production and bolster their strategies toward a digital to physical conversion [3]. To illustrate the digital to the physical linkage of AM, Figure 1.1 serves as an overview of the gross elements for a generic AM process.
The digital nature of AM processes lends itself to the possibility of adding functionality to the components across the process chain, herein functionality relates to the form or geometry, as the geometry of the workpiece is built up from digital data, so does the functionality as relates to the material placement and material composition. Hofmann et al. [4] and Sobczak and Drenchev [5] explored the various classes of functionally graded metal components. It is useful to classify the functional gradients in AM components according to different kinds of material and geometric gradation. Figure 1.2 shows a schematic of four types of material gradients in AM technologies. Type‐I is with a single material, and the functionality comes from the design and geometry of the structure. Type‐II deals with at least two materials used during the AM process, forming a discrete interface with an abrupt transition between the two materials. Type‐III involves at least two materials with a gradient interface between them. The material gradient can be introduced by process parameter change (microstructural control) or by in‐situ physical addition of multiple materials. Type‐IV refers to any hybrid functionality that is introduced by a combination of Types I−III or by the addition of sensors/other functional mechanisms. Functionality can also be achieved by integrating several AM processes into a hybrid process chain [6]. While the geometric gradients apply to most AM components (single/multi‐material), the material gradients are process dependent. Specifically, AM machine tools can change the material either at the voxel, layer, or part level. The capabilities of the process thus determine the kinds of functional gradients in AM components, which can be classified into geometric and material gradation.
Figure 1.1 Overview of physical and digital links of an AM process chain.
Figure 1.2 Schematic overview of functional AM components.
1.1.1 Industrial Application of Metal AM in the Energy Sector
Industrial applications of functional metal AM components can be found across various sectors including nuclear power, oil & gas, turbine components, wind & tidal energy, fuel cell components, and electromagnetic energy to name a few. Some such applications are discussed in this subsection. The GE Leap fuel nozzle was one of the first certified metal AM components to undergo high‐critical testing and deployment into production [7]. Siemens has been at the forefront of metal AM applications with replacement parts for nuclear plants, sealing rings for steam turbine blades and high‐efficiency gas turbine burners [8]. Oerlikon has showcased topology optimized turbine blades and drill bits for oil & gas applications with integrated sensors [9]. Biome renewables has designed and retrofitted an AM part to increase efficiency of existing wind and tidal turbine installations [10]. Aidro has manufactured high‐pressure hydraulic manifolds and heat exchangers for oil & gas applications [11]. The Oakridge National Lab (ORNL) has demonstrated a newly designed nuclear reactor core with multi‐material and integrated sensor functionality planned in the near future [12]. Optisys manufactures high‐performance antennas for critical electromagnetic energy sensor applications for satellites [13]. Thermal management applications—like heat exchangers, fuel cell components, and rocket nozzles—greatly benefit from the design freedom offered by metal AM [14]. The diversity of potential applications for metal AM in the energy sector is just starting to be explored. A better understanding of the potential can be gained by reviewing recent advances in functional metal AM components by classifying the functionality according to geometric and material gradients.
1.1.2 Geometrical Gradients in AM
AM lends increased design freedom for the manufacturing of unique functional geometries. Hegab [15] reviewed the design aspects of geometrically graded functional materials. These range from rudimentary component optimization through integrated component design, to flexures, engineered to form compliant mechanisms that are constrained in specific degrees of freedom. The ease by which metamaterials can be manufactured from a highly engineered and well‐defined unit cell enables the construction of filters, membranes as well as light and stiff components where the uncertainty from using a stochastic manufacturing method such as foamed materials is taken out of the equation. Said metamaterials can be designed using topology optimization, also known as generative design, to functionally grade a component toward a specific wanted behavior such as thermal conductivity or elastic deformation. The above‐mentioned capabilities enable AM to be strategically employed to induce added functionality of a part. For example, how a load‐bearing part will buckle and deform and eventually collapse plastically can be precisely be achieved by a combination of integrated component design, compliant mechanisms, and topology optimized metamaterial gradient. The performance of geometrically graded AM parts depends on the voxel size, which in turn determines the limits to physical complexity. Hence, AM processes with smaller voxels, namely powder bed fusion (Section 1.2) and sintering‐based hybrid AM (Section 1.5), have the best applications of geometrical gradation.
1.1.3 Material Gradients in AM
Traditional manufacturing processes start typically from one feedstock and then convert it into the desired shape. AM processes on account of being a selective consolidation based manufacturing processes offer tremendous flexibility in functional material gradients. Naebe & Shirvanimoghaddam [16] reviewed functionally graded components manufactured through different methods and showcased the importance of AM for expanding the scope and application of functional components. Loh, Pei, Harrison, and Monzón [17] reviewed functionally graded AM components and showed that material gradation was currently only limited by AM process tool design. Rafiee, Farahani, and Therriault [18] reviewed various multi‐material additive manufacturing methodologies and found that certain AM processes are better at combining multiple materials than others. Extrusion based additive manufacturing (Section 1.5) is an example where the pointwise deposition of extrudate constitutes the workpiece, and complete control of the extrude through a mixing extruder allows for a multitude of materials to be dynamically blended and deposited [19]. Likewise, direct energy deposition (Section 1.3) allows for graded interfaces due to in‐situ powder mixing and hence allows for pointwise grading of the materials while minimizing the waste generated throughout the process [20]. In the case of powder‐bed technologies (Section 1.2) and vat photopolymerization AM (VPAM) technologies (Section 1.5), cross contamination of the feedstock materials induces the risk of a waste/component ratio where the waste product is the larger output. This can be remedied by ensuring that the build envelope is packed as densely as possible and improvements to the AM process are necessary to encourage wider adoption of material gradients in these technologies. Solid‐state AM is uniquely suited for multiple materials due to the low‐temperature processing capability that eliminates typical problems with melting and solidification (Section 1.4).
The
