Influence of surface and interface roughness on X-ray and extreme ultraviolet reflectance: A comparative numerical study

Esashi, Yuka; Tanksalvala, Michael; Zhang, Zhe; Jenkins, Nicholas W.; Kapteyn, Henry C.; Murnane, Margaret M.

doi:10.1364/osac.422924

Cited by 13 publications

(3 citation statements)

References 59 publications

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“…It plays a key role in energy dissipation and stress relaxation. Therefore, the knowledge and control of the quality of interfaces in multilayer structures are important for many applications, especially in optics and microelectronics [24]. For example, interlayer roughness, non-parallel layer interfaces and non-uniformity of the optical constants can significantly affect the optical reflectivity and transmittance of a multilayer coating [25].…”

Section: Interlayer Roughnessmentioning

confidence: 99%

Microstructure and Surface Topography Study of Nanolayered TiAlN/CrN Hard Coating

et al. 2022

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The microstructure and surface topography of PVD hard coatings are among the most important properties, as they significantly determine their mechanical, tribological and other properties. In this study, we systematically analyzed the microstructure and topography of a TiAlN/CrN nanolayer coating (NL-TiAlN/CrN), not only because such coatings possess better mechanical and tribological properties than TiAlN and CrN monolayer coatings, mainly because the contours of the individual layers, in the cross-sectional STEM or SEM images of such coatings, make it easier to follow topographic and microstructural changes that occurred during its growth. We investigated the effects of the substrate rotation modes on the microstructure and surface topography of the NL-TiAlN/CrN coating, as well as on the periodicity of the nanolayer structure. The influence of the substrate material and the ion etching methods were also studied, while special attention was given to the interlayer roughness and influence of non-metallic inclusions in the steel substrates on the growth of the coating. The topographical features of the NL-TiAlN/CrN coating surface are correlated with the observations from the cross-sectional TEM and FIB analysis. Selected non-metallic inclusions, covered by the NL-TiAlN/CrN coating, were prepared for SEM and STEM analyses by the focused ion beam. The same inclusions were analyzed prior to and after deposition. We found that substrate rotation modes substantially influence the microstructure, surface topography and periodicity of the NL-TiAlN/CrN layer. Non-metallic inclusions in the substrates cause the formation of shallow craters or protrusions, depending on their net removal rates during the substrate pretreatment (polishing and ion etching), as compared to the matrix.

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Section: Interlayer Roughnessmentioning

confidence: 99%

Microstructure and Surface Topography Study of Nanolayered TiAlN/CrN Hard Coating

et al. 2022

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“…Oxidation and contamination layers are not sharply bounded and well-defined but rather intermixed and nonstoichiometric [36]. With the argument elaborated in our earlier work considering the optical constants of Ru [36], oxidation and contamination are modeled as two discrete layers since modeling nonuniform profiles (gradients) is computationally laborious and time-consuming [75]. Optimally, a more realistic approach with a gradient profile is intuitively favored.…”

Section: Inverse Problem Adjustment and Data Analysismentioning

confidence: 99%

Nested Sampling aided determination of tantalum optical constants in the EUV spectral range

Saadeh¹,

Naujok²,

Wu³

et al. 2022

Appl. Opt.

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We report on determining the optical constants of Ta in the sub-extreme ultraviolet (EUV) spectral range 5.0–24.0 nm from the angle-dependent reflectance (ADR) measured using monochromatized synchrotron radiation. Two sputtered samples with differing thicknesses were investigated. Complementarily x-ray reflectance was measured at shorter wavelengths and evaluated by Fourier transform to facilitate an unambiguous selection of a model for the data evaluation based on an inverse solution of the Fresnel’s equations for a layered system. Bayesian inferences coupled with a Nested Sampling (NS) algorithm were utilized to derive the optical constants with their corresponding uncertainties. This report further emphasizes the applicability of an acclaimed NS algorithm on a high-dimensional inverse problem. We explore the possibility of addressing the correlations between the optical constants of thin films and their structural parameters based on other established studies.

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“…[1][2][3][4] Neuhold et al proved that x-ray reflectivity is an excellent tool to investigate buried interfaces in organic electronic devices 5 although the interpretation of XRR measurements depends on a large number of parameters such as thickness and roughness and is therefore difficult. 1 Theoretical considerations discuss the influence of roughness in layer stacks 6,7 and demonstrate the impact of the roughness with decreasing thickness of the layers.…”

Section: Introductionmentioning

confidence: 99%

Determination of layer morphology of rough layers in organic light emitting diodes by X‐ray reflectivity

Sachs

Fuhrmann

Deferme

et al. 2022

Engineering Reports

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X-ray reflectivity (XRR) has been proven to be a useful tool to investigate thin layers as well as buried interfaces in stacks built of very thin layers. Nevertheless, x-ray reflectivity measurements are limited by the roughness of the layers and interfaces as the roughness destroys the interference structure, the so-called Kiessig fringes. As investigations of thin layers in organic light emitting devices (OLEDs) are still subject of research and development, the focus of this paper is the investigation of a layer of indium tin oxide (ITO) which serves as transparent anode material in OLEDs. Due to the fabrication process, ITO shows rough surface structures, so-called spikes, hindering the determination of the ITO layer thickness and roughness in XRR measurements. In this paper, it is theoretically and experimentally proven that a smoothing layer on the ITO enables the determination of the buried ITO layer thickness and roughness as well as the density of the spikes. Furthermore, a sputtered aluminum layer (e.g. cathode material) showing spikes in atomic force microscopy covered with a smoothing layer reveals Kiessig fringes allowing the determination of the density of buried spikes. In general, it is shown that a smoothing layer on a rough surface enhances the sensitivity of x-ray reflectivity measurements.

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Influence of surface and interface roughness on X-ray and extreme ultraviolet reflectance: A comparative numerical study

Cited by 13 publications

References 59 publications

Microstructure and Surface Topography Study of Nanolayered TiAlN/CrN Hard Coating

Microstructure and Surface Topography Study of Nanolayered TiAlN/CrN Hard Coating

Nested Sampling aided determination of tantalum optical constants in the EUV spectral range

Determination of layer morphology of rough layers in organic light emitting diodes by X‐ray reflectivity

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