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

Putman, Duncan

  • Google
  • 3
  • 6
  • 12

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2021Thermodynamic study of single crystal, Ni-based superalloys in the γ+γ’ two-phase region using Knudsen effusion mass spectrometry, DSC and SEM9citations
  • 2018Study into the Role of Nickel Vapor on Surface Modification of a Third-Generation Single-Crystal Superalloy3citations
  • 2017Computational Study of Spacing Selection in Directionally Growing Dendritic Arrayscitations

Places of action

Chart of shared publication
Müller, Michael Michael
1 / 1 shared
Spathara, Dimitra
2 / 2 shared
Sergeev, Dmitry
1 / 1 shared
Kobertz, Dietmar
1 / 1 shared
Warnken, Nils
3 / 40 shared
Indrizzi, Vanessa
1 / 2 shared
Chart of publication period
2021
2018
2017

Co-Authors (by relevance)

  • Müller, Michael Michael
  • Spathara, Dimitra
  • Sergeev, Dmitry
  • Kobertz, Dietmar
  • Warnken, Nils
  • Indrizzi, Vanessa
OrganizationsLocationPeople

document

Computational Study of Spacing Selection in Directionally Growing Dendritic Arrays

  • Putman, Duncan
  • Warnken, Nils
  • Indrizzi, Vanessa
Abstract

The primary dendrite arm spacing (PDAS) is widely used in the directional solidification community as an important microstructural parameter. It is commonly accepted that the PDAS is not a single value, but that a range of stable spacing exists. The limits and the maximum of the PDAS distribution depend on the growth conditions of the PDAS array, namely the thermal gradient and the solidification velocity.<br/>The paper focuses on modelling the competitive growth of dendrites in an array during directional solidification, and the mechanism that establish the spacing distribution, i.e. the creation of new dendrites and removal of dendrites. <br/>For this purpose a novel mesoscale model is proposed. It is able to capture the solidification front position by tracking the positions of dendrites tips. The tracking technique is based on massless markers, each representing a dendrite tip, moving through a fixed grid. Upon changes of solidification conditions the local PDAS is adjusted, by creating new markers (dendrites) or by deleting existing ones, following sets of predefined rules. These are based on the evaluation of the spacing between each dendrite and its nearest neighbours. This yields a fast model that can take into account large numbers of dendrites.<br/>The model has been used to study directional solidification of SCN-Acetone alloy under cyclic variation of the thermal gradient. The results are compared to experimental data previously published by Ma [1]. The model does show good agreement with the experiments, and is able to reproduce the experimentally observed hysteresis effects in the PDAS upon cycling the thermal gradient. Different sets of rules reproduce different aspects of the experimental findings.<br/>

Topics
  • impedance spectroscopy
  • experiment
  • directional solidification