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

Barroy, Pierre

  • Google
  • 3
  • 11
  • 8

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2021Sliding Friction Behavior of Sintered Ni-Cr Composites with Solid Lubricants1citations
  • 2021Laser-Assisted High Speed Machining of 316 Stainless Steel: The Effect of Water-Soluble Sago Starch Based Cutting Fluid on Surface Roughness and Tool Wear6citations
  • 2020Microstructure and surface characterization of Ni-Cr based composites containing variable solid lubricants1citations

Places of action

Chart of shared publication
Ahmad, Faiz
2 / 9 shared
Puille, Clement
2 / 2 shared
Lahmar, Abdelilah
2 / 27 shared
Durand-Drouhin, Olivier
2 / 3 shared
Khan, Amir Azam
3 / 5 shared
Mohamad, Wan Farhana
2 / 2 shared
Tamrin, Khairul Fikri
1 / 1 shared
Sheikh, Nadeem Ahmed
1 / 1 shared
Yassin, Abdullah
1 / 1 shared
Yasmin, Farhana
1 / 1 shared
Mohamaddan, Shahrol
1 / 2 shared
Chart of publication period
2021
2020

Co-Authors (by relevance)

  • Ahmad, Faiz
  • Puille, Clement
  • Lahmar, Abdelilah
  • Durand-Drouhin, Olivier
  • Khan, Amir Azam
  • Mohamad, Wan Farhana
  • Tamrin, Khairul Fikri
  • Sheikh, Nadeem Ahmed
  • Yassin, Abdullah
  • Yasmin, Farhana
  • Mohamaddan, Shahrol
OrganizationsLocationPeople

article

Laser-Assisted High Speed Machining of 316 Stainless Steel: The Effect of Water-Soluble Sago Starch Based Cutting Fluid on Surface Roughness and Tool Wear

  • Tamrin, Khairul Fikri
  • Sheikh, Nadeem Ahmed
  • Yassin, Abdullah
  • Barroy, Pierre
  • Yasmin, Farhana
  • Khan, Amir Azam
  • Mohamaddan, Shahrol
Abstract

Laser-assisted high speed milling is a subtractive machining method that employs a laser to thermally soften a difficult-to-cut material's surface in order to enhance machinability at a high material removal rate with improved surface finish and tool life. However, this machining with high speed leads to high friction between workpiece and tool, and can result in high temperatures, impairing the surface quality. Use of conventional cutting fluid may not effectively control the heat generation. Besides, vegetable-based cutting fluids are invariably a major source of food insecurity of edible oils which is traditionally used as a staple food in many countries. Thus, the primary objective of this study is to experimentally investigate the effects of water-soluble sago starch-based cutting fluid on surface roughness and tool's flank wear using response surface methodology (RSM) while machining of 316 stainless steel. In order to observe the comparison, the experiments with same machining parameters are conducted with conventional cutting fluid. The prepared water-soluble sago starch based cutting fluid showed excellent cooling and lubricating performance. Therefore, in comparison to the machining using conventional cutting fluid, a decrease of 48.23% in surface roughness and 38.41% in flank wear were noted using presented approach. Furthermore, using the extreme learning machine (ELM), the obtained data is modeled to predict surface roughness and flank wear and showed good agreement between observations and predictions.

Topics
  • impedance spectroscopy
  • surface
  • stainless steel
  • experiment
  • grinding
  • milling