Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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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.

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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.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2019Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantificationcitations
  • 2019Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantification26citations

Places of action

Chart of shared publication
Pericieous, K.
1 / 1 shared
Phillion, Ab
1 / 4 shared
Kao, A.
2 / 3 shared
Cai, B.
1 / 9 shared
Boller, E.
2 / 24 shared
Lee, Pd
1 / 41 shared
Leonardis, A.
1 / 1 shared
Leonardis, Ales
1 / 1 shared
Pericleous, K.
1 / 17 shared
Lee, P. D.
1 / 70 shared
Cai, Biao
1 / 13 shared
Phillion, A. B.
1 / 13 shared
Chart of publication period
2019

Co-Authors (by relevance)

  • Pericieous, K.
  • Phillion, Ab
  • Kao, A.
  • Cai, B.
  • Boller, E.
  • Lee, Pd
  • Leonardis, A.
  • Leonardis, Ales
  • Pericleous, K.
  • Lee, P. D.
  • Cai, Biao
  • Phillion, A. B.
OrganizationsLocationPeople

article

Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantification

  • Basevi, H.
  • Kao, A.
  • Leonardis, Ales
  • Pericleous, K.
  • Boller, E.
  • Lee, P. D.
  • Cai, Biao
  • Phillion, A. B.
Abstract

Fe contamination is a serious composition barrier for Al recycling. In Fe-containing Al-Si-Cu alloy, a brittle and plate-shaped β phase forms, degrading the mechanical properties. Here, 4D (3D plus time) synchrotron X-ray tomography was used to observe the directional solidification of Fe-containing Al-Si-Cu alloy. The quantification of the coupled growth of the primary and β phase via machine learning and particle tracking, demonstrates that the final size of the β intermetallics were strongly influenced by the solute segregation and space available for growth whereas the β orientation was controlled by the temperature gradient direction. The work can be used to validate predictive models.

Topics
  • impedance spectroscopy
  • phase
  • tomography
  • intermetallic
  • machine learning
  • directional solidification