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

Ion, William

  • Google
  • 14
  • 24
  • 37

University of Strathclyde

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (14/14 displayed)

  • 2021Optimisation of cutting parameters and surface deformation during thin steel sheets plasma processing using Taguchi approach7citations
  • 2017A novel methodology for in-process monitoring of flow forming2citations
  • 2017Automated microstructural analysis of titanium alloys using digital image processing7citations
  • 2017In-process monitoring and quality control of hot forging processes towards Industry 4.0citations
  • 2017Protective coatings for ceramic superplastic forming dies2citations
  • 2016Protective coatings for superplastic forming ceramic diescitations
  • 2016Investigating relationships between laser metal deposition deployment conditions and material microstructural evolutioncitations
  • 2016Remanufacturing H13 steel moulds and dies using laser metal depositioncitations
  • 2014Thermal sprayed protective coatings for superplastic forming ceramic dies : a monitoring system of die conditioncitations
  • 2014Protective coatings for superplastic forming diescitations
  • 2014Protective coatings for superplastic forming ceramic diescitations
  • 2014Protective coatings for superplastic forming ceramic dies : opportunities for thermal spray technologycitations
  • 2014Thermal sprayed protective coatings for superplastic forming ceramic diescitations
  • 2013Identifying the dominant failure mode in the hot extrusion tooling used to forge nickel based superalloy19citations

Places of action

Chart of shared publication
Gani, Adel
1 / 2 shared
Yang, Erfu
2 / 3 shared
Conway, Alastair
1 / 3 shared
Appleby, Andrew
1 / 1 shared
Yakushina, Evgenia
1 / 18 shared
Campbell, Andrew John
1 / 3 shared
Marshall, Stephen
1 / 12 shared
Murray, Paul
1 / 11 shared
Zante, Remi Christophe
2 / 4 shared
Yan, Xiu-Tian
1 / 1 shared
Onyeiwu, Chimaeze
1 / 1 shared
Rodden, Tony
1 / 1 shared
Staiano, Andrea
7 / 8 shared
Ohare, L.
1 / 2 shared
Zuelli, Nicola
2 / 11 shared
Ohare, Lynne
6 / 6 shared
Wilson, Michael
2 / 2 shared
Xirouchakis, Paul
2 / 6 shared
Payne, Grant
2 / 5 shared
Fitzpatrick, Stephen
2 / 14 shared
Ahmad, Abdul Ossman
2 / 3 shared
Anderson, Magnus
1 / 3 shared
Brooks, Jeffery
1 / 12 shared
Mcguire, Kenny
1 / 1 shared
Chart of publication period
2021
2017
2016
2014
2013

Co-Authors (by relevance)

  • Gani, Adel
  • Yang, Erfu
  • Conway, Alastair
  • Appleby, Andrew
  • Yakushina, Evgenia
  • Campbell, Andrew John
  • Marshall, Stephen
  • Murray, Paul
  • Zante, Remi Christophe
  • Yan, Xiu-Tian
  • Onyeiwu, Chimaeze
  • Rodden, Tony
  • Staiano, Andrea
  • Ohare, L.
  • Zuelli, Nicola
  • Ohare, Lynne
  • Wilson, Michael
  • Xirouchakis, Paul
  • Payne, Grant
  • Fitzpatrick, Stephen
  • Ahmad, Abdul Ossman
  • Anderson, Magnus
  • Brooks, Jeffery
  • Mcguire, Kenny
OrganizationsLocationPeople

article

Automated microstructural analysis of titanium alloys using digital image processing

  • Yakushina, Evgenia
  • Campbell, Andrew John
  • Marshall, Stephen
  • Murray, Paul
  • Ion, William
Abstract

<p>Titanium is a material that exhibits many desirable properties including a very high strength to weight ratio and corrosive resistance. However, the specific properties of any components depend upon the microstructure of the material, which varies by the manufacturing process. This means it is often necessary to analyse the microstructure when designing new processes or performing quality assurance on manufactured parts. For Ti6Al4V, grain size analysis is typically performed manually by expert material scientists as the complicated microstructure of the material means that, to the authors knowledge, no existing software reliably identifies the grain boundaries. This manual process is time consuming and offers low repeatability due to human error and subjectivity. In this paper, we propose a new, automated method to segment microstructural images of a Ti6Al4V alloy into its constituent grains and produce measurements. The results of applying this technique are evaluated by comparing the measurements obtained by different analysis methods. By using measurements from a complete manual segmentation as a benchmark we explore the reliability of the current manual estimations of grain size and contrast this with improvements offered by our approach.</p>

Topics
  • impedance spectroscopy
  • grain
  • grain size
  • strength
  • titanium
  • titanium alloy