Scanning Probe Microscopy Characterization of Optical Thin Films

Klapetek, Petr

doi:10.1007/978-3-319-75325-6_11

Cited by 1 publication

(2 citation statements)

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“…Atomic force microscopy (AFM) represents the most employed non-optical technique in the characterization of randomly rough surfaces (see e.g. [17,72]). Methods of AFM enable us to perform an efficient characterization of these surfaces similarly as the optical methods.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of randomly rough surfaces using angle-resolved scattering of light and atomic force microscopy

Šustek¹,

Vohánka²,

Ohlı́dal³

et al. 2021

J. Opt.

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The roughness of four samples of silicon single-crystal surfaces roughened by anodic oxidation is studied using atomic force microscopy (AFM) and angle-resolved scattering of light. The power spectral density functions (PSDFs) are determined on the basis of the measured values of the intensity of the scattered light. This is done on the basis of three models, which establish relation between the intensity of the light scattered in the given direction and the values of the PSDF at a certain spatial frequency. Two of the models are based on the scalar diffraction theory (SDT), while the third is based on the Rayleigh–Rice perturbation theory. The formulae corresponding to the SDT are derived in the theoretical part of the paper. The condition for the Fraunhofer diffraction is not satisfied if the values of the wavelength, distance to the detector and the dimensions of the illuminated spot on the sample used in the experiment are considered. However, it is shown that if the calculation of the intensity of the scattered light is performed in a certain way, then the validity of the expansion only up to the linear terms in the phase terms, i.e. in the same way as in the Fraunhofer diffraction, is not limited by the dimensions of the light spot but by the autocorrelation length of the randomly rough surface. The results obtained by the optical methods are compared with those obtained by AFM. It is shown that there is a good agreement between these results.

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Section: Introductionmentioning

confidence: 99%

“…That is why the AFM methods represent appropriate tools for checking results obtained by the optical methods in characterizing randomly rough surfaces (see e.g. [72,73]).…”

Section: Introductionmentioning

confidence: 99%