Methods for topography artifacts compensation in scanning thermal microscopy

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dc.contributor.authorMartinek, Jancs
dc.contributor.authorKlapetek, Petrcs
dc.contributor.authorCharvátová Campbell, Annacs
dc.coverage.issue1cs
dc.coverage.volume155cs
dc.date.issued2015-08-01cs
dc.description.abstractThermal conductivity contrast images in scanning thermal microscopy (SThM) are often distorted by artifacts related to local sample topography. Three methods for numerically estimating and compensating for topographic artifacts are compared in this paper: a simple approach based on local sample geometry at the probe apex vicinity, a neural network analysis and 3D finite element modeling of the probe–sample interaction. A local topography and an estimated probe shape are used as source data for the calculation in all these techniques; the result is a map of false conductivity contrast signals generated only by sample topography. This map can be then used to remove the topography artifacts from measured data.en
dc.description.abstractThermal conductivity contrast images in scanning thermal microscopy (SThM) are often distorted by artifacts related to local sample topography. Three methods for numerically estimating and compensating for topographic artifacts are compared in this paper: a simple approach based on local sample geometry at the probe apex vicinity, a neural network analysis and 3D finite element modeling of the probe–sample interaction. A local topography and an estimated probe shape are used as source data for the calculation in all these techniques; the result is a map of false conductivity contrast signals generated only by sample topography. This map can be then used to remove the topography artifacts from measured data.en
dc.formattextcs
dc.format.extent55-61cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationULTRAMICROSCOPY. 2015, vol. 155, issue 1, p. 55-61.en
dc.identifier.doi10.1016/j.ultramic.2015.04.011cs
dc.identifier.issn0304-3991cs
dc.identifier.orcid0000-0002-7591-4101cs
dc.identifier.orcid0000-0001-5241-9178cs
dc.identifier.other114643cs
dc.identifier.researcheridD-6819-2012cs
dc.identifier.urihttp://hdl.handle.net/11012/201148
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofULTRAMICROSCOPYcs
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S0304399115000959cs
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/0304-3991/cs
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/cs
dc.subjectScanning thermal microscopyen
dc.subjectArtifactsen
dc.subjectNeural networksen
dc.subjectScanning thermal microscopy
dc.subjectArtifacts
dc.subjectNeural networks
dc.titleMethods for topography artifacts compensation in scanning thermal microscopyen
dc.title.alternativeMethods for topography artifacts compensation in scanning thermal microscopyen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-114643en
sync.item.dbtypeVAVen
sync.item.insts2025.10.14 14:15:23en
sync.item.modts2025.10.14 10:04:02en
thesis.grantorVysoké učení technické v Brně. Fakulta stavební. Ústav fyzikycs
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