1. Microstructure and surface topography study of nanolayered TiAlN/CrN hard coatingPeter Panjan, Peter Gselman, Matjaž Panjan, Tonica Bončina, Aljaž Drnovšek, Mihaela Albu, Miha Čekada, Franc Zupanič, 2022, original scientific article Abstract: 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.
Keywords: magnetron sputtering, nanolayer hard coatings, growth defects, surface topography, interlayer roughness, non-metallic inclusion, focused ion beam (FIB), scanning electron microscopy (SEM), scanning transmission electron microscopy (STEM)
Published in DKUM: 19.03.2025; Views: 0; Downloads: 3
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2. Prediction of the hardness of hardened specimens with a neural networkMatej Babič, Peter Kokol, Igor Belič, Peter Panjan, Miha Kovačič, Jože Balič, Timotej Verbovšek, 2014, original scientific article Abstract: In this article we describe the methods of intelligent systems to predict the hardness of hardened specimens. We use the mathematical method of fractal geometry in laser techniques. To optimize the structure and properties of tool steel, it is necessary to take into account the effect of the self-organization of a dissipative structure with fractal properties at a load. Fractal material science researches the relation between the parameters of fractal structures and the dissipative properties of tool steel. This paper describes an application of the fractal dimension in the robot laser hardening of specimens. By using fractal dimensions, the changes in the structure can be determined because the fractal dimension is an indicator of the complexity of the sample forms. The tool steel was hardened with different speeds and at different temperatures. The effect of the parameters of robot cells on the material was better understood by researching the fractal dimensions of the microstructures of hardened specimens. With an intelligent system the productivity of the process of laser hardening was increased because the time of the process was decreased and the topographical property of the material was increased.
Keywords: fractal dimension, fractal geometry, neural network, prediction, hardness, steel, tool steel, laser
Published in DKUM: 17.03.2017; Views: 2032; Downloads: 120
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3. Morphology and corrosion properties PVD Cr-N coatings deposited on aluminium alloysDarja Kek-Merl, Ingrid Milošev, Peter Panjan, Franc Zupanič, 2011, original scientific article Abstract: The attempt to find an alternative coating for corrosion protection of Al- alloys was made. PVD coatings are one of the possible alternatives for replacement of ecological unfriendly chromate coatings. Chromium-nitride (Cr-N) and Ni/Cr-N coatings were sputtered on aluminium substrates (AA7075 and cladded AA2024). Surface and sub-surface characterizations were performed by AFM and SEM. Special attention was given to defects incorporated into coatings, since they play important role in the corrosion protection of the coating/substrate systems. The cross-sections through the typical defects were performed by ion beam milling incorporated into the SEM. The Vickers hardness of the Cr-N with and without layer of Ni on both substrates was determined. After the coatings deposition, the values of Vickers hardness (10 mN load) increase for 10 to 100-fold compared to the substrates. The corrosion behaviour of Cr-N and Ni/Cr-N thin films was investigated in near neutral 0.1 M solution of NaCl using potentiodynamics electrochemical measurement. Cr-N and Ni/Cr-N coatings shift the corrosion potentials to more positive values. The best corrosion resistance among the tested coating/substrate systems were found for Ni/Cr-N on AA7075 substrate.
Keywords: Al-alloys, corrosion properties, CrN films, FIB, PVD coatings
Published in DKUM: 17.03.2017; Views: 1359; Downloads: 95
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4. A new method for estimating the Hurst exponent H for 3D objectsMatej Babič, Peter Kokol, Nikola Guid, Peter Panjan, 2014, original scientific article Abstract: Mathematics and computer science are very useful in many other sciences. We use a mathematical method, fractal geometry, in engineering, specifically in laser techniques. Characterization of the surface and the interfacial morphology of robot-laser-hardened material is crucial to understand its properties. The surface microstructure of robot-laser-hardened material is rough. We aimed to estimate its surface roughness using the Hurst parameter H, which is directly related to the fractal dimension. We researched how the parameters of the robot-laser cell impact on the surface roughness of the hardened specimen. The Hurst exponent is understood as the correlation between the random steps X1 and X2, which are followed by time for the time difference t. In our research we understood the Hurst exponent H to be the correlation between the random steps X1 and X2, which are followed by the space for the space difference d. We also have a space component. We made test patterns of a standard label on the point robot-laser-hardened materials of DIN standard GGG 60, GGG 60 L, GGG 70, GGG 70 L and 1.7225. We wanted to know how the temperature of point robot-laser hardening impacts on the surface roughness. We developed a new method to estimate the Hurst exponent H of a 3D-object. This method we use to calculate the fractal dimension of a 3D-object with the equation D = 3 - H.
Keywords: fractal structure, Hurst exponent, robot, hardening, laser
Published in DKUM: 14.03.2017; Views: 1685; Downloads: 161
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5. Characterization of defects in PVD TiAlN hard coatingsPeter Gselman, Tonica Bončina, Franc Zupanič, Peter Panjan, Darja Kek-Merl, Miha Čekada, 2012, original scientific article Abstract: PVD hard coatings are continuously gaining their importance in different fields of applications. In industrial use, they are often exposed to corrosive environments. Hard coatings possess inherently good corrosion resistance, but the substrate-hard coating systems may suffer from a severe corrosion attack due to the defects (craters, pin holes) in the coatings. On the sites, where defects extend through the coating, pitting corrosion can take place. These sites are drawbacks in the applications of hard coating. A PVD TiAlN hard coating was prepared on cold-work, tool-steel (AISI D2) substrates by sputtering using unbalanced magnetron sources. The growth defects incorporated into the coating were studied after the deposition and corrosion experiments. We used two methods: (1) scanning electron microscopy (SEM) for general overview of the coating topography and 2D-characterization of defects, and (2) scanning electron microscopy with a focused ion beam (SEM-FIB) for making serial cross-sections through the selected defects in order to provide images for a 3D-reconstruction of defects. In this work we tried to investigate the formation of a defect at a specific location and findout whether the selected defect causes pitting corrosion.
Keywords: trde prevleke, PVD prevleke, defekti, jamičasta korozija, mikrostruktura, PVD hard coating, defect, pitting corrosion, microstructure
Published in DKUM: 10.07.2015; Views: 1437; Downloads: 104
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