Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Naji, M.
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Pedersen, Henrik Chresten

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2022A Tunable Hyperspectral Imager for Detection and Quantification of Marine Biofouling on Coated Surfaces8citations
  • 2016Replication of optical microlens arrays using photoresist coated molds16citations
  • 2016Replication of nanopits and nanopillars by roll-to-roll extrusion coating using a structured cooling roll7citations
  • 2010Optical detections from worn and unworn titanium compound surfaces3citations
  • 2010Wear monitoring of protective nitride coatings using image processing8citations
  • 2009Dynamic study of a sliding interface wear process of TiAlN and CrN multi-layers by X-ray absorptioncitations
  • 2009Image processing of worn and unworn protective coatings of TiAlN and TiN on 100Cr6 steelcitations

Places of action

Chart of shared publication
Erik Weinell, Claus
1 / 33 shared
Pedersen, Christian
1 / 4 shared
Dam-Johansen, Kim
1 / 56 shared
Pedersen, Morten Lysdahlgaard
1 / 2 shared
Petersen, Paul Michael
1 / 8 shared
Santos, Joaquim
1 / 1 shared
Ulusoy, Burak
1 / 4 shared
Chakrabarti, Maumita
1 / 1 shared
Dam-Hansen, Carsten
1 / 3 shared
Stubager, Jørgen
1 / 2 shared
Pedersen, T. F.
1 / 1 shared
Murthy, Swathi
1 / 6 shared
Pranov, Henrik
1 / 7 shared
Taboryski, Rafael Jozef
1 / 34 shared
Rasmussen, Inge Lise
4 / 6 shared
Mikkelsen, N. J.
4 / 4 shared
Belin, M.
4 / 6 shared
Martin, J.-M.
2 / 2 shared
Guibert, M.
4 / 4 shared
Schou, Jørgen
3 / 83 shared
Feidenhansl, R.
1 / 6 shared
Martin, J. M.
1 / 9 shared
Chart of publication period
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2016
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Co-Authors (by relevance)

  • Erik Weinell, Claus
  • Pedersen, Christian
  • Dam-Johansen, Kim
  • Pedersen, Morten Lysdahlgaard
  • Petersen, Paul Michael
  • Santos, Joaquim
  • Ulusoy, Burak
  • Chakrabarti, Maumita
  • Dam-Hansen, Carsten
  • Stubager, Jørgen
  • Pedersen, T. F.
  • Murthy, Swathi
  • Pranov, Henrik
  • Taboryski, Rafael Jozef
  • Rasmussen, Inge Lise
  • Mikkelsen, N. J.
  • Belin, M.
  • Martin, J.-M.
  • Guibert, M.
  • Schou, Jørgen
  • Feidenhansl, R.
  • Martin, J. M.
OrganizationsLocationPeople

conferencepaper

Image processing of worn and unworn protective coatings of TiAlN and TiN on 100Cr6 steel

  • Pedersen, Henrik Chresten
  • Rasmussen, Inge Lise
  • Mikkelsen, N. J.
  • Belin, M.
  • Martin, J. M.
  • Guibert, M.
  • Schou, Jørgen
Abstract

A model system, consisting of a titanium aluminum nitride (TiAlN) coating on top of an ‘optical’ titanium nitride (TiN) signal layer deposited on 100Cr6 steel substrates, was exposed to an extremely abrasive wear process. The TiAlN top-coatings, of thicknesses of up to 3 µm, were removed by a reciprocating wear process in a linear tribo-meter with up to 105 repetitive cycles, leaving the embedded TiN signal layers uncovered at the bottom the wear scars. The worn surfaces were characterized by subsequent image processing. A color detection, by a simple optical imaging system, of the wear scar with the exposed TiN layer showed a significant increase of ~40% of the relative color values from the TiAlN top layers to the embedded TiN signal layers. A similar reflectance detection experiment with a red laser optical system showed a comparatively significant signal increase of ~30% from the TiAlN top-coating to the TiN signal layer. The two different methods, image processing and laser reflectance measurements, lead thus to identical results, showing that image processing by means of color detection or monitoring and laser reflectance are potential techniques for intelligent determination of residual thickness of realistic tribological coatings of tools prior to complete wear.

Topics
  • surface
  • experiment
  • aluminium
  • nitride
  • steel
  • titanium
  • tin