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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Schiebahn, Alexander

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RWTH Aachen University

in Cooperation with on an Cooperation-Score of 37%

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Publications (5/5 displayed)

  • 2023Non-destructive evaluation of the friction stir welding process, generalizing a deep neural defect detection network to identify internal weld defects across different aluminum alloys18citations
  • 2023Optimization of the weldability and joint strength of Al Mg Si cladded aluminum alloys via RSW: a statistical and metallurgical approachcitations
  • 2022Strain Monitoring of a Structural Adhesive Bond by Embedding a Polymer Optical Fiber3citations
  • 2022Curing Adhesives with Woven Fabrics Made of Polymer Optical Fibre and PET Yarn3citations
  • 2021Individualized and controlled laser beam pretreatment process for adhesive bonding of fiber-reinforced plastics. II. Automatic laser process control by spectrometry2citations

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Rabe, Pascal
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Reisgen, U.
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Pedro, De Andrade Mato Grosso P. Bamberg
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Christ, Martin Leonhard
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Reisgen, Uwe
4 / 18 shared
Luber, Michael
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Engelbrecht, Rainer
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Rostan, Katharina
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Weiland, Josef
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Gries, Thomas
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Seewald, Robert
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Kallweit, Jan
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Pätzel, Mark
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Dittmar, Hagen
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Overmeyer, Ludger
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Kaierle, Stefan
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Wippo, Verena
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Jaeschke, Peter
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Co-Authors (by relevance)

  • Rabe, Pascal
  • Reisgen, U.
  • Pedro, De Andrade Mato Grosso P. Bamberg
  • Christ, Martin Leonhard
  • Reisgen, Uwe
  • Luber, Michael
  • Engelbrecht, Rainer
  • Rostan, Katharina
  • Weiland, Josef
  • Gries, Thomas
  • Seewald, Robert
  • Kallweit, Jan
  • Pätzel, Mark
  • Dittmar, Hagen
  • Overmeyer, Ludger
  • Kaierle, Stefan
  • Wippo, Verena
  • Jaeschke, Peter
OrganizationsLocationPeople

article

Individualized and controlled laser beam pretreatment process for adhesive bonding of fiber-reinforced plastics. II. Automatic laser process control by spectrometry

  • Dittmar, Hagen
  • Overmeyer, Ludger
  • Schiebahn, Alexander
  • Kaierle, Stefan
  • Wippo, Verena
  • Jaeschke, Peter
  • Weiland, Josef
  • Reisgen, Uwe
Abstract

<jats:p>This paper describes the research conducted on the automation for a UV laser-based surface pretreatment of fiber-reinforced composites in order to improve adhesive bonding conditions. In a preceding process step, a laser-line-triangulation system gathered inline information on a composite part’s surface like topology and location of surface contaminants. These data are the basis for an automation of the laser-based surface treatment [J. Weiland, B. Kunze, H. Dittmar, B. Marx, A. Schiebahn, P. Jaeschke, L. Overmeyer, and U. Reisgen, Proc. Inst. Mech. Eng. Part E: J. Process Mech. Eng. 234, 1–10 (2020)]. The gathered data describe the position of bonding areas and surface contaminants and are converted into relative coordinates of the laser’s scanning field. During the following laser process, the bonding area is ablated to improve adhesive bonding conditions. The process is monitored online by a broad bandwidth spectrometer covering the range of λ = 200–1100 nm to detect changes in the surface composition. If the spectrometer detects signals related to specific surface contaminants during the laser process, the position of the contamination is logged. In this case, only the areas that showed traces of surface contaminations are laser treated again until the spectrometer stops detecting the contaminant signature. This work presents results of two series of experiments. During the first series of experiments, the spectrometer monitored a UV laser process on a carbon fiber reinforced epoxy. The laser processing was performed on a clean and contaminated surface. An industry standard release agent contaminated the plastic surface. The spectrometer detected differences between the clean and contaminated surface that will be used for an automatic process control. In a second series of experiments, the authors performed a processing parameter analysis in order to identify a potential process window for laser-based surface pretreatment for glass-fiber reinforced polyamide 6. Contact angle analysis, surface roughness measurements, peel strength, and shear strength tests were performed. The results show that an inline controlled laser process is robustly able to pretreat composite surfaces based on spectrometric measurements.</jats:p>

Topics
  • impedance spectroscopy
  • surface
  • polymer
  • Carbon
  • experiment
  • glass
  • glass
  • strength
  • Surface roughness measurement
  • spectrometry
  • fiber-reinforced composite