Tip dilation artefacts & roughness measurement – parametric approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F19%3A00113382" target="_blank" >RIV/00216224:14740/19:00113382 - isvavai.cz</a>

Výsledek na webu

<a href="http://nanometrologie.cz/sbornik_2019.pdf" target="_blank" >http://nanometrologie.cz/sbornik_2019.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Tip dilation artefacts & roughness measurement – parametric approach

Popis výsledku v původním jazyce

Morphological dilation of surface with AFM tip (tip convolution) is a more or less unavoidable effect which distorts the measured topography. Hence many reconstruction methods based on Legendre transformation or Villarrubia’s morphological algorithms were proposed and studied as well as various other corrections for specific measured geometrical shapes. In characterisation of randomly rough surfaces we are usually only interested in statistical quantities, such as mean square roughness or autocorrelation length. Therefore, a different approach can be taken. Instead of attempting to reconstruct the surface, we find the map (true roughness parameters; tip parameters) - (measured parameters) for a specific class of rough surfaces. This allows a simple and fast estimation of tip convolution influence and, to a certain degree, also correction. We explore this avenue for Gaussian surfaces, show how composite parameters allow reducing the dimensionality of the problem and elucidate some interesting related phenomena, such as the increase of measured roughness with tip wear

Název v anglickém jazyce

Tip dilation artefacts & roughness measurement – parametric approach

Popis výsledku anglicky

Morphological dilation of surface with AFM tip (tip convolution) is a more or less unavoidable effect which distorts the measured topography. Hence many reconstruction methods based on Legendre transformation or Villarrubia’s morphological algorithms were proposed and studied as well as various other corrections for specific measured geometrical shapes. In characterisation of randomly rough surfaces we are usually only interested in statistical quantities, such as mean square roughness or autocorrelation length. Therefore, a different approach can be taken. Instead of attempting to reconstruct the surface, we find the map (true roughness parameters; tip parameters) - (measured parameters) for a specific class of rough surfaces. This allows a simple and fast estimation of tip convolution influence and, to a certain degree, also correction. We explore this avenue for Gaussian surfaces, show how composite parameters allow reducing the dimensionality of the problem and elucidate some interesting related phenomena, such as the increase of measured roughness with tip wear

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10305 - Fluids and plasma physics (including surface physics)

Projekt

<a href="/cs/project/LQ1601" target="_blank" >LQ1601: CEITEC 2020</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů