Metallurgy, mechanistic models and machine learning in metal printing

DebRoy, T.; Mukherjee, T.; Wei, Huiliang; Elmer, J. W.; Milewski, J.

doi:10.1038/s41578-020-00236-1

Cited by 247 publications

(83 citation statements)

References 204 publications

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“…However, the flowchart of Figure 17 allows numerical teams to easily implement a set of phenomenological equations based on physical roots. Therefore, improvement within the so-called mechanistic models can be achieved thanks to the specific highlighting of the mechanisms that govern each type of transformation in solid phase [ 73 ].…”

Section: Discussionmentioning

confidence: 99%

“…From a different perspective, machine learning (ML) has been used in all steps of AM as a tool that allows for rapidly predicting the microstructure, properties and defects without dealing with the solution of complex equations based on phenomenological understanding [ 73 ]. A combination of the TTB concept with rapidly evolving ML approaches opens up very promising prospects for future works.…”

Section: Discussionmentioning

confidence: 99%

“…Phase field models are used to resolve microstructural features in small length scales [ 71 , 72 , 73 ]. For this purpose, an order parameter based on free energy that represents the state of the entire microstructure is calculated, assuming all the variables to be continuous across the interface [ 72 ].…”

Section: Solid Phase Transformation Mechanisms and Kinetics—state Of The Artmentioning

confidence: 99%

“…Phase field-base models often tackle both precipitation and dissolution of second-phase particles on the one hand, and diffusive transformations on the other. Therefore, martensitic transformations are ignored [ 73 ].…”

Section: Solid Phase Transformation Mechanisms and Kinetics—state Of The Artmentioning

confidence: 99%

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A New Concept for Modeling Phase Transformations in Ti6Al4V Alloy Manufactured by Directed Energy Deposition

et al. 2021

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The microstructure directly influences the subsequent mechanical properties of materials. In the manufactured parts, the elaboration processes set the microstructure features such as phase types or the characteristics of defects and grains. In this light, this article aims to understand the evolution of the microstructure during the directed energy deposition (DED) manufacturing process of Ti6Al4V alloy. It sets out a new concept of time-phase transformation-block (TTB). This innovative segmentation of the temperature history in different blocks allows us to correlate the thermal histories computed by a 3D finite element (FE) thermal model and the final microstructure of a multilayered Ti6Al4V alloy obtained from the DED process. As a first step, a review of the state of the art on mechanisms that trigger solid-phase transformations of Ti6Al4V alloy is carried out. This shows the inadequacy of the current kinetic models to predict microstructure evolution during DED as multiple values are reported for transformation start temperatures. Secondly, a 3D finite element (FE) thermal simulation is developed and its results are validated against a Ti6Al4V part representative of repair technique using a DED process. The building strategy promotes the heat accumulation and the part exhibits heterogeneity of hardness and of the nature and the number of phases. Within the generated thermal field history, three points of interest (POI) representative of different microstructures are selected. An in-depth analysis of the thermal curves enables distinguishing solid-phase transformations according to their diffusive or displacive mechanisms. Coupled with the state of the art, this analysis highlights both the variable character of the critical points of transformations, and the different phase transformation mechanisms activated depending on the temperature value and on the heating or cooling rate. The validation of this approach is achieved by means of a thorough qualitative description of the evolution of the microstructure at each of the POI during DED process. The new TTB concept is thus shown to provide a flowchart basis to predict the final microstructure based on FE temperature fields.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Solid Phase Transformation Mechanisms and Kinetics—state Of The Artmentioning

confidence: 99%

Section: Solid Phase Transformation Mechanisms and Kinetics—state Of The Artmentioning

confidence: 99%

See 2 more Smart Citations

A New Concept for Modeling Phase Transformations in Ti6Al4V Alloy Manufactured by Directed Energy Deposition

et al. 2021

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“…As in casting and fusion welding, fusion-based metal additive manufacturing inevitably compromises the control of porosity, residual stress, and hot cracking due to the liquid phase bonding mechanism [18,19]. These issues are especially worsened by the small molten pool size, large thermal gradient, and high cooling rate [20]. Moreover, because textured, columnar grain structures naturally form along the build direction [21], microstructure control has been a recurring challenge despite the advances in recent years [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Additive friction stir deposition: a deformation processing route to metal additive manufacturing

Mishra

2020

Materials Research Letters

103

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As the forging counterpart of fusion-based additive processes, additive friction stir deposition offers a solid-state deformation processing route to metal additive manufacturing, in which every voxel of the feed material undergoes severe plastic deformation at elevated temperatures. In this perspective article, we outline its key advantages, e.g. rendering fully-dense material in the as-printed state with fine, equiaxed microstructures, identify its niche engineering uses, and point out future research needs in process physics and materials innovation. We argue that additive friction stir deposition will evolve into a major additive manufacturing solution for industries that require high load-bearing capacity with minimal post-processing. IMPACT STATEMENT This paper delineates additive friction stir deposition, which offers a solid-state deformation processing route to metal additive manufacturing and renders fully-dense material with fine, equiaxed microstructures in the as-printed state.

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Issues in Metal Matrix Composites Fabricated by Laser Powder Bed Fusion Technique: A Review

Essien

Vaudreuil

2022

Adv Eng Mater

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Technologies for the additive manufacturing (AM) of metals have progressed throughout the years, with significant improvements in both quality of AM components and wider scale application. In just about every current application for powder bed fusion (PBF) processes, the powders used are alloys of base metals like aluminum, iron, nickel, cobalt, and titanium, with a chemistry sometimes adapted to enable their processing by a laser-based system. While the current state of development enables the production of parts for demanding industries such as aerospace, a new class of materials such as metal matrix composites (MMCs) could enhance further applications of AM-fabricated metallic parts. MMCs combine a metallic powder with a reinforcing agent, a ceramic powder being the most commonly used. These powders can be mixed, blended, or mechanically alloyed together into a composite powder, before being consolidated layer-by-layer into the designed part. [1] This part will exhibit reinforcement particles dispersed within the bulk metal matrix. The MMCs development thus needs to achieve enhanced properties through a compromise between tenacity of the matrix and the rigidity of reinforcing particles. Figure 1 shows a schematic of processed MMC and its processing steps.The PBF process uses a high energy laser to fuse powder particles into a near net shape component. Combining different parameters (preprocessing, processing, etc.) to produce a fully dense part in AM is, however, a complex process. The consolidation process involves multiple phenomena such as heating (thermal expansion), melt pool formation, solidification, and cooling (thermal contraction), all of which occur simultaneously and in a repeated manner. [2,3] This process complexity is increased significantly when trying to attain fully dense MMC from metal and ceramic. Multiple reasons are involved, ranging from the raw materials used to interactions between laser and powder. A segregation of dissimilar materials found in the composite powder (mixed powder system) can arise on the build platform during feeding. [4] This would create issues of particles clustering and uneven dispersion, encouraging further defects formation.The capability of fabricating fully dense components with desired properties (mechanical, electrical, etc.) and less defects in AM has been the focus of researchers and industries. [5] However, inherent defects like porosities and surface roughness in AM parts remain a challenge. Various factors related to AM machines, material properties, and processing parameters are responsible for these defects.Processing parameters influence the overall quality of AM parts by influencing temperature gradients, consolidation and solidification, thermal-induced stresses as well as the susceptibility of PBF-processed part to defects. Changes in powder chemical composition can influence consolidation and defect generation. [6,7] Proper considerations must, thus, be given in understanding, predicting, and preventing defects in PBF-processed

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Metallurgy, mechanistic models and machine learning in metal printing

Cited by 247 publications

References 204 publications

A New Concept for Modeling Phase Transformations in Ti6Al4V Alloy Manufactured by Directed Energy Deposition

A New Concept for Modeling Phase Transformations in Ti6Al4V Alloy Manufactured by Directed Energy Deposition

Additive friction stir deposition: a deformation processing route to metal additive manufacturing

Issues in Metal Matrix Composites Fabricated by Laser Powder Bed Fusion Technique: A Review

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