Materials Map

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

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Küpper, Moritz E.

  • Google
  • 1
  • 3
  • 8

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2022Evolution of Surface Topography and Microstructure in Laser Polishing of Cold Work Steel 1.2379 (AISI D2) Using Quadratic, Top-Hat Shaped Intensity Distributions8citations

Places of action

Chart of shared publication
Rittinghaus, Silja-Katharina
1 / 22 shared
Ross, Ingo
1 / 6 shared
Cortina, Magdalena
1 / 6 shared
Chart of publication period
2022

Co-Authors (by relevance)

  • Rittinghaus, Silja-Katharina
  • Ross, Ingo
  • Cortina, Magdalena
OrganizationsLocationPeople

article

Evolution of Surface Topography and Microstructure in Laser Polishing of Cold Work Steel 1.2379 (AISI D2) Using Quadratic, Top-Hat Shaped Intensity Distributions

  • Rittinghaus, Silja-Katharina
  • Küpper, Moritz E.
  • Ross, Ingo
  • Cortina, Magdalena
Abstract

<jats:p>Within the scope of this study, basic experimental research was carried out on macro-laser polishing of tool steel 1.2379 (D2) using a square intensity distribution and continuous wave laser radiation. The influence of the individual process parameters on surface topography was analyzed by a systematic investigation of a wide range of process parameters for two different, square laser beam diameters. Contrary to a typical laser polishing approach, it was shown that short interaction times (high scanning velocity and small laser beam dimensions) are required to reduce both micro-roughness and meso-roughness. A significant reduction of surface roughness of approx. 46% was achieved from Raini = 0.33 ± 0.026 µm to Ramin = 0.163 ± 0.018 µm using a focused square laser beam with an edge length of dL,E = 100 µm at a scanning velocity of vscan = 200 mm/s, a laser power PL = 60 W and n = 2 passes. However, characteristic surface features occur during laser polishing and are a direct consequence of the laser polishing process. Martensite needles in the micro-roughness region, undercuts in the meso-roughness region, and surface waviness in the macro-roughness region can dominate different regions of the resulting surface roughness spectrum. In terms of mechanical properties, average surface hardness was determined by hundreds of nano-indentation measurements and was approx. 390 ± 21 HV0.1 and particularly homogeneous over the whole laser polished surface.</jats:p>

Topics
  • microstructure
  • surface
  • hardness
  • polishing
  • cold-work steel