BACKGROUNDMetallic components are the cornerstone of modern industries such as aviation, aerospace, automobile manufacturing, and energy production. The stringent requirements for high-performance metallic components impede the optimization of materials selection and manufacturing. Laser-based additive manufacturing (AM) is a key strategic technology for technological innovation and industrial sustainability. As the number of applications increases, so do the scientific and technological challenges. Because laser AM has domain-by-domain (e.g., point-by-point, line-by-line, and layer-by-layer) localized forming characteristics, the requisite for printing process and performance control encompasses more than six orders of magnitude, from the microstructure (nanometer- to micrometer-scale) to macroscale structure and performance of components (millimeter- to meter-scale). The traditional route of laser-metal AM follows a typical “series mode” from design to build, resulting in a cumbersome trial-and-error methodology that creates challenges for obtaining high-performance goals.ADVANCESWe propose a holistic concept of material-structure-performance integrated additive manufacturing (MSPI-AM) to cope with the extensive challenges of AM. We define MSPI-AM as a one-step AM production of an integral metallic component by integrating multimaterial layout and innovative structures, with an aim to proactively achieve the designed high performance and multifunctionality. Driven by the performance or function to be realized, the MSPI-AM methodology enables the design of multiple materials, new structures, and corresponding printing processes in parallel and emphasizes their mutual compatibility, providing a systematic solution to the existing challenges for laser-metal AM. MSPI-AM is defined by two methodological ideas: “the right materials printed in the right positions” and “unique structures printed for unique functions.” The increasingly creative methods for engineering both micro- and macrostructures within single printed components have led to the use of AM to produce more complicated structures with multimaterials. It is now feasible to design and print multimaterial components with spatially varying microstructures and properties (e.g., nanocomposites, in situ composites, and gradient materials), further enabling the integration of functional structures with electronics within the volume of a laser-printed monolithic part. These complicated structures (e.g., integral topology optimization structures, biomimetic structures learned from nature, and multiscale hierarchical lattice or cellular structures) have led to breakthroughs in both mechanical performance and physical/chemical functionality. Proactive realization of high performance and multifunctionality requires cross-scale coordination mechanisms (i.e., from the nano/microscale to the macroscale).OUTLOOKOur MSPI-AM continues to develop into a practical methodology that contributes to the high performance and multifunctionality goals of AM. Many opportunities exist to enhance MSPI-AM. MSPI-AM relies on a more digitized material and structure development and printing, which could be accomplished by considering different paradigms for AM materials discovery with the Materials Genome Initiative, standardization of formats for digitizing materials and structures to accelerate data aggregation, and a systematic printability database to enhance autonomous decision-making of printers. MSPI-oriented AM becomes more intelligent in processes and production, with the integration of intelligent detection, sensing and monitoring, big-data statistics and analytics, machine learning, and digital twins. MSPI-AM further calls for more hybrid approaches to yield the final high-performance/multifunctional achievements, with more versatile materials selection and more comprehensive integration of virtual manufacturing and real production to navigate more complex printing. We hope that MSPI-AM can become a key strategy for the sustainable development of AM technologies. Download high-res image Open in new tab Download PowerpointMaterial-structure-performance integrated additive manufacturing (MSPI-AM).Versatile designed materials and innovative structures are simultaneously printed within an integral metallic component to yield high performance and multifunctionality, integrating in parallel the core elements of material, structure, process, and performance and a large number of related coupling elements and future potential elements to enhance the multifunctionality of printed components and the maturity and sustainability of laser AM technologies.

Material-structure-performance integrated laser-metal additive manufacturing.

Laser powder bed fusion additive manufacturing is an emerging 3D printing technique for the fabrication of advanced metal components. Widespread adoption of it and similar additive technologies is hampered by poor understanding of laser-metal interactions under such extreme thermal regimes. Here, we elucidate the mechanism of pore formation and liquid-solid interface dynamics during typical laser powder bed fusion conditions using in situ X-ray imaging and multi-physics simulations. Pores are revealed to form during changes in laser scan velocity due to the rapid formation then collapse of deep keyhole depressions in the surface which traps inert shielding gas in the solidifying metal. We develop a universal mitigation strategy which eliminates this pore formation process and improves the geometric quality of melt tracks. Our results provide insight into the physics of laser-metal interaction and demonstrate the potential for science-based approaches to improve confidence in components produced by laser powder bed fusion. Laser-matter interactions during laser powder bed fusion additive manufacturing remain poorly understood. Here, the authors combine in situ X-ray imaging and finite element simulations to show how detrimental pores form under printing conditions and develop a strategy to suppress them.

/pdf/dynamics-of-pore-formation-during-laser-powder-bed-fusion-31pwqc4nq7.pdf

Dynamics of pore formation during laser powder bed fusion additive manufacturing.

Mechanistic models for additive manufacturing of metallic components

Additive manufacturing enables the printing of metallic parts, such as customized implants for patients, durable single-crystal parts for use in harsh environments, and the printing of parts with site-specific chemical compositions and properties from 3D designs. However, the selection of alloys, printing processes and process variables results in an exceptional diversity of microstructures, properties and defects that affect the serviceability of the printed parts. Control of these attributes using the rich knowledge base of metallurgy remains a challenge because of the complexity of the printing process. Transforming 3D designs created in the virtual world into high-quality products in the physical world needs a new methodology not commonly used in traditional manufacturing. Rapidly developing powerful digital tools such as mechanistic models and machine learning, when combined with the knowledge base of metallurgy, have the potential to shape the future of metal printing. Starting from product design to process planning and process monitoring and control, these tools can help improve microstructure and properties, mitigate defects, automate part inspection and accelerate part qualification. Here, we examine advances in metal printing focusing on metallurgy, as well as the use of mechanistic models and machine learning and the role they play in the expansion of the additive manufacturing of metals. Several key industries routinely use metal printing to make complex parts that are difficult to produce by conventional manufacturing. Here, we show that a synergistic combination of metallurgy, mechanistic models and machine learning is driving the continued growth of metal printing.

Metallurgy, mechanistic models and machine learning in metal printing

Effect of heat treatment on the microstructural evolution of a nickel-based superalloy additive-manufactured by laser powder bed fusion.

Application of Finite Element, Phase-field, and CALPHAD-based Methods to Additive Manufacturing of Ni-based Superalloys.

Comparative grain topology

Scientific communities struggle with the challenge of effectively and efficiently sharing content and data. An online portal provides a valuable space for scientific communities to discuss challenges and collate scientific results. Examples of such portals include the Micromagnetic Modeling Group (μMAG) [1], the Interatomic Potentials Repository (IPR) [2, 3] and on a larger scale the NIH Genetic Sequence Database (GenBank) [4]. In this work, we present a description of a generic web portal that leverages existing online services to provide a framework that may be adopted by other small scientific communities. The first deployment of the PFHub framework supports phase-field practitioners and code developers participating in an effort to improve quality assurance for phase-field codes. Funding statement: D.W. wishes to acknowledge the Materials Genome Initiative funding allocated to the National Institute of Standards and Technology. S.J.D wishes to acknowledge funding from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award #DE-SC0008637 as part of the Center for PRedictive Integrated Structural Materials Science (PRISMS Center) at University of Michigan. P.W.V. is grateful for the financial assistance under the award 70NANB14H012 from the National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design (CHiMaD).

/pdf/pfhub-the-phase-field-community-hub-4oemrc8loq.pdf

PFHub: The Phase-Field Community Hub

The advent of three dimensional data collection, grain reconstruction, and subsequent materials analysis has created opportunities to revisit problems in grain growth and polycrystalline structure In this paper we review the relevant literature concerning the total number of polyhedral grains of a given number of faces and take the additional first steps at enumerating the topologies of the members within each set Analysis of the dispersion in topology relative to the idealized N-hedra is presented The relevance to grain growth simulations and experiments is discussed

Trevor Keller

Papers

Application of Finite Element, Phase-field, and CALPHAD-based Methods to Additive Manufacturing of Ni-based Superalloys.

Comparative grain topology

PFHub: The Phase-Field Community Hub

Enumeration of Polyhedra for Grain Growth Analysis