AluminumAluminum (Al) alloys are known for their high strengthStrength-to-weight ratio, good thermal conductivity, and cost-effectiveness, making them suitable for heat exchangerHeat exchangers applications. However, most commercial Al alloysAl alloys exhibit limited thermal stabilityThermal stability at elevated temperatures (>200 °C). The binary Al-Ca system has lower density than pure aluminumAluminum and shows promising thermal stabilityThermal stability at elevated temperatures. Here, we investigate the ternary Al-Ca-Ce alloy system, which has not been studied extensively, as a potential candidate for high-temperature applications. We characterize the phases present, and find Al4(Ca, Ce) and Al11(Ce, Ca)3 intermetallicIntermetallics compounds, with mutual solid solubility of Ce and Ca in their respective phases. Al4Ca is monoclinic at room temperature in binary Al-Ca and tetragonal at high temperatures; in Al-Ca-Ce, the Al4Ca phase is tetragonal at room temperature. We further investigate the influence of this mutual solubility on the coarsening behavior and thermal stabilityThermal stability of the ternary Al-Ca-Ce alloy system via ageing treatments at 250 and 400 °C. HardnessHardness measurementsMeasurements confirm that addition of Ce to a hypo eutecticEutectic Al-Ca alloy is not detrimental to the coarsening behavior of Al-6Ca (wt.

Directed Energy Deposition (DED) offers rapid large scale fabrication, but difficulty in delivering consistent microstructures and properties hinders the use of DED fabricated components in safety or performance critical applications. Variability stems from the complex thermal cycles generated by the toolpath used to print the required geometry. Several practical methods have become established in DED to regulate overheating, such as active cooling of the baseplate structure or the use of an infrared camera to inject interlayer pauses to ensure the top layer of the component cools to a set temperature, which have been shown to affect microstructure. However, no critical assessment has been performed as to how effective these controls are in promoting microstructural uniformity in the context of complex layer timing commonly generated by non-prismatic geometries. Here we show how controls influence the thermal field, phase transformations, and dynamic annealing of a low-temperature transformation steel using infrared imaging and operando neutron diffraction. Counterintuitively, common thermal homogenization process controls can reduce microstructural uniformity because these approaches stabilize peak temperature while overlooking temperatures near the solid-state phase transformation fronts. Instead, the cyclic reheating induces spatially-variant dynamically annealed regions which can be modulated via control parameters. We show that these controls have spatially linked effects centimeters away from the active weld, which implies that microstructure control must co-optimize thermal input across many subsequent layers. Our results demonstrate the pressing need for higher order controls that integrate predictive elements of simulation data to stabilize printed properties for future qualification of DED components.

A new, solute-lean Al-0.3Zr-0.2Ce-0.2Cu (wt.%) alloy is developed for additive manufacturing that overcomes the classical tradeoff between conductivity and creep resistance. The rapid-cooling-enabled supersaturation of Zr, and its uniform distribution in alpha-Al matrix, along with formation of submicron (Ce,Cu)-rich intermetallic particles on solidification lead to unusually high creep resistance at 200 degrees C. Near-zero secondary creep rates are achieved up to the alloy yield stress (YS) of 65 MPa at 200 degrees C in as-fabricated state. The Zr-solute-induced dislocation-climb suppression mechanism underlying this improvement also restricts dynamic recovery above YS, as noted from appreciable primary creep and its transitioning to near-zero secondary creep rates. A combination of relatively coarse, epitaxially-grown alpha-Al grains, low Zr concentration in alpha-Al, and the impurity-scavenging effect of Ce to purify alpha-Al matrix produces high electrical conductivity of similar to 48 %IACS. Aging precipitation of L1(2)-Al3Zr nanoprecipitates doubles the YS (to similar to 150 MPa) at room temperature and increases alloy conductivity to similar to 58 %IACS, but loss of solid-solution Zr out of alpha-Al matrix leads to activation of dislocation climb, degrading the creep properties as compared to the supersaturated Al-Zr solid solution in the as-fabricated state. Compared to L1(2)-Al3Zr nanoprecipitates, submicron (Ce,Cu)-rich particles formed on solidification are more effective at impeding dislocation climb, producing a threshold stress for dislocation creep of similar to 50 MPa at 200 degrees C. The new alloy design concepts, especially solute-induced dislocation-climb suppression for creep resistance, explored here may pave way for the design of new metallic alloys for thermal/electrical conductors and other high-temperature applications.

To explore the feasibility of using laser powder bed fusion systems to print bulk amorphous Al alloys, a single autogenous weld produced by laser remelting on a cast Al-5La-9Ni (at.%) alloy was studied for its microstructure and mechanical behavior. The solidification rates experienced by material within the welds were high enough to produce entirely amorphous regions within the welds. Welds were characterized using SEM, STEM, and APT and were found to contain Ni-rich amorphous clusters. Micropillar compression tests were used to assess mechanical properties of the welds and found that all of the amorphous regions exhibited yield strengths around 1 GPa. These results are discussed in the context of diffusivity of Ni and rare earth elements in liquid, glass forming ability, thermodynamic driving force for phase formation during solidification, free volume concentrations in bulk metallic glasses, and cluster-related softening.

It has been recently demonstrated that eutectic alloys processed by additive manufacturing have excellent high-temperature mechanical properties. We suggest that nickel-base eutectic alloys may enable new combinations of structural and functional properties. To this end, we investigate the processability, microstructure, and thermal stability of five, binary near-eutectic Ni-X (X = B, Ce, La, Y, and Zr) alloys processed via surface laser-remelting. The microstructure of all alloys contain a two-phase lamellar eutectic microstructure consisting of gamma-Ni and intermetallic phases; this microstructure is significantly finer (100-200 nm lamellar spacing) in the laser-remelted alloys than in the cast substrate (0.5-1.0 & micro;m lamellar spacing). The microhardness of the laser-remelted alloys (550-770 HV) is 35-50% higher than that of the cast alloys (370-570 HV) due to this finer eutectic spacing. An anomalous eutectic microstructure appears at the meltpool boundaries, containing globular and lamellar gamma-Ni phases. The alloys contain a high volume fraction (>50 vol%) of intermetallic phase which forms a continuous network, causing brittleness. Following laser-remelting trials, the alloys showed a high density of solid-state cracks, except for the Ni-Zr alloy which processed well. During thermal exposure at 700 and 900 degrees C for up to 500 h, the eutectic microstructure coarsens. Coarsening occurs heterogeneously and initiates at the meltpool boundaries. This process occurs more slowly in the Ni-Zr and Ni-Y alloys, and more rapidly in the remaining alloys, resulting in greater microhardness retention in the Ni-Zr and Ni-Y alloys following thermal exposure at 700 degrees C. Thus, among the five alloys, the Ni-Zr system exhibits a good combination of high-temperature mechanical properties and processability. We conclude with recommendations for future work on designing additively manufactured alloys based on these eutectic Ni systems.

A major challenge in simulating the thermal behavior in additive manufacturing processes is the disparate length and time scales between transport phenomena occurring in the melt pool and the component. A common simulation approach relies on spatial decomposition for parallel computing, but due to the nature of heat transfer in AM, where most of the computational expenditure is localized near the melt pool, the computational speedup from spatial parallelization saturates quickly. Therefore, additional parallelism by means of time-domain decomposition is needed to fully take advantage of high-performance computing (HPC) resources. This work introduces a time-parallel method to improve the computational scalability of additive manufacturing simulations on HPC systems, while maintaining high temporal resolution of heat transfer near the melt pool. The method, inspired by the nonlinear paraexp formalism, performs an iterative superposition of nonlinear solutions to the initial value problem, integrating the heat equation across overlapping time-parallel intervals. For a single layer of the NIST AMB2018-01 L7 benchmark problem, the method achieves a 38.51x speedup in wall-clock time with a maximum error in the global temperature solution of 0.99%. This reduces the total solution time from 196.72 min to 5.11 min on 128 nodes of the ORNL Frontier supercomputer. The tradeoff between accuracy and total wall-clock time is investigated and recommendations for time-parallel deployment for AM problems are made.

We investigated the high-temperature behavior of binary eutectic nickel-base alloys with low-solubility elements, towards developing alloys with new combinations of structural and functional (e.g. thermal or corrosion) properties. Based on thermodynamic screening, we cast binary near-eutectic Ni-B, Ni-Ca, Ni-Ce, Ni-La, Ni-Y, and Ni-Zr alloys and characterized their microstructure and high-temperature properties. All alloys (except Ni-Ca) contain a fine eutectic microstructure, containing submicron alternating lamellae of γ-Ni and continuous intermetallic phases. The eutectic microstructure did not significantly coarsen at 700°C (except for Ni-B), but measurably coarsened in all alloys at 900°C, most quickly in Ni-B, followed by Ni-Ce, Ni-La, Ni-Y, and Ni-Zr. Coarsening in these alloys occurs by fault migration; diffusion within the intermetallic, and its interfacial energy, likely influence coarsening kinetics. At room-temperature, all alloys possess negligible ductility due to the continuous, brittle intermetallic. At 700 and 900°C, the Ni-Zr alloy showed the best combination of strength and ductility. Oxidation experiments at 900°C on Ni-Zr and Ni-Ce revealed heavy internal oxidation of the continuous intermetallic phase. Overall, the Ni-Zr alloy showed good high-temperature coarsening resistance and strength, though ductility and oxidation resistance require improvement for use in structural applications. Possible routes for improving alloy properties via additive manufacturing are discussed

The high cycle fatigue behavior of laser powder bed fusion processed AlSi10Mg has been investigated at 350 degrees C (T/T-m similar to 0.7). The alloy exhibited a fatigue strength of 30 MPa defined by runout after 10(7) cycles at a conventional loading frequency of 20 Hz, corresponding to a notable fatigue strength to ultimate tensile strength ratio of 0.73. The surprising fatigue resistance was attributed to the strain-rate hardening effect at high fatigue loading frequency relative to tensile loading rates at 350 degrees C. The strain-rate hardening effect was validated by performing ultrasonic fatigue tests (20 kHz loading frequency) with three orders of magnitude higher strain-rates than those at conventional loading frequency. The higher strain-rates in ultrasonic fatigue increased the magnitude of strain-rate hardening resulting in longer AlSi10Mg fatigue lives compared to fatigue at conventional frequency, thus confirming the strain-rate hardening effect. The fatigue crack initiation mechanism was strain-rate dependent. Post-mortem microstructural examination revealed intergranular cavitation inside clusters of fine equiaxed grains. The cavities interlinked with each other to initiate near-surface fatigue cracks at conventional frequency. Cavitation occurred to a lesser extent at the ultrasonic frequency. As a result, fatigue cracks initiated at pre-existing processing defects near the surface in ultrasonic fatigue samples. This investigation underscores the role of fine grain clusters in promoting high-temperature fatigue crack initiation and indicates a possible trade-off between printability via grain refinement and high-temperature fatigue resistance of additively manufactured alloys.

Non-equilibrium phase formation and the interaction between the nucleation and solidification of competing phases are significant challenges in aluminum alloy design, as key properties such as ductility heavily depend on the grain morphologies and phases present in solidified castings. This manuscript expands upon existing multiphase cellular automata (CA) modeling work to predict hypereutectic Al–Fe alloy microstructures, considering primary and eutectic phase nucleation in both the bulk liquid and at existing solid–liquid interfaces, along with solute diffusion and phase-dependent growth morphologies. The 2D growth approximation for the primary intermetallic θ-Al13Fe4 phase is validated against in-situ radiography data from the literature, and sensitivity of the predicted multiphase grain structure of Al-2.5 wt% Fe to multiple model inputs governing nucleation density, undercooling, and eutectic growth is explored. The predicted primary FCC and eutectic area fractions are found to be particularly sensitive to two highly uncertain inputs — the bulk nucleation undercooling and the eutectic growth coefficient. For cooling rates representative of furnace cooling and rates representative of die casting conditions, the simulations using calibrated input parameters accurately predicted the spatial distribution of primary θ-Al13Fe4, primary FCC-Al, and eutectic phases along with the primary phase grain morphologies. The demonstrated ability to reproduce accurate phase selection and phase fractions for a range of solidification conditions will enable model application for aluminum alloy and casting design with extension to more complex alloys in the future. The simulation results also highlight areas of high experimental uncertainty where collecting additional data could reduce model uncertainty in future work.

As-solidified microstructures of near-eutectic alloys often contain multiple primary phases that are not expected from equilibrium phase diagrams. Such microstructures are caused by cooling-rate-dependent solidification pathways, a factor not captured by the Scheil-Gulliver model or variations thereof. Here, we present a model and algorithm that incorporate the critical nucleation undercooling for each solid phase into the Scheil-Gulliver model. We hypothesize that the non-equilibrium microstructure formation is primarily governed by a nucleation-competition mechanism. This mechanism accounts for both stable/metastable phase selection and primary-phase formation within eutectic regions driven by asymmetric nucleation barriers. The model is validated against a hypereutectic Al-Fe alloy, where it successfully reproduces the observed microstructural constituents, revealing the key dependencies of solidification microstructure on nucleation kinetics. Applicability to multicomponent systems is demonstrated through a hypereutectic Al-Fe-Si ternary alloy, where the model successfully predicts divorced eutectic microstructures and the associated oscillatory solidification pathways along univariant lines. The proposed framework establishes a nucleation-dependent computational approach for interpreting and predicting solidification microstructures.

This study examines the processing behavior, microstructure, surface roughness, and hardness properties of an aluminum alloy containing 8.2 Ce, 4.5 Ni, 0.5 Mn, and 0.7 Zr (wt%) fabricated using laser powder bed fusion. Sixty samples were produced across a range of laser powers, scan speeds, and hatch spacings to evaluate their effect on porosity, hardness, and microstructural features. Porosity was measured using X-ray computed tomography, while microstructure and surface roughness were characterized by scanning electron (SEM) and laser confocal microscopy. High dense and cracking-free Al-Ni-Ce alloy was successfully manufactured. Porosity showed a U-shaped dependence on energy input, increasing under both insufficient and excessive melting conditions. Hardness increased with cooling rate due to finer cellular structures and solute redistribution. A general statistical model was developed to capture the relationships between processing parameters and material response. Results identify a narrow processing window defined by laser powers between 350 and 370 W, scan speeds from 1400 to 1800 mm/s, and hatch distances between 0.14 and 0.18 mm. Within this window, porosity is minimized (below 0.01%) and hardness is maximized (up to 160 HV), demonstrating that careful control of these parameters enables dense, high strength aluminum components suitable for demanding structural applications.

The high solidification rates during additive manufacturing cause highly localized thermal and strain gradients. The effect of these gradients on the evolution of local orientation misorientations within a grain is not well understood. In this study, stainless steel 316H parts were fabricated via laser powder bed fusion using three different energy densities: 43, 71, and 135 J/mm3. Electron backscatter diffraction showed that the maximum misorientations of the grains can be up to 25 degrees along the build direction. Misorientation gradients (RMg) within grains are process-dependent and can change from 0.036 degrees/mu m to 0.015 degrees/mu m with increased volumetric energy densities. The characterized misorientation gradients are an indication of the level of dislocations and, to an extent, the plastic deformation resulting from the rapid solidification during laser powder bed fusion.

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. An extension to the time-temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time-temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process-microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process- microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

Cellular automata (CA) models of as-solidified grain structure, originally developed and applied to casting, have become a common means of predicting grain structure resulting from Additive Manufacturing (AM) processes. The majority of these models are based on the decentered octahedron approach, which attempts to correct for the effect of grid anisotropy on the prediction of competitive solidification of dendritic grains. However, AM solidification occurs under cooling rates (T) and thermal gradients (G) that are orders of magnitude larger than those encountered in casting, and no systematic investigation on the effect of the CA model cell size (dx) and time step (dt) on AM microstructure predictions has been performed. In this study, such an investigation is first performed via simulation of individual grains of various crystallographic orientations with a fixed, unidirectional G, showing that CA prediction of the steady-state undercooling matched the expected values based on the interfacial response function at small G and deviated from the expected values at large G. Simulation of competitive growth of multiple grains showed a weakening of the predicted texture as G and dx became large. Simulation of solidification under AM conditions, where G and T vary spatially across the melt pools, showed that not only does grain selection weaken and deviate from expectations at large dx, but grains with crystallographic ( 100 ) aligned with the grid directions are more adversely affected by the temperature field discontinuities than grains with other crystallographic orientations. Despite the fact that the exact grain competition results depended on dt, the overall texture development was notably less sensitive to dt than dx, provided that a reasonable value of dt is selected based on the ratio of dx to the maximum local solidification velocity in the simulation domain. Finally, from the directional solidification and AM simulation results, an analysis of computational cost compared to simulation resolution is performed based on an equation derived to quantify the relatively inaccuracy ingrain selection based on the model and temperature field inputs. From this analysis, it is concluded that there is a need for algorithmic improvements to improve CA grain competition accuracy for large G processing conditions as sufficiently small dx to resolve the necessary competition is intractable for many AM processing conditions.

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part's design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility "Peregrine v2023-10" public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure-property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Tensile creep response and cavitation damage evolution in an additively manufactured Al-7.5Ce-4.5Ni-0.4Mn-0.7Zr (wt%) alloy with peak-aging and overaging treatments were investigated in the 300-400 degrees C range. Microstructural heterogeneity and its response to heat treatment and subsequent creep deformation were studied to understand the interplay between cavity formation, creep lifetime and ductility. Increasing the applied stress activated the nucleation of more cavities, an experimental observation that is well described using the vacancy accumulation model. Cavities nucleated prematurely due to localized plasticity in the denuded zones that formed at/near melt-pool or grain boundaries. Microstructure/deformation heterogeneity with consequent evolution of stress triaxiality, especially at lower stresses, causes accelerated cavitation, thus producing low creep ductility (similar to 0.2-2.4 %), compared to (similar to 12-21 %) ductility of the alloy measured by regular tensile tests at equivalent temperatures. A constrained diffusional cavity growth mechanism with continuous cavity nucleation during creep is established as the dominant mechanism, implying that cavitation involves vacancy diffusion, yet its growth rate is dictated by the minimum creep rate. The ductility-limiting creep and cavitation mechanisms discussed here provide new insight into the creep behavior of 3D-printed metallic alloys.

There is a current need for new aluminum alloy design strategies to target applications requiring high strength and conductivity with reductions in mass. A new lightweight Al-2Ni-0.5Zr (wt. %) conductor alloy was fabricated using laser powder bed fusion. A design of experiments probed the alloy's solidification cracking susceptibility. It was observed that solidification cracking was generally reduced with fast scan speeds, above 1500 mm/s, and smaller hatch spacings. The different cooling rates throughout the melt pool produced a heterogeneous distribution of cellular and equiaxed Al3Ni precipitates in the as-printed alloy. Additionally, the rapid solidification characteristic of laser powder bed fusion created a super-saturated Zr solid solution. An aging heat treatment at 375 degrees C for 24 h imparted strengthening through the precipitation of L1(2)-Al3Zr nanoprecipitates, which counteracted the softening caused by the fragmentation and coarsening of Al3Ni precipitates. The yield strength increased from 138 MPa in the as-printed condition to 168 MPa after aging, while the ductility remained constant at similar to 21 %. The aging treatment simultaneously increased the electrical conductivity from 40.8 % IACS (International Annealed Copper Standard) to 53.5 % IACS. Modeling of the strengthening mechanisms and electrical conductivity contributions rationalized the simultaneous increase in strength and conductivity upon aging. The strengthening efficacy of the Al3Ni and L1(2)-Al3Zr precipitates, combined with the low Ni and Zr solubility in the FCC Al matrix, facilitated both high strength and electrical conductivity. Overall, the combination of strength and electrical conductivity positions this alloy as a suitable choice for additively manufactured lightweight conductors.

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. These problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.