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Computational Mechanics

, Volume 64, Issue 4, pp 917–935 | Cite as

Computational study on microstructure evolution and magnetic property of laser additively manufactured magnetic materials

  • Min YiEmail author
  • Bai-Xiang Xu
  • Oliver Gutfleisch
Original Paper

Abstract

Additive manufacturing offers an unprecedented opportunity for the quick production of complex shaped parts directly from a powder precursor. But its application to functional materials in general and magnetic materials in particular is still at the very beginning. Here we present the first attempt to computationally study the microstructure evolution and magnetic properties of magnetic materials (e.g. Fe–Ni alloys) processed by selective laser melting (SLM). SLM process induced thermal history and thus the residual stress distribution in Fe–Ni alloys are calculated by finite element analysis (FEA). The evolution and distribution of the \(\gamma \)-Fe–Ni and \(\hbox {FeNi}_3\) phase fractions are predicted by using the temperature information from FEA and the output from CALculation of PHAse Diagrams (CALPHAD). Based on the relation between residual stress and magnetoelastic energy, magnetic properties of SLM processed Fe–Ni alloys (magnetic coercivity, remanent magnetization, and magnetic domain structure) are examined by micromagnetic simulations. The calculated coercivity is found to be in line with the experimentally measured values of SLM-processed Fe–Ni alloys. This computation study demonstrates a feasible approach for the simulation of additively manufactured magnetic materials by integrating FEA, CALPHAD, and micromagnetics.

Keywords

Additive manufacturing Magnetic materials Selective laser melting Microstructure evolution Micromagnetic simulation 

Notes

Acknowledgements

The support from the German Science Foundation (DFG YI 165/1-1 and DFG XU 121/7-1), the Profile Area From Material to Product Innovation—PMP (TU Darmstadt), the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (Grant agreement No 743116), and the LOEWE research cluster RESPONSE (Hessen, Germany) is acknowledged. The authors also greatly appreciate their access to the Lichtenberg High Performance Computer of Technische Universität Darmstadt.

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Materials ScienceTechnische Universität DarmstadtDarmstadtGermany

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