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

Deshmane, Nachiket S.

  • Google
  • 1
  • 2
  • 0

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023Modelling of yield point phenomenon in bake-hardening grade steelcitations

Places of action

Chart of shared publication
Perdahcioglu, Semih E.
1 / 1 shared
Van Den Boogaard, Ton
1 / 135 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Perdahcioglu, Semih E.
  • Van Den Boogaard, Ton
OrganizationsLocationPeople

document

Modelling of yield point phenomenon in bake-hardening grade steel

  • Perdahcioglu, Semih E.
  • Deshmane, Nachiket S.
  • Van Den Boogaard, Ton
Abstract

<p>In this study the yield point phenomenon in Bake-Hardening grade steel is predicted using a physically based thermo-mechanical model. A modified Taylor equation is proposed with a physically based dislocation density evolution approach. The softening that follows the higher yield point is incorporated with a Voce type decaying exponential function. The strain rate dependency of the plastic hardening is also incorporated in the model. The yield point in the decay function is also strain rate dependent but does not follow the same dependency of plastic hardening. This was solved by making the decay function strain rate dependent by adding a modified strain rate stress term to the exponential function. This parameter is calculated based on tensile experiments. Due to the softening behavior of the material, the numerical model is mesh size sensitive. Hence, a lower order strain gradient enhanced approach is implemented. The gradient is in a form of an additional hardening term assigned in the locally strained bands based on the plastic strain gradient. Hill48 yield criterion is used to assimilate the anisotropy in the steel grade. The numerical results show good correspondence with experimental tensile tests. The regularization significantly reduced the mesh size dependency of the numerical results.</p>

Topics
  • density
  • impedance spectroscopy
  • polymer
  • experiment
  • steel
  • dislocation