Full length articleThe significance of spatial length scales and solute segregation in strengthening rapid solidification microstructures of 316L stainless steel
Graphical abstract
Introduction
Selective laser melting (SLM) is a novel technique to produce metallic parts layer by layer: a powder layer—typically 40 to 100 microns thick—is spread on a substrate, after which a laser selectively melts predetermined regions in the layer. New powder layers are spread and melted until the full part is formed. This process has numerous benefits, such as the capability to produce complex part geometries without welded weak spots, accelerated design and testing through digital twins, and the potential to produce better mechanical properties than traditional—such as wrought or cast—manufacturing techniques [1], [2], [3]. In addition, SLM can be used to directly control local process conditions to tailor the microstructure, in order to reach desired local mechanical properties [4].
316L stainless steel is an important additive manufacturing material with applications in the biomedical and aerospace industries. Traditionally manufactured 316L steel nevertheless suffers from relatively low yield strength [5], whereas 316L produced with properly optimized SLM can exhibit high yield strengths, which can be attributed primarily to the subgrain cellular microstructure that develops during rapid solidification [6], [7], [8], [9], [10].
Nonetheless, while there has been significant progress in understanding the micromechanics of additively manufactured 316L steel [8], [11], lack of clarity exists the relative importance of different microstructure features (cell spacing, microsegregation, dislocations structures, grain boundaries) in determining its unique mechanical properties. The link to performance, such as fatigue life, also remains unclear. Furthermore, the relationship between local process conditions and the cellular solidification microstructure is still not fully understood, although important contributions have been made, for example, in linking experimental cell spacing to scanning speed [12], [13], [14] or estimated cooling rates [15]. Overall, the lack of deep understanding between process conditions, rapid solidification microstructures and micromechanical response are reflected in a significant variation in the reported mechanical properties (yield strength, elongation to failure) for SLM of 316L steel [8], [9], [16], [17].
Causal links between process conditions, solidification microstructures, and the resulting mechanical behavior can be better understood with computer modeling. For example, Keller et al. conducted process-structure modeling SLM of Inconel 625 by coupling a heat transfer process model to a 2D directional solidification phase field model [18], and Ghosh et al. extended these phase field simulations to three dimensions [19], comparing the cell spacing to scaling laws and cell core compositions to analytical models. Kundin et al. presented a 2D multi-component phase field modeling analysis for selective laser melting of manganese steel to investigate the model convergence and cell spacings [20].
There have been several micromechanical modeling based investigations of SLM 316L structures. Bronkhorst et al. conducted crystal plasticity simulations for directed energy deposited 316L polycrystalline structures [11] with an explicit description of dislocation density evolution. They concluded that the length scale effects and initial dislocation density play an important role in determining the materials mechanical behavior, and that microsegregation can also contribute to the material behavior. However, their model only assumed collective size dependency, i.e. grain size effects were imposed top-down as a classical Hall-Petch relation without directly considering geometrically necessary dislocation (GND) type hardening in the model. Wang et al. suggested that the grain substructure determines the SLM 316L mechanical behavior in low strain regime, which is typically observed as the initial yield strength of the material [8]. Their simulations included polycrystalline microstructures, but they omitted the grain substructures in their simulation work. Therefore, there is a knowledge gap in simulating grain substructures within a crystal plasticity model.
The process-structure-properties relationships for SLM manufactured 316L steel are presented schematically in Fig. 1. These relationships are complex as shown by the black and red connectors. However as mentioned earlier, there is a close coupling between microhardness (plastic flow resistance and initial stages of plasticity), subgrain cellular microstructure, and local process conditions; these are the relationships that are investigated in this work (red connectors). In addition, strengthening due to grain boundaries is also considered. As discussed earlier, previous studies show that microhardness (initial stages of plasticity) is determined primarily by the subgrain cellular structure for 316L steel produced via SLM [6], [7], [8], [9], [10]. Furthermore, this cellular structure is determined by the local process conditions at the melt pool (ultimately reduced to thermal gradient G, pulling speed Vp), which are primarily determined by the SLM laser power, scanning speed, and beam width [12], [13], [14], [15]. In order to perturb these cellular structure markedly, proper post heat treatments are required [7], [21]. Here pulling speed Vp refers to the local melt pool solidification velocity, which is typically significantly smaller than the laser scanning speed due to a high angle between the scan vector and the melt pool boundary [15].
This work serves as a proof-of-concept for investigating the causal linkages between alloy chemistry, SLM process conditions, and rapid solidification microstructures. Microstructures obtained via phase field modeling are further linked to a length-scale-dependent micromechanical behavior during the initial stages of plasticity via crystal plasticity modeling. The linkage used in this work is sequential, meaning that there is no back-coupling from the crystal plasticity model to the phase field model. We focus on the subgrain cellular solidification structure, and the associated strengthening effects due to solid solution strengthening and length-scale dependence. In addition, we consider strengthening effects due to grain boundaries. A quantitative rapid solidification phase field model is used to generate cellular solidification microstructures for a range of process conditions characterized by a combination of thermal gradient and pulling speed. The phase field model contains relevant rapid solidification effects through an anisotropic kinetic coefficient, and an appropriate description of solute trapping. The resulting solidification structures are compared to the available experimental cell spacing - cooling rate data in the literature. From these solidification structures, representative domains are extracted, and their mechanical response is simulated with a Cosserat crystal plasticity model. In addition, idealized Voronoi-tessellated polycrystalline structures are considered to investigate strengthening due to grain boundaries. The effect of local variations in solid solution strengthening due to microsegregation is modeled by defining a different slip resistance for cell core and cell boundaries, corresponding to different local compositions. Microstructural length-scale effects are incorporated separately both in the initial yielding and hardening rules. The crystal plasticity model is calibrated based on experiments from the literature, starting from grain size dependency of traditionally manufactured low cooling rate 316L structures, and finally using available experimental and characterization data for SLM microstructures.
Section snippets
Methods
In what follows, we assume that 316L stainless steel has a nominal composition of Fe-17wt%Cr-11wt%Ni-2.5wt%Mo, shown in Table 1 together with the AISI 316L steel composition range. Although the equilibrium high-temperature phase is BCC ferrite, in rapid solidification the ferritic phase disappears completely [22], [23]. Therefore, the only relevant rapid solidification phase transformation is liquid to FCC.
The modeling methods consist of phase field model for rapid solidification (Section 2.1),
Rapid solidification microstructures
Selective laser melting (SLM) operated in continuous scanning mode leads to directional solidification conditions, and produces evident cellular subgrain structures. The cellular solidification structure features (cell spacing, microsegregation) are directly linked to the local directional solidification conditions, ultimately characterized by thermal gradient G and pulling speed Vp [41].
Therefore, solidification in the phase field model is driven by thermal gradient G moving at pulling speed Vp
Discussion
Our crystal plasticity simulations suggest that in SLM of 316L, cell spacing is more important than the magnitude of solute segregation (concentration difference between cell core and cell boundary). Furthermore, our phase field simulations suggest that cell spacing is significantly more sensitive to solidification speed (pulling speed) than to thermal gradient; this is supported by earlier investigations [20]. Therefore it is likely that pulling speed is the main process condition that should
Conclusion
We analyzed the relationship between process conditions, solidification microstructures, and micromechanical responses, for selective laser melting (SLM) of 316L stainless steel, based on sequentially coupled rapid solidification phase field modeling and micromechanical crystal plasticity modeling.
The phase field model assumed an ideal dilute binary alloy where diffusion of chromium was considered. The solute trapping effects were described quantitatively using the results of an asymptotic
Declaration of Competing Interest
The authors declare that they do not have any financial or nonfinancial conflict of interests.
Acknowledgement
This work was supported by Academy of Finland under HIERARCH project, Grant No. 318065. NP wishes to acknowledge the National Science and Engineering Research Council of Canada, and the Canada Research Chairs for support with this project. MW wishes to acknowledge the VINN Excellence Center Hero-m 2i, financed by the Swedish Governmental Agency for Innovation Systems (VINNOVA) for support in this project.
References (57)
- et al.
Additive manufacturing of metallic components–process, structure and properties
Prog. Mater. Sci.
(2018) - et al.
Modulating laser intensity profile ellipticity for microstructural control during metal additive manufacturing
Acta Mater.
(2017) - et al.
Recent developments in stainless steels
Mater. Sci. Eng. R Rep.
(2009) - et al.
Additively manufactured hierarchical stainless steels with high strength and ductility
Nat. Mater.
(2018) - et al.
Structural representation of additively manufactured 316l austenitic stainless steel
Int. J. Plast.
(2019) - et al.
Energy input effect on morphology and microstructure of selective laser melting single track from metallic powder
J. Mater. Process. Technol.
(2013) - et al.
Dislocation network in additive manufactured steel breaks strength–ductility trade-off
Mater. Today
(2018) - et al.
Intragranular cellular segregation network structure strengthening 316l stainless steel prepared by selective laser melting
J. Nucl. Mater.
(2016) - et al.
Microstructure and fracture behavior of 316l austenitic stainless steel produced by selective laser melting
J. Mater. Sci. Technol.
(2016) - et al.
Application of finite element, phase-field, and CALPHAD-based methods to additive manufacturing of ni-based superalloys
Acta Mater.
(2017)
Simulation and analysis of γ-ni cellular growth during laser powder deposition of ni-based superalloys
Comput. Mater. Sci.
Effect of heat treatment on microstructure and mechanical properties of 316l steel synthesized by selective laser melting
Mater. Sci. Eng. A
Thermo-calc & dictra, computational tools for materials science
CALPHAD
Quantitative phase field modeling of solute trapping and continuous growth kinetics in quasi-rapid solidification
Acta Mater.
Solute trapping in aluminum alloys
Acta Metall. Mater.
Quantitative 3d phase field modelling of solidification using next-generation adaptive mesh refinement
Comput. Mater. Sci
Cosserat continuum modelling of grain size effects in metal polycrystals
Proc. Appl. Math. Mech.
Hallâpetch behaviour of 316l austenitic stainless steel at room temperature
Mater. Sci. Technol.
On the Hall–Petch relationship and substructural evolution in type 316L stainless steel
Acta Metall. Mater.
Solidification microstructures: a conceptual approach
Acta Metall. Mater.
Simulation of the cell to plane front transition during directional solidification at high velocity
J. Cryst Growth
Solidification
Estimation of melt pool dimensions, thermal cycle, and hardness distribution in the laser-engineered net shaping process of austenitic stainless steel
Metall. Mater. Trans. A
Time-resolved in situ measurements during rapid alloy solidification: experimental insight for additive manufacturing
JOM
Phase-field modeling of binary alloy solidification with coupled heat and solute diffusion
Phys. Rev. E
Phase-field modeling of solute trapping: comparative analysis of parabolic and hyperbolic models
Int. J. Mater. Res.
Modeling of additive manufacturing processes for metals: challenges and opportunities
Curr. Opin. Solid State Mater. Sci.
Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing
Comput. Mech.
Cited by (115)
Stress corrosion cracking behavior of 316 L manufactured by different additive manufacturing techniques in hydrofluoric acid vapor
2024, Journal of Materials Science and TechnologySoftening mechanism and failure behavior of 9Cr oxide dispersion strengthened steel resistance spot welded joint
2024, Journal of Manufacturing ProcessesMicrostructural evolution and multi-mechanism strengthening model of nanocrystalline Al-Mg alloys
2024, Journal of Alloys and CompoundsThe effects of SLM process parameters on the relative density and hardness of austenitic stainless steel 316L
2024, Journal of Materials Research and Technology