Advancing Metal Additive Manufacturing: Engineering Microstructures for Tailored Properties

Significance 

Modern metal manufacturing processes have traditionally relied on a combination of mechanical and thermal techniques to shape materials and control their microstructure and properties. Processes like forging and extrusion apply mechanical strain to metals, altering their properties through dislocation accumulation and subsequent heat treatment-induced recrystallization. These methods have been employed since ancient times, but they face limitations in the context of modern additive manufacturing (AM) technologies, also known as 3D printing. AM allows the creation of complex geometries by depositing materials layer by layer. However, this simultaneous formation of material and geometry limits the ability to control the microstructure of metals without compromising the part’s intricate shape. Researchers from the University of Cambridge, led by Professor Dr. Matteo Seita, have published a study in the peer-reviewed journal Nature Communications that introduces innovative strategies for controlling the microstructure of additively manufactured stainless steel without relying on mechanical deformation. By leveraging laser powder bed fusion (LPBF) technology, the research team has developed techniques to program the thermal stability of stainless steel, enabling precise control over its microstructure in three dimensions at high spatial resolution.

Recrystallization is a crucial process in traditional thermo-mechanical metal manufacturing, where mechanical deformation triggers microstructural changes, leading to improved material properties. Previous research by the team showed that recrystallization in stainless steel 316L produced by LPBF shares similar mechanisms with conventionally produced metals. It is driven by a critical dislocation density and influenced by chemical heterogeneity within the microstructure. To gain control over dislocation density and chemical heterogeneity during LPBF, the authors devised two distinct processing strategies: “H” and “L.” These strategies vary the density of geometrically necessary dislocations and promote chemical homogenization through the manipulation of parameters like hatch spacing and laser scanning. After heat treatment, the “H” strategy yielded a microstructure similar to the as-printed state, while the “L” strategy resulted in complete recrystallization, demonstrating precise control over microstructure evolution. Remarkably, the researchers demonstrated site-specific microstructure control by encoding binary code into the material’s microstructure, showcasing the three-dimensional capabilities of their approach. Furthermore, these strategies are machine-agnostic, emphasizing their versatility in various LPBF machines. The level of 3D microstructure design achieved in new study is unprecedented in the field. Unlike previous methods that created two-dimensional architectures, these LPBF strategies offer deformation-free, site-specific control over microstructure, allowing the modification of multiple microstructural features simultaneously.

LPBF materials can be viewed as stacks of overlapping melt pools, with each pool inducing localized thermo-mechanical effects. The number of melt pools per unit area per layer, determined by hatch spacing, affects the total plastic strain and dislocation density in the as-printed material. The authors confirmed that varying hatch spacing allows precise tuning of dislocation density without requiring additional mechanical deformation. Micro-segregation of solute elements during solidification can hinder recrystallization by creating chemical heterogeneity in the alloy. The density of cells and the amount of solute segregating at cell boundaries affect the alloy’s thermal stability. Laser remelting was applied to dissolve this micro-segregation, promoting complete recrystallization. Operando X-ray diffraction experiments confirmed that changes in hatch spacing did not significantly affect heating and cooling rates during LPBF. This indicates that the altered dislocation density arises primarily from changes in cumulative plastic strain. Furthermore, the researchers found that recrystallization was influenced by residual stresses and oxide nanoparticle formation, although these factors did not play a significant role in thermal stability compared to dislocation density and chemical homogenization. They also demonstrated that programming thermal stability during LPBF enables the engineering of mechanical properties to a greater extent than conventional thermo-mechanical processes. Layered microstructures containing combinations of recrystallized and non-recrystallized regions exhibited enhanced mechanical properties due to hetero-deformation induced (HDI) strengthening. The interfaces between these microstructures, composed of one “soft” and one “hard” phase, contributed to increased strength and work hardening.

The volume fraction and thickness of the constituent microstructure-layers were manipulated to create coarse and fine architectures. The authors’ findings showed that the mechanical properties followed the rule-of-mixture for coarse architectures, but the fine architecture exhibited work hardening exceeding the predicted behavior. This phenomenon was attributed to HDI strengthening, where GNDs accommodating plastic strain incompatibility generated back and forward stresses along the interfaces. They developed a viscoplastic model to predict the mechanical response of these layered microstructures. The model considered properties of the individual microstructures and the interface zone. Experimental data confirmed that the model accurately predicted the behavior of different architectures with varying numbers of interface zones.

This groundbreaking research offers promising avenues for advancing metal additive manufacturing. By programmatically controlling microstructures through LPBF, engineers can tailor material properties with unprecedented precision. The ability to encode three-dimensional microstructures and manipulate multiple microstructural features simultaneously opens up new opportunities for designing materials with optimized properties and novel functionalities. Future applications of this technology could include materials resistant to fatigue or hydrogen embrittlement, enhancing the performance and safety of critical components in various industries. While this study focused on stainless steel, the principles and techniques presented here are expected to be applicable to a wide range of materials produced by LPBF.

Advancing Metal Additive Manufacturing: Engineering Microstructures for Tailored Properties - Advances in Engineering
Credit image: Nature Communications, 2023; 14 (1) DOI: 10.1038/s41467-023-42326-y

About the author

Dr Matteo Seita

Granta Design Assistant Professor
University of Cambridge 

Research interests

My research focuses on metal additive manufacturing (AM), characterization and testing, and microstructure engineering of structural alloys. I’m very interested in studying how the point-by-point material forming process typical of AM yields the microstructure heterogeneity that is frequently observed in metal parts. This heterogeneity is a double-edged sword. On the one hand, it leads to large property scatter and casts uncertainty over parts performance, hindering the adoption of additive technologies by the industry. On the other hand, it may impart exceptional mechanical properties, which even surpass those found in conventionally produced materials. My goal is to understand and control this microstructure heterogeneity to design and produce materials with “architected microstructures” which will exhibit more predictable behavior and tailored functionalities. My vision is that this unique capability will enable a new design paradigm in metal AM for producing both geometry-and microstructure-optimized parts.

Reference

Shubo Gao, Zhi Li, Steven Van Petegem, Junyu Ge, Sneha Goel, Joseph Vimal Vas, Vladimir Luzin, Zhiheng Hu, Hang Li Seet, Dario Ferreira Sanchez, Helena Van Swygenhoven, Huajian Gao, Matteo Seita. Additive manufacturing of alloys with programmable microstructure and properties. Nature Communications, 2023; 14 (1) DOI: 10.1038/s41467-023-42326-y

Go to Nature Communications

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