Details

Autor(en) / Beteiligte

• Cupak, C.
• Szabo, P.S.
• Biber, H.
• Stadlmayr, R.
• Grave, C.
• Fellinger, M.
• Brötzner, J.
• Wilhelm, R.A.
• Möller, W.
• Mutzke, A.
• Moro, M.V.
• Aumayr, F.

Titel

Sputter yields of rough surfaces: Importance of the mean surface inclination angle from nano- to microscopic rough regimes

Ist Teil von

• Applied surface science, 2021-12, Vol.570, p.151204, Article 151204

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2021

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The roughness of a surface is known to have a strong influence on the sputtering process. Commonly used 1D Monte Carlo codes for calculating sputter yields show good agreement with experimental data only for comparably flat surfaces, whereas local ion incidence angles, shadowing and redeposition influence the sputter yields in both magnitude and angular dependence on rough surfaces. In the present work, we therefore investigated tungsten samples of largely different roughness, characterised by atomic force and confocal microscopy. A highly sensitive quartz crystal microbalance was used to determine sputter yields during ion irradiation. Low ion fluences were applied to ensure that the surface morphology did not change during irradiation. The results were used to benchmark our new ray-tracing simulation code SPRAY, which can take microscopy images without limitations in size as input. SPRAY was furthermore applied to perform systematic simulations for artificially roughened and computer-generated surfaces. A clear result was that the governing parameter for description of the sputtering behaviour is the mean value of the surface inclination angle distribution, rather than the commonly used root mean square roughness. Our simulations show that this parameter is universally applicable for a wide range of different surface structures. [Display omitted] •A decisive roughness parameter for prediction of effective sputter yields was identified.•The code SPRAY was developed for fast sputter simulations with rough surface input.•Microscopy image resolution and size are important for roughness characterisation.