Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting
By Y. Zhong, Leifeng Liu, S. Wikman, D. Cui, Zhijian Shen. 2016
681 citations recorded by the source corpus.
Subfields: Automotive Engineering, Materials Chemistry, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/1f707062b4311759f0e5d5d3fad10860f7e03bea
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- S. M. Yusuf
- N. Gao
- J. van Humbeeck
- I. Yadroitsev
- Jean-Pierre Kruth
- I. Yadroitsava
- Dierk Raabe
- E. Jägle
In Materials Chemistry
In Mechanical Engineering
- N. Gao
- S. M. Yusuf
- I. Yadroitsev
- I. Yadroitsava
- J. van Humbeeck
- Jean-Pierre Kruth
- E. Jägle
- Pavel Krakhmalev
Citations in the corpus
- High cycle fatigue life prediction of laser additive manufactured stainless steel: A machine learning approach (2019, background): “directional grains and melt pools at the macro-scale, and ultrafine sub-grains, porosities and inclusions at the micro-scale [16, 17], become relevant.”
- Steels in additive manufacturing: A review of their microstructure and properties (2020, background): “The high tensile and yield strength have been related to the finer microstructure and dislocation substructure as per Hall-Petch relation [27,38,42,47].”
- Fatigue and fracture behaviour of laser powder bed fusion stainless steel 316L: Influence of processing parameters (2017, background): “The ultrafine grains are in the order of a few microns [13, 14], which is much smaller than the length scale of casting where dendrite cells and second phase particles are in the order of tens of microns [15, 16].”