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  4. Exploring crystallographic texture manipulation in stainless steels via laser powder bed fusion: insights from neutron diffraction and machine learning
 
research article

Exploring crystallographic texture manipulation in stainless steels via laser powder bed fusion: insights from neutron diffraction and machine learning

Sofras, Christos
•
Čapek, Jan
•
Leinenbach, Christian
Show more
2024
Virtual and Physical Prototyping

Laser powder bed fusion of metals (PBF-LB/M) is a pivotal additive manufacturing technique that enables the production of intricate components. In addition to enabling the production of complex shapes, it allows for a high degree of freedom in manipulating the microstructure. The present investigation explores the manipulation of the crystallographic texture in AISI 304L stainless steels via PBF-LB/M, due to the possibility of tailoring the secondary hardening phenomena. Neutron diffraction provides efficient texture assessment, while decision tree regression reveals the complex interplay between processing parameters and the resulting crystallographic textures. Our investigation identifies the optimal PBF-LB/M processing parameters for obtaining strong texture along the build and laser scan directions. Additionally, microstructural characterisation of selected samples reveals the complex solidification structures. By employing advanced characterisation techniques and machine learning, this work provides insights into achieving or avoiding specific crystallographic textures during PBF-LB/M processing of stainless steels or other materials.

  • Details
  • Metrics
Type
research article
DOI
10.1080/17452759.2024.2390483
Scopus ID

2-s2.0-85201525888

Author(s)
Sofras, Christos

Laboratory for Neutron Scattering, Villigen

Čapek, Jan

Laboratory for Neutron Scattering, Villigen

Leinenbach, Christian

Empa - Swiss Federal Laboratories for Materials Science and Technology

Logé, Roland E.  

École Polytechnique Fédérale de Lausanne

Strobl, Markus

Laboratory for Neutron Scattering, Villigen

Polatidis, Efthymios

Laboratory for Neutron Scattering, Villigen

Date Issued

2024

Published in
Virtual and Physical Prototyping
Volume

19

Issue

1

Article Number

e2390483

Subjects

crystallographic texture

•

machine learning

•

neutron diffraction

•

PBF-LB/M

•

process optimisation

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LMTM  
FunderFunding(s)Grant NumberGrant URL

Swiss National Science Foundation

200021_188767

Available on Infoscience
January 24, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/243580
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