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

Kumar, Nilesh

  • Google
  • 3
  • 12
  • 7

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2023Influence of the current source on microstructure and degradation of the copper-steel interface during resistance spot weldingcitations
  • 2022Bandgap engineering and modulation of thermodynamic, and optical properties of III-N monolayers XN (X=In, Ga ∧ Al) by mutual alloying1citations
  • 2022An advanced dislocation density-based approach to model the tensile flow behaviour of a 64.7Ni–31.96Cu alloy6citations

Places of action

Chart of shared publication
Bergheau, Jean-Michel
1 / 32 shared
Fabrègue, D.
1 / 10 shared
Hamdi, Hedi
1 / 2 shared
Chantrenne, Patrice
1 / 6 shared
Foroozmehr, Fayaz
1 / 1 shared
Pouvreau, Cedric
1 / 2 shared
Dupuy, Thomas
1 / 3 shared
Dancette, Sylvain
1 / 16 shared
Yadav, Surya D.
1 / 3 shared
Gupta, Pulkit
1 / 1 shared
Poletti, Maria Cecilia
1 / 79 shared
Joseph, Alen S.
1 / 1 shared
Chart of publication period
2023
2022

Co-Authors (by relevance)

  • Bergheau, Jean-Michel
  • Fabrègue, D.
  • Hamdi, Hedi
  • Chantrenne, Patrice
  • Foroozmehr, Fayaz
  • Pouvreau, Cedric
  • Dupuy, Thomas
  • Dancette, Sylvain
  • Yadav, Surya D.
  • Gupta, Pulkit
  • Poletti, Maria Cecilia
  • Joseph, Alen S.
OrganizationsLocationPeople

article

An advanced dislocation density-based approach to model the tensile flow behaviour of a 64.7Ni–31.96Cu alloy

  • Yadav, Surya D.
  • Gupta, Pulkit
  • Poletti, Maria Cecilia
  • Joseph, Alen S.
  • Kumar, Nilesh
Abstract

<p>Modelling the flow behaviour enables to understand the underlying deformation mechanisms underneath the various conditions imposed during the thermo-mechanical processing. Thus, herein flow stress response of 64.7Ni–31.96Cu alloy with different grain size is modelled at varying temperatures and strain rates, employing a dislocation density reliant physical model. The model takes account of immobile dislocations and assimilates strain hardening effect, Hall–Petch effect and the short-range interactions. Furthermore, the model addresses the static and dynamic recovery as key aspects during plastic deformation. In this advanced approach, the influence of twin boundaries has been incorporated and modelled flow curves show reasonable agreement with the experimental ones. The effect of different grain sizes and connected changes in the amount of twins on the flow stress can be obtained from the model. Predicted final dislocation densities and cell size are in the range of 6.91–10.26 × 10<sup>14</sup> m<sup>−2</sup> and 0.59–0.80 μm, respectively, for varying test conditions. It was observed that there is a sharp increase in dislocation density at the commencement of deformation. Concomitantly, hardening is also more profound during initial deformation. The investigation also revealed that excluding the twin boundaries in this physical-based approach would lead to underestimation of flow stress. This model also makes it possible to evaluate the relative contributions from different strengthening mechanisms.</p>

Topics
  • density
  • impedance spectroscopy
  • polymer
  • grain
  • grain size
  • dislocation
  • deformation mechanism