreement with the simulation results. Finally, two simulated ideal structures are proposed here, together with their corresponding real samples. The simulation results show they are suitable for BTR. MDPI 2014-12-05 /pmc/articles/PMC4299057/ /pubmed/25490584 http://dx.doi.org/10.3390/s141223159 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Wan, Jiahuan
Xu, Linyan
Wu, Sen
Hu, Xiaodong
Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title_full Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title_fullStr Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title_full_unstemmed Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title_short Investigation on Blind Tip Reconstruction Errors Caused by Sample Features
title_sort investigation on blind tip reconstruction errors caused by sample features
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299057/
https://www.ncbi.nlm.nih.gov/pubmed/25490584
http://dx.doi.org/10.3390/s141223159
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