Issue |
J. Eur. Opt. Soc.-Rapid Publ.
Volume 9, 2014
|
|
---|---|---|
Article Number | 14004 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.2971/jeos.2014.14004 | |
Published online | 25 January 2014 |
Regular papers
Effect of surface roughness on optical heating of metals
1
Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Straße 1, 40237 Düsseldorf, Germany
2
Christian Doppler Laboratory for Diffusion and Segregation Phenomena during the Production of High Strength Steel Sheets
3
SENTECH Instruments GmbH, Schwarzschildstraße 2, 12489 Berlin, Germany
* michael.auinger.at@ieee.org
** a.erbe@mpie.de
Received:
7
October
2013
Revised:
18
November
2013
Heating by absorption of light is a commonly used technique to ensure a fast temperature increase of metallic samples. The rate of heating when using optical heating depends critically on the absorption of light by a sample. Here, the reflection and scattering of light from UV to IR by surfaces with different roughness of iron-based alloy samples (Fe, 1 wt-% Cr) is investigated. A combination of ellipsometric and optical scattering measurements is used to derive a simplified parametrisation which can be used to obtain the absorption of light from random rough metal surfaces, as prepared through conventional grinding and polishing techniques. By modelling the ellipsometric data of the flattest sample, the pseudodielectric function of the base material is derived. Describing an increased roughness by a Maxwell-Garnett model does not yield a reflectivity which follows the experimentally observed sum of scattered and reflected intensities. Therefore, a simple approach is introduced, based on multiple reflections, where the number of reflections depends on the surface roughness. This approach describes the data well, and is subsequently used to estimate the fraction of absorbed energy. Using numerical modelling, the effect on the heating rate is investigated. A numerical example is analysed, which shows that slight changes in roughness may result in big differences of the energy input into a metallic sample, with consequences on the achieved temperatures. Though the model oversimplifies reality, it provides a physically intuitive approach to estimate trends.
Key words: Metals / infrared / scattering at rough surfaces / ellipsometry and polarimetry / mathematical methods (general) / thermal emission
© The Author(s) 2014. All rights reserved.
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