process [Yoder et al. 2021 Griffiths et al. 2019, 2021]) and rely upon frictional or ultrasonic methods of joining. The heat sources for fusion-based techniques include lasers, electron beams, plasma sources, and, most recently, resistance-based techniques (such as Joule heating [Huang et al. 2014 Batista et al. 2020]). The incoming material to be added is prototypi- cally wire or powder, but can also include thin sheet or ribbon (Kobryn et al. 2022 Hascoet et al. 2014). The atmospheres can be equally varied, ranging from vacuum to inert shield gas to deposition in controlled atmosphere glove boxes. This variability has an impact on the composition of the as-deposited materials in fusion-based systems. AM systems can be additive only, or hybrid involving the recursive oper- ation of both additive and subtractive (machining), or other techniques, such as laser peening for local control of the residual stress (Hackkel et al. 2018 Madireddy et al. 2019). Systems can be equipped to deliver material from a single feed source or from multiple feed sources to enable the spatial control of the composition in a preprogrammed manner (Kelly et al. 2021 Schwartz and Boydston 2019). The as-de- posited structures can be free form or supported using lattice structures such as in powder beds (Collins et al. 2016 Davis et al. 2009 Zalameda et al. 2013 Vaissier et al. 2019 Hussein et al. 2013). Similarly, the architectures can be designed to be fully dense, lattices, or with variations of controlled internal cavities (Juechter et al. 2018 Wang et al. 2018 Tao 2016 Gardan and Schneider 2015). Figure 1 provides a broad overview of the types of structures, systems, and processes that exist. Considering these capabilities in aggregate, and imagining future systems where the “material effectors” are selectable to achieve a particular materials state with a particular function in a particular location (a logical fusion of concepts found in AM and metamorphic manufacturing [Xie et al. 2016 Daehn and Taub 2018 Feucht et al. 2020 Love et al. 2013 Good and Landau 2017]), one can begin to conceive of new materials and desirable topologies across a range of length scales. In general, the types of physical processes of fusion-based AM techniques involve: the transfer of energy from the heat source into the material, which includes consideration of the material’s reflectivity to the particular energy wavelength and adjusted for particular configurations that correspond to the efficiency and redun- dancy of energy-impingement events the heat-transfer mechanisms within the part, including radiation, conduction, and convection (Raghavan et al. 2013 Gutowski et al. 2017) the heat-transfer mechanisms associated with the material’s thermodynamics, including phase transformations and any attending enthalpy of mixing of different species (Kumara et al. 2020 Zhang et al. 2019b Kenel et al. 2017) the fluid dynamics of the liquid, including Marangoni convection, buoyancy, gravity, and other complex melt-pool dynamics (Hojjatzadeh et al. 2019 Gan et al. 2017 Khairallah et al. 2016) possible secondary processes in proximity to the molten pool, including capillarity, wetting, sintering, and thermal grooving (Blank et al. 2019 Mullins 1957, 1958) dynamics mediated by the liquid/vapor interface, including volatilization or gettering of elemental species, and the gas dynamics, including kinetic motion of molecules (Sato and Kuwana 1995 Semiatin et al. 2004 Collins et al. 2014) physical processes at the liquid/solid interface, including melting and solidification solid-state phase transformations and the current evolution (and retention) of elastic-plastic defor- mation processes induced by either phase transformations, phase evolution, or transients in thermal gradients. These processes are further complicated by the motion of the heat source, inducing so-called thermal gyrations into the part whose magnitude and frequency are functions of the part geometry and the build scan strategies (G-code). Each of these is sufficiently complex so as to merit their own treatment, and as such lies beyond the scope of this paper. However, an understanding of such broad categorizations is helpful to understand the types of measurements that will be useful in understanding key metrics of the materials state that influ- ence the properties and performance of the material. Table 1 provides correlations between these general types of physical processes and a hierarchy of materials state parameters that govern the properties and performance of materials. For some materials, these correlations have been quantified, and the most important factors have been determined. Important Materials State Factors From the perspective of failure in most metallic systems (assuming a reasonable level of ductility), the principal aim is to understand the presence of defects and damage and their evolution during service. Thus, concepts such as fatigue and fracture go hand in hand with materials state awareness and any attempt to link NDE methods with AM, whether ex situ or in situ. In AM materials, the dominant macroscopic defects include porosity, lack of fusion (LOF), cracking/tearing, and balling. After the macroscopic defects are considered, two other variables demand our attention. The first variable, residual stress, can couple with defects, leading to unexpected failure. Explicitly, it is necessary to state that residual stress is the gradient in the local density of dislocations, which are the atomic-scaled line defects responsible for an alloy’s ductil- ity, and which can lead to considerable strengthening of the material. Thus, a material can have a low average dislocation density but a high residual stress (large gradients), a high dis- location density but a low residual stress (small gradients), or other permutations. The second variable involves grains, their size, and any preferential crystallographic orientation, also known as texture. Texture is increasingly recognized as having an important role on the properties and performance of materials. Texture is very common in AM materials, owing to ME | AMNDEOVERVIEW 48 M A T E R I A L S E V A L U A T I O N • A P R I L 2 0 2 2

the steep thermal gradients and rapid solidification (Quintana et al. 2020 Saville et al. 2021 Kamath et al. 2021 Kunze et al. 2015 Dinda et al. 2012 Song et al. 2014), though it can be con- trolled through processing. The presence of periodic texture has been linked with some challenges in inspectability. The final two broad categories, materials composition (both average and local) and the “rest” of the microstructure (typically phases, their size and distribution) are critically important to setting the baseline mechanical properties of engineering alloys (such as strength, ductility, and fracture toughness). At a minimum, there are local compositional fluc- tuations in AM components (Kenney et al. 2021 Collins 2004 Hayes et al. 2017), which can lead to variations in the elastic stiffness tensor (Cij), and thus should be relevant for the NDE community. These five categories of variables are described briefly in the following sections. Interestingly, there is a coupling between these variables that provides potential strategies to better identify them using NDE techniques. Some examples of coupling between variables will be introduced. Defects There are at least five types of macroscopic defects associated with a volumetric variation of some sort: spherical porosity, LOF porosity, balling, cracking or hot tearing, and fish scaling (Zhou et al. 2015 Tammas-Williams et al. 2015 Pogson et al. 2004 Sochalski-Kolbus et al. 2015). Figure 2 provides examples of these four types of macroscopic defects. Often and erroneously, spherical porosity (Figure 2a) is assumed to indicate an existing gas pore. The correct interpre- tation is that the pore formed when it consisted of a gaseous species inside the pore. However, there are two sources for such gas. The first source is gaseous elements, such as argon, that are contained in some powder particles prior to depo- sition or that are captured by liquid dynamics from the sur- rounding atmosphere. These elemental species will remain in the pores and are unlikely to be healed permanently through other post-deposition processing steps (Kenney et al. 2021 Collins et al. 2016 Collins 2004 Zhang et al. 2019a Chlebus et al. 2015). The second source is alloying elements that are vaporized and create a keyhole (Kenney et al. 2021 Hojjatzadeh et al. 2019 Collins et al. 2016 Petrov et al. 1998 King et al. 2014). These elements have surface Rayleigh insta- bilities whose dynamics can result in spherical pockets of vapors of the constituent metal elements that behave as a gas, resulting in spherical pores, and which then condense on the surface of the pore, leading to a pore that is under vacuum. The thermophysical properties, including density, of these two types of spherical pores will differ. There is emerging work that is using high-energy X-rays to image experiments that emulate powder bed systems to study the origins of these defects (Menasche et al. 2021 Xavier et al. 2020 Jop et al. 2020), while T A B L E 1 Materials state variables linked to different physical processes related to AM Physical process Materials state variables Composition Phases (size, fraction) Grain size/ texture Defects (pores, cracks, lack of fusion, balling) Residual stress Average Local Heat input X X X Macroscopic heat transfer X X Materials thermodynamics X X Fluid dynamics within the molten pool X Fluid processes adjacent to the molten pool X X X Liquid/vapor interface processes X X X X Liquid/solid interface processes X X Solid-state phase transformations X X X Elastic and plastic deformation, gradients X X X X X Thermomechanical gyrations X X X Euclidean deposition (i.e., G-code) effects X X X A P R I L 2 0 2 2 • M A T E R I A L S E V A L U A T I O N 49