Measurement of Roughness of Two Interfaces of a Dielectric Film by Scattering Ellipsometry

Germer, Thomas A.

doi:10.1103/physrevlett.85.349

Cited by 31 publications

(20 citation statements)

References 30 publications

(33 reference statements)

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“…Variations in the thickness of surface oxides (e.g. the iron and/or chromium oxides in this study) may cause additional deviations [8]- [11], [17,20,40], if they should be present at elevated temperatures and atmospheric conditions of interest. Furthermore, the sample and the reference are assumed to be similar in mass and composition.…”

Section: Consequences For Optical Heatingmentioning

confidence: 93%

“…Systematic investigation of reflection and scattering [32] have been performed for sinusoidal-shaped surface morphologies [24], other well-defined geometries [11,15,16,17,23,33] and sub-surface defects [21,34]. Simplified models exist also for special cases, where the optical wavelength is much smaller (or much larger) than the in-plane periodicity of a surface pattern [35].…”

Section: Reflection and Scattering Measurementsmentioning

confidence: 99%

“…Recent years have seen a tremendous progress in the understanding of the optical properties of surfaces with nanoscopic up to microscopic roughness [15]- [17], surfaces decorated with or embedding small particles [12], [18]- [22], or regular, non-planar surfaces, including defects [11,23,24]. Nevertheless, a full, rigorous description of the scattering from an arbitrary metallic surface is still rather challenging.…”

Section: Introductionmentioning

confidence: 99%

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Effect of surface roughness on optical heating of metals

Auinger

Ebbinghaus

Blümich

et al. 2014

J. Eur. Opt. Soc.-Rapid Publ.

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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.

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Section: Consequences For Optical Heatingmentioning

confidence: 93%

Section: Reflection and Scattering Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of surface roughness on optical heating of metals

Auinger

Ebbinghaus

Blümich

et al. 2014

J. Eur. Opt. Soc.-Rapid Publ.

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“…Polarized light scattering has been shown to enable the distinction amongst numerous scattering mechanisms in a number of other systems. [5][6][7][8][9][10][11] In many cases, the scattering function is a product of two factors, one of which is dependent upon the source of the scattering, which also determines its polarization properties, and another, which depends upon the statistical description of the ensemble of scatterers and which primarily affects only the intensity distribution. This separation of the scattering function into two functions is analogous to the use of form factors and structure factors, respectively, in x-ray scattering.…”

Section: Introductionmentioning

confidence: 99%

Modeling the appearance of special effect pigment coatings

Germer¹,

Nadal

2001

SPIE Proceedings

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Metallic and pearlescent coatings are becoming increasingly important in automotive, currency, and cosmetic applications. These coatings consist of metallic or dielectric platelets suspended in a binder, and are often applied between a pigmented basecoat, and a transparent topcoat. The scattering properties of these composite coatings vary depending upon the incident and viewing directions, as well as the wavelength. The complex nature of the scattering arises from the competition between multiple scattering sources: front surface reflection from the topcoat, reflection from the platelets, diffuse scattering from the pigmented undercoat, and scattering between platelets. The complex interplay between multiple scattering sources affects the ability to achieve quality control during the preparation of these coatings. In addition, the topcoat surface morphology, the properties of the pigmented basecoat, and the intrinsic properties, concentration, and angular distribution of the platelets influence the final appearance of the coating. In this paper, we will present models for light scattering from front surface facet reflection, subsurface flake reflection, and diffuse subsurface scattering. Experimental scattering measurements on pearlescent coatings show that the polarization can be well described in different geometry regimes by these different scattering sources. The models can be used to extract the slope distribution function of the flakes from the intensity data, but some aspects of the results behave inconsistently. Comparison is also made between experimental and calculated diffuse reflectance spectra. These results are intended to enable improved characterization of special effect coatings necessary for quality control and appearance modeling applications.

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“…In each of these examples a small change in the distribution of heights, widths, or curvatures of the peaks has an important effect on the rough surface's behavior (Kim et al, 2006). Light scattering from optical coatings is the best example for how strongly processes could be affected by the roughness of interfaces (Germer, 2000). However, in spite of the great influence of surface roughness on system behavior its measurement is still a notable problem of Metrology (Villarubia, 2005;Van Gorp et al, 2007).…”

Section: Complexity Criticality and Roughnessmentioning

confidence: 99%

Fractal Metrology for biogeosystems analysis

Argüelles¹,

Oleschko

Tarquis

et al. 2010

Biogeosciences

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Abstract. The solid-pore distribution pattern plays an important role in soil functioning being related with the main physical, chemical and biological multiscale and multitemporal processes of this complex system. In the present research, we studied the aggregation process as self-organizing and operating near a critical point. The structural pattern is extracted from the digital images of three soils (Chernozem, Solonetz and "Chocolate" Clay) and compared in terms of roughness of the gray-intensity distribution quantified by several measurement techniques. Special attention was paid to the uncertainty of each of them measured in terms of standard deviation. Some of the applied methods are known as classical in the fractal context (box-counting, rescaling-range and wavelets analyses, etc.) while the others have been recently developed by our Group. The combination of these techniques, coming from Fractal Geometry, Metrology, Informatics, Probability Theory and Statistics is termed in this paper Fractal Metrology (FM). We show the usefulness of FM for complex systems analysis through a case study of the soil's physical and chemical degradation applying the selected toolbox to describe and compare the structural attributes of three porous media with contrasting structure but similar clay mineralogy dominated by montmorillonites.

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Measurement of Roughness of Two Interfaces of a Dielectric Film by Scattering Ellipsometry

Cited by 31 publications

References 30 publications

Effect of surface roughness on optical heating of metals

Effect of surface roughness on optical heating of metals

Modeling the appearance of special effect pigment coatings

Fractal Metrology for biogeosystems analysis

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