Metal additive manufacturing (AM) presents advantages such as increased complexity for a lower part cost and part consolidation compared to traditional manufacturing. The multiscale, multiphase AM processes have been shown to produce parts with non-homogeneous microstructures, leading to variability in the mechanical properties based on complex process–structure–property (p-s-p) relationships. However, the wide range of processing parameters in additive machines presents a challenge in solely experimentally understanding these relationships and calls for the use of digital twins that allow to survey a larger set of parameters using physics-driven methods. Even though physics-driven methods advance the understanding of the p-s-p relationships, they still face challenges of high computing cost and the need for calibration of input parameters. Therefore, data-driven methods have emerged as a new paradigm in the exploration of the p-s-p relationships in metal AM. Data-driven methods are capable of predicting complex phenomena without the need for traditional calibration but also present drawbacks of lack of interpretability and complicated validation. This review article presents a collection of physics- and data-driven methods and examples of their application for understanding the linkages in the p-s-p relationships (in any of the links) in widely used metal AM techniques. The review also contains a discussion of the advantages and disadvantages of the use of each type of model, as well as a vision for the future role of both physics-driven and data-driven models in metal AM.

The microstructure of additively manufactured (AM) metals has been shown to be heterogeneous and spatially non-uniform when compared to conventionally manufactured metals. Consequently, the effective mechanical properties of AM-metal parts are expected to vary both within and among builds. Here, we present a framework for simulating process–(micro)structure–property relationships of AM metals produced via direct laser deposition (DLD). The framework predicts grain nucleation and competitive growth as a function of thermal history for a multi-pass, multi-layer DLD process. The resulting three-dimensional microstructure is automatically sub-sampled to perform virtual mechanical testing throughout the build domain using a parallelized elasto-viscoplastic fast Fourier transform code, accounting for grain-boundary strengthening. The effective stress–strain response of each sub-sampled volume is automatically analyzed to extract effective mechanical properties, which are used to generate property maps showing the spatial variability of effective mechanical properties throughout the simulated build volume. As a demonstration, the framework is applied to different DLD stainless steel 316L build volumes having different process-induced microstructures. The multi-physics framework and property maps could provide a path toward qualification of AM-metal parts.

We use high-speed video imaging to investigate vapor explosions during the impact of a molten Field's metal drop onto a pool of water. These explosions occur for temperatures above the Leidenfrost temperature and are observed to occur in up to three stages as the metal temperature is increased, with each explosion being more powerful that the preceding one. The Field's metal drop breaks up into numerous microbeads with an exponential size distribution, in contrast to tin droplets where the vapor explosion deforms the metal to form porous solid structures. We compare the characteristic bead size to the wavelength of the fastest growing mode of the Rayleigh-Taylor instability.

The ability to manufacture complex designs from multiple materials has long been a key objective for applications operating in extreme environments. Multi-material (MM) additive manufacturing (MMAM) has significantly enhanced the functionality of additive manufacturing (AM) by enabling the integration of dissimilar alloys while leveraging the inherent advantages of AM, including design flexibility, reduced material waste, and rapid production, with the ability to tailor mechanical properties through spatial material distribution and local processing conditions. This process unlocks unprecedented opportunities across industries such as aerospace, automotive, biomedical, energy, and nuclear sectors. This article provides a comprehensive review of the state-of-the-art in MMAM, focusing on the manufacturing processes, molten pool formation, alloy compatibility, and bimetallic interface characteristics—including microstructural and mechanical properties—as well as modeling and simulation approaches for performance prediction and optimization, with developments tracked from 2013 to 2024. This review article predominantly focuses on: (i) MM-laser powder bed fusion, (ii) MM-directed energy deposition, and (iii) MM-wire-arc AM by detailing the mechanisms of molten pool formation at the interface and dissimilar alloy material compatibilities. Subsequently, the article provides an in-depth analysis of the meso- and micro-structural characteristics at the interface in bimetallic structures across widely employed MMAM alloys. The mechanics of MMs under various mechanical properties are presented, including microhardness/micro-indentation, tensile, flexural, compression, and fatigue strength, which are critical for MMAM applications in extreme conditions. In addition, current modeling and simulation approaches for MMAM are discussed with respect to the challenges and opportunities to increase MMAM adoption. The article concludes with a future roadmap for advancing MMAM by overcoming feedstock and build material cross-contamination, monitoring the in situ process, standardizing MM testing, and further developing thermo-mechanical modeling, specifically, for MMAM.

Ultra high-speed imaging is used to investigate the vapor explosion when a drop impacts onto a high-temperature pool. The two liquids are immiscible, a low boiling-temperature perfluorohexane drop, at room temperature, which impacts a high boiling-temperature soybean-oil pool, which is heated well above the boiling temperature of the drop. We observe different regimes: weak and strong nucleate boiling, film boiling or Leidenfrost regime and entrainment followed by vapor explosion. The vapor explosions were seen to depend on the formation of a rotational flow at the edge of the impact crater, near the pool surface, which resembles a vortex ring. This rotational motion entrains a thin sheet of the drop liquid, to become surrounded by the oil. In that region, the vapor explosion starts at a point after which it propagates azimuthally along the entire periphery at high speed