Self-consistent autocorrelation for finite-area bias correction in roughness measurement

Simple item page
dc.contributor.authorNečas, Davidcs
dc.coverage.issue2cs
dc.coverage.volume6cs
dc.date.accessioned2025-02-03T14:50:57Z
dc.date.available2025-02-03T14:50:57Z
dc.date.issued2024-06-01cs
dc.description.abstractScan line levelling, a ubiquitous and often necessary step in AFM data processing, can cause a severe bias on measured roughness parameters such as mean square roughness or correlation length. Although bias estimates have been formulated, they aimed mainly at assessing the severity of the problem for individual measurements. Practical bias correction methods are still missing. This work exploits the observation that the bias of autocorrelation function (ACF) can be expressed in terms of the function itself, permitting a self-consistent formulation. From this two correction approaches are developed, both with the aim to obtain convenient formulae which can be easily applied in practice. The first modifies standard analytical models of ACF to incorporate, in expectation, the bias and thus actually match the data the models are used to fit. The second inverts the relation between true and estimated ACF to realise a model-free correction. Both are tested using simulated and experimental data and found effective, reducing the total error of roughness parameters several times in the typical cases.en
dc.formattextcs
dc.format.extent14cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationEngineering Research Express. 2024, vol. 6, issue 2, 14 p.en
dc.identifier.doi10.1088/2631-8695/ad5302cs
dc.identifier.issn2631-8695cs
dc.identifier.orcid0000-0001-7731-8453cs
dc.identifier.other189989cs
dc.identifier.researcheridD-7166-2012cs
dc.identifier.urihttps://hdl.handle.net/11012/250000
dc.language.isoencs
dc.publisherIOP Publishing Ltdcs
dc.relation.ispartofEngineering Research Expresscs
dc.relation.urihttps://iopscience.iop.org/article/10.1088/2631-8695/ad5302cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2631-8695/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectscanning probe microscopyen
dc.subjectroughnessen
dc.subjectautocorrelationen
dc.subjectbiasen
dc.titleSelf-consistent autocorrelation for finite-area bias correction in roughness measurementen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-189989en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:50:57en
sync.item.modts2025.01.30 10:32:04en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Plazmové technologie pro materiálycs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Necas_2024_Eng._Res._Express_6_025560.pdf
Size:
942.12 KB
Format:
Adobe Portable Document Format
Description:
file Necas_2024_Eng._Res._Express_6_025560.pdf
Download
Collections
Plazmové technologie pro materiály