Laser Powder Bed Fusion Process Research Articles

Tensile and High Cycle Fatigue Performance at Room and Elevated Temperatures of Laser Powder Bed Fusion Manufactured Hastelloy X

The application potential of additive manufacturing nickel-based superalloys in aeroengines and gas turbines is extensive, and evaluating their mechanical properties is crucial for promoting the engineering application in load-bearing components. In this study, Hastelloy X alloy was prepared using the laser powder bed fusion process combined with solution heat treatment. The tensile and high cycle fatigue properties were experimentally investigated at room temperature as well as two typical elevated temperatures, 650 °C and 815 °C. It was found that, during elevated-temperature tensile deformation, the alloy exhibits significant serrated flow behavior, primarily observed during the initial stage of plastic deformation at 650 °C but occurring throughout the entire plastic deformation process at 815 °C. Notably, when deformation is small, sawtooth fluctuations are significantly higher at 815 °C compared to 650 °C. Irregular subsurface lack of fusion defects serve as primary sources for fatigue crack initiation in this alloy including both single-source and multi-source initiation mechanisms; moreover, oxidation on fracture surfaces is more prone to occur at elevated temperatures, particularly at 815 °C.

A thermodynamically consistent phase transformation model for multiphase alloys: application to Ti$$_6$$Al$$_4$$V in laser powder bed fusion processes

AbstractTitan aluminium alloys belong to the group of $$\alpha $$ α –$$\beta $$ β -alloys, which are used for many applications in industry due to their advantageous mechanical properties, e.g. for laser powder bed fusion (PBF-LB) processes. However, the composition of the crystal structure and the respective magnitude of the solid fraction highly influences the material properties of titan aluminium alloys. Specifically, the thermal history, i.e. the cooling rate, determines the phase composition and microstructure for example during heat treatment and PBF-LB processes. For that reason, the present work introduces a phase transformation framework based, amongst others, on energy densities and thermodynamically consistent evolution equations, which is able to capture the different material compositions resulting from cooling and heating rates. The evolution of the underlying phases is governed by a specifically designed dissipation function, the coefficients of which are determined by a parameter identification process based on available continuous cooling temperature (CCT) diagrams. In order to calibrate the model and its preparation for further applications such as the simulation of additive manufacturing processes, these CCT diagrams are computationally reconstructed. In contrast to empirical formulations, the developed thermodynamically consistent and physically sound model can straightforwardly be extended to further phase fractions and different materials. With this formulation, it is possible to predict not only the microstructure evolution during processes with high temperature gradients, as occurring in e.g. PBF-LB processes, but also the evolving strains during and at the end of the process.

Transfer learning-based quality monitoring of laser powder bed fusion across materials

Laser powder bed fusion (LPBF) is a promising additive manufacturing (AM) technique that has gained rapid growth. Despite the unique advantages such as producing complex-shaped metal parts, LPBF has been still slowed by the poor process repeatability and part consistency. In-situ monitoring methods combining sensing sensors and machine leaning (ML) tools have attracted much attention for defect detection and quality identification. However, the current ML algorithms usually rely on the availability of massive labeled datasets, and the trained model for monitoring a certain powder material cannot be directly applied to monitoring another material with different properties. Moreover, for a new material, it is time-consuming and expensive to collect the sufficient labeled data for building the quality monitoring model from scratch. To this end, motivated by transfer learning (TL), we propose a TL-based quality monitoring approach across two different materials in the LPBF process. Three different sensing datasets of layer-wise images of the solidified layer, photodiode signals, and acoustic emission signals are separately transferred from the 316L stainless steel to the TC4 titanium alloy. A convolutional neural network (CNN)-based quality monitoring model is first built by the sufficient source datasets from 316L stainless steel material. Then, the pre-trained CNN model is fine-tuned with a small amount of the target datasets for quality monitoring on TC4 titanium alloy material. Experimental results demonstrate the effectiveness of the proposed method for quality monitoring from one material to another with limited target datasets, with a classification accuracy above 92 % just with 5 % of target datasets on all three transferred datasets.

Relating laser powder bed fusion process parameters to (micro)structure and to soft magnetic behaviour in a Fe-based bulk metallic glass

This work aims to establish fundamental processing-(micro)structure-property links in a commercial Fe-based Kuamet6B2 bulk metallic glass (BMG) processed by laser powder bed fusion (LPBF). With that purpose, amorphous powders were processed using a pulsed-wave system and a simple meander strategy. The laser power, the scan speed, and the hatch distance were varied over wide intervals within the conduction regime. The processability window leading to samples with good dimensional accuracy and mechanical stability was determined. Within this window, the manufactured samples were crystalline/amorphous composites and the crystalline regions were formed by equiaxed ultrafine and nanograins with random orientations. Processing parameters yielding the densest prints caused severe crystallization while, conversely, parameter sets allowing the material to retain a high amorphous fraction led to significant lack-of-fusion defects and residual cracking along directions perpendicular to crystalline/amorphous interfaces. Comparatively, for a fixed hatch distance, the scanning speed had a stronger effect than the laser power in the resulting amorphous fraction due to its stronger influence on the melt pool size and, in turn, on the corresponding HAZ volume. The saturation magnetization and the coercive field were inversely related to the amorphous fraction. This work allows to derive fundamental guidelines for the successful additive manufacturing of soft magnetic Fe-based bulk metallic glasses (BMGs) by laser powder bed fusion (LPBF).

Tailoring Microstructure and Mechanical Properties of Additively Manufactured Inconel 625 by Remelting Strategy in Laser Powder Bed Fusion

Tailoring Microstructure and Mechanical Properties of Additively Manufactured Inconel 625 by Remelting Strategy in Laser Powder Bed Fusion

Influence of laser powder bed fusion parameters on microstructure and mechanical properties of Co–Cr dental alloy

This research investigates the impact of three process parameters of Laser Powder Bed Fusion (LPBF) - laser power, scanning speed, and base plate preheating temperature on the structure and mechanical properties of the EOS CoCr SP2 dental alloy. The LPBF process was used to fabricate dental Co–Cr alloy specimens for microstructural analysis and mechanical properties testing. Light and electron microscopy were used to determine microstructural parameters, including porosity, inclusions, and cracks. The material's chemical composition was analysed by EDS, while XRD and EBSD methods were used to determine the presence of microstructural phases and the crystallographic orientation of individual grains. The mechanical properties were evaluated through a static tensile test (Rp0.2, ε), a toughness test (KVa), and a three-point bending test to determine the flexural strength (Rms). In the microstructure, differences were observed that reflected statistically significant differences in mechanical properties (one-way analysis of variance (ANOVA) and Scheffé post hoc test (α = 0.05)) Using the base plate preheating temperature ϑp = 310 °C with a constant scanning speed v = 900 mm/s in combination with increasing laser power P from 160 W to 250 W the proportion of porosity decreased while the mechanical properties of toughness (KVa) and flexural strength (Rms) increase to maximum values.

Investigating post-processing impact on fatigue performance of LPBF Ti6Al4V with heat treatment, high pressure heat treatment, and dry electropolishing strategies

This study investigates the impact of post-processing techniques on the fatigue behaviour of specimens in Ti6Al4V made by laser powder bed fusion (LPBF) for relevant applications, such as motorsport. Despite the LPBF advantages in terms of complex design and weight reduction, challenges such as reduced fatigue performance persist. Therefore, the application of post-processing treatments can play a critical role. In addition to traditional sandblasting (SB), three post-processing conditions were investigated to enhance mechanical properties under quasi-static and fatigue loading conditions: heat treatment (HT) and the innovative High Pressure Heat Treatment (HPHT) along with dry electropolishing (EP) treatment. The results indicate that both the HT and HPHT treatments produced a macrostructure with equiaxial grains composed of fine α + β lamellae. Mechanical analyses demonstrated that the HPHT-SB-EP condition exhibits properties comparable to those of forged Ti6Al4V used in the automotive field, with a good balance between strength and ductility. The EP treatment effectively reduced surface roughness and inherent surface irregularities caused by the LPBF process. The best fatigue results were achieved with the HPHT-SB-EP condition, despite data scattering. An increase in fatigue resistance was observed by using SB at a higher pressure.

Effect of process parameters on the roughness and tensile behavior of parts manufactured by the metals LPBF process

AbstractThe laser powder bed fusion process for metals (LPBF‐M) results in the development of stochastic surface features that significantly influence the interactions between parts and their surrounding environment, as well as their mechanical properties. The process parameters influence the surface quality, which is quantified by the surface roughness. Therefore, customizing the surface roughness during the build process can significantly contribute to obtaining ready‐to‐use parts, reducing the need for extensive surface posttreatments. This paper utilizes theoretical estimations of melt pool depth under iso‐linear energy density, iso‐power, and iso‐temperature manufacturing process parameter conditions. These estimations are then compared with experimental evaluations of surface roughness and tensile strength in upright‐built specimens to extract the trends in terms of the input energy versus roughness, and the input energy versus tensile behavior. The results show that iso‐energy values yield similar roughnesses due to the consistent expected melt pool depth. Moreover, an increase in melt pool depth generates higher surface roughness, while smaller melt pool dimensions result in improved roughness. Additionally, a comparison between the melt pool size and tensile test performance reveals a detrimental impact on the tensile strength for specimens estimated to have smaller melt pool depths.

A comparative analysis of compressive and wear failure of laser-powder bed fused Stainless Steel 316L produced with different hatch spacing in stripe and contour patterns

The selection of hatch spacing is crucial in additive manufacturing processes to produce a defect free Stainless Steel 316L (SS) components, especially in laser powder bed fusion (LPBF) process. Improper selection of hatch spacing could lead to various failure regimes (like vertical cracking, porosity, and un-melted particles) in Stainless Steel 316L (SS) component produced through laser powder bed fusion (LPBF). Further, the failure regimes have a direct impact on the hardness, compression strength, friction, and wear properties of LPBF SS components. The present study has taken substantial efforts to analyse the impact of various hatch spacing (0.08 mm, 0.10 mm. and 0.12 mm) in stripe and contour patterns, in terms of morphology, mechanical, and tribological properties of LPBF SS components. Also, the present study elucidates how variations in hatch spacing influences the features like particle fusion, crack formation, density, hardness, surface roughness, compression, and wear properties. The stripe pattern with low hatch spacing of 0.08 mm showed better particle fusion and high surface roughness; whereas the high hatch spacing has produced voids, un-melted powder particles, and cracks in the stripe and contour pattern. High densities and hardness values were attributed to the stripe patterns with more effective melting and fusing of powder particles. XRD analysis revealed the stable phase compositions across various hatch spacing with a predominant FCC crystal structure. Residual stress distribution was significantly influenced by the hatch spacing for both stripe and contour patterns. Importantly, the low hatch space leads has promoted the tensile residual stress formation and vice versa for the higher hatch spacing. Stripe patterns showed higher compression strengths with buckling and shear mode as a compression failure. The stripe pattern demonstrated a low specific wear rate (SWR) and coefficient of friction (COF) compared to the contour pattern, with respect to the various hatch spacing. Furthermore, the simulated body fluid (SBF) lubrication regime played a significant role in reducing the COF. Patches, groves, furrows, and craters demonstrated the abrasive and adhesive failure for both stripe and contour pattern, which is further detailed in the article.

Laser additive manufacturing of TiB2-modified Cu15Ni8Sn/GH3230 heterogeneous materials: Processability, interfacial microstructure and mechanical performance

Cu/Ni heterogeneous materials integrate excellent thermal conductivity and high-temperature mechanical properties, enabling them to be widely used in the aerospace domain. Differences in the thermal and physical properties of the Cu and Ni materials, however, make them difficult to be processed using the laser powder bed fusion (LPBF) additive manufacturing process. This study systematically examines the effects of various LPBF process parameters on microstructure, element diffusion, bonding strength and microhardness at the Cu/Ni interface, as well as investigating the mechanisms of defect formation within Cu/Ni heterogeneous materials. The results indicate that a reasonable control of laser energy input (< 100 J/mm3) facilitates the Cu/Ni components through strong interfacial metallurgical bonding without pore defect formation. Compared to single-material Cu alloy, the ultimate tensile strength (UTS) of the horizontally bonded Cu/Ni specimen increased by 55.25%, without significant reductions in elongation. The vertically bonded Cu/Ni tensile specimen fractured in the middle of the Cu region rather than the interfacial region, indicating superb interfacial bonding strength. Another advantage lies in the enhancement of thermophysical properties, with a 109.5% increase in thermal conductivity achieved in the LPBF-fabricated Cu/Ni heterogeneous materials compared to the single-material Ni alloy. Quasi-static compression experiments indicated that the Cu/Ni lattice structure could absorb more energy when compressed parallel to the build direction (BD), compared to being perpendicular to the BD. This study provides guidance for the design and manufacture of high-performance Cu/Ni heterogeneous components via LPBF.

Designing materials by laser powder bed fusion with machine learning-driven bi-objective optimization

To exploit the full industrial potential of additive manufacturing (AM) beyond prototyping, the resource-consuming identification of the optimal processing conditions needs to be minimized. This task becomes more challenging when multiple properties of the part shall be simultaneously optimized. We utilize ML methods in a case study on LPBF of a Zr-based glass-forming alloy. Our experiments show that processing parameters affect density and amorphicity opposingly, demonstrating the efficacy of our ML-based approach. We employ multi-objective optimization using Gaussian Process Regression to model and predict target properties and their uncertainties of parts fabricated by laser powder bed fusion (LPBF) – a widely used metal AM technology. With density and amorphicity as target parameters, we optimize models using the Pareto front facilitated by the Non-Dominated Sorting Genetic Algorithm II. Despite deviations in the amorphicity data, we demonstrate this method to identify the high-performance region of the process parameters and its ability to be iteratively enhanced with additional experimental data. This bi-objective optimization approach provides a robust toolset for navigating LPBF processing. It can be easily extended to a larger set of target properties and transferred to further AM technologies.

The influence mechanisms of re-fused scanning on the surface roughness, microstructural evolution and mechanical properties of laser powder bed fusion processed AlMgScZr alloy

Laser powder bed fusion (LPBF) stands out as the foremost method for achieving intricate structure with superior design flexibility among additive manufacturing technologies. Within the LPBF process, surface roughness serves as a critical metric governing both fabrication precision and build quality. This study delves into the evolution of the top and side surface roughness as re-fused scanning times increase in LPBF-fabricated AlMgScZr alloy. Concurrently, the investigation evaluates alterations in microstructural characteristics and mechanical properties. Various characterization techniques, including confocal laser scanning microscope, scanning electron microscope, X-ray diffraction, electron backscatter diffraction, as well as tensile and microhardness tests, are employed. The findings concerning the top surface reveal that the initial application of re-fused scanning contributes to enhanced surface roughness. This improvement stems from refined grain structures and induced lattice distortions, facilitated by rapid heat dissipation and thermal recycling within the solidified layer. Consequently, microhardness increases. However, introducing the subsequent re-fused scanning exacerbates surface roughness and instigates Marongoni flow instability, magnesium depletion, and alterations in lattice structures. Moreover, with increasing the re-fused times, there is a noticeable enhancement in preferential crystallite growth orientation along the (200)α-Al crystal plane. Regarding the side surface, escalating re-fused times correlate with deteriorating roughness and alterations in molten pool shape and size, attributable to successive energy input. Despite these surface variations, minimal differences are observed in yield strength, tensile strength, and elongation. In essence, this research offers valuable insights into selecting optimal scanning methodologies during the LPBF process, thus guiding improvements in fabrication precision and component quality.

Data-driven Approach to Explore the Contribution of Process Parameters for Laser Powder Bed Fusion of a Ti-6Al-4V Alloy

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

Dependences of the defect, microstructure and properties of 15-5 PH martensitic stainless steel on the laser powder bed fusion process parameters

15-5 PH martensitic stainless steel is widely utilized in the marine, chemical, and aerospace industries owing to its high strength and corrosion resistance properties. The highly tailored samples can be produced via laser powder bed fusion technology, however it is still unknown how to optimize process parameter windows and conduct mechanism research for 15-5 PH steel forming. The results show that fusion defects are mostly concentrated in the region with low laser power (P) of 200 W, and there is no obvious distribution pattern in the pore and porosity defects. Excellent dense samples can be formed mainly at medium P of 260 W and medium scanning speed (V) of 1200 mm/s. The proportion of body center cubic structure reaches 91.7 % for the hatch space (H) of 0.06 mm, and a heterogeneous layered structure with alternating fine and coarse grain layers is formed. The sample exhibits high strength and excellent plasticity, where the ultimate tensile strength, yield strength, elongation to fracture, impact toughness, and hardness are 1161 MPa, 825 MPa, 17.5 %, 122.5 J/cm2, and 34.6 HRC, respectively. The excellent comprehensive property is due to fine-grained strengthening, dislocation strengthening, solid solution strengthening and intrinsic factors/oxide dispersion strengthening.

Laser Powder Bed Fusion Processing of Low Cost CoCrFeNiMoxNby High Entropy Alloys with Promising High-Temperature Properties via In Situ Alloying Commercial Powders

A blend of only commercial powders, including Ni625, CoCrF75, and 316L, were used as the raw material for fabricating non-equiatomic CoCrFeNiMoxNby high entropy alloys (HEAs) through laser powder bed fusion (PBF-LB/M) via in situ alloying, instead of using pure elemental powders, thus reducing the raw materials cost. The rapid cooling inherent in the PBF-LB/M process facilitated the dissolution of Mo and Nb, resulting in a single FCC phase characterized by high relative densities. High-temperature tensile tests were conducted at room temperature, 700 °C, 800 °C, and 900 °C, revealing mechanical properties that surpassed those reported in existing HEA literature. The remarkable strength of the HEAs developed in this study primarily stemmed from the incorporation of Mo and Nb, leading to the precipitation of Mo and Nb-rich lave phases at elevated temperatures. While constraining elongation when confined to grain boundaries, these precipitates enhanced strength without compromising elongation when distributed throughout the matrix. This work is a feasibility study to explore the usage of commodity compositions from the market to develop HEAs using PBF-LB/M, which opens the possibility of using scraps to further the development of new materials. Consequently, this study presents a rapid and cost-effective approach for HEA development, improving efficiency and sidestepping the direct utilization of critical raw metals for sustainable manufacturing. Moreover, this work also underscores the outstanding mechanical performance of these HEAs at high temperatures, paving the way for the design of innovative alloys for future high-temperature applications.

A Novel Physics-Based Model for Predicting Melt Pool Dimensions in Laser Powder Bed Fusion Process

Abstract This paper employed a scaling analysis to represent the processing parameters, affecting the melting process in the dimensionless numbers, identify the relationships of these dimensionless numbers, and develop semi-empirical correlations to predict the width and depth of the melt pool. To develop the correlations, Ti-6Al-4V powder was used to print 38 tracks at various processing conditions. The correlations were then fit into this experimental data using python code to find the constants of the correlations. The correlations were then used to predict the depth and width of the melt pools. It was found that the mean discrepancy between the predicted melt pool dimensions and the experiment is 7%. To evaluate the accuracy of the correlation in predicting the melt pool dimensions of the materials never used during the development of the correlations, the melt pool depth of some tracks made out of stainless steel 316L printed at various conditions was predicted using the model, and it was found that the mean discrepancy between the predicted melt pool depth and experiment is 11%.

Reduction of oxygen content in laser powder bed fusion process atmosphere – Effects on stochastic defect formation and mechanical properties

Stochastic defects in materials manufactured via laser powder bed fusion (LPBF) can severely compromise mechanical performance and are challenging to predict and detect, thus motivating the development of defect mitigation strategies. Particle oxidation is a factor well-known to generate defects by disturbing melt pool dynamics. If the particles are spatters, additional disturbances increase the likelihood of defect formation. In this study, restricting oxygen content in the process atmosphere to 50 ppm is investigated to minimize stochastic spatter-induced defects and improve the mechanical properties of Hastelloy X. Specimens were manufactured under this condition at two nominal layer thicknesses, analyzed for internal defects, and mechanically tested. Contrary to expectations, reducing the oxygen content did not prevent spatter-induced defect formation; rather, it could exacerbate the formation of more numerous and larger defects. Nevertheless, this tighter control of the process atmosphere led to significant microstructural refinement, which, when combined with sparse defects, resulted in improved fatigue performance. Despite the inherent ductility of Hastelloy X, the presence of abundant defects significantly larger than the microstructural characteristic size proved detrimental to fatigue performance. Notably, the occurrence of defects exhibited considerable variation across the build area, contributing to scatter in fatigue data. However, quantitative analysis of in-situ monitoring data enabled prediction of variability in defect content and mechanical performance.

L-PBF AM process failures causal chain: an FMEA-based monitoring approach for process control

ABSTRACT The laser powder bed fusion (L-PBF) additive manufacturing process offers many advantages. However, its industrial integration still needs to be improved due to the certification constraints of the produced parts. Thus, this paper proposes a phenomenological causal chain of process failures to ensure the control of the L-PBF process and further certify the quality of the parts produced. Consequences of unsuitable thermal regimes are analysed using a failure mode and effects analysis (FMEA) approach, allowing a more global understanding of all the causal chain-related data. The proposed approach is based on standard acquisition equipment available on industrial machines and proves relevant for identifying process failures. Experimental validation of the proposed monitoring method is implemented on a use case using dedicated software. Finally, it is shown that the method is relevant in this confrontation and compatible with the time scale of the process for future NC integration and real-time monitoring.

Mechanical and thermal properties of Gyroid-based W[sbnd]Cu composites produced via laser powder bed fusion assisted by infiltration

Plasma-facing components for thermonuclear fusion reactors require the introduction of new materials due to outstanding demands in mechanical, thermal, and thermal cycle fatigue resistivity properties. One promising solution is the WCu composite material or multimaterial that combines the properties of both components. In the present work, WCu samples were obtained by laser powder bed fusion (LPBF) consolidation of a tungsten porous matrix followed by copper infiltration. A design of structures with ordered porosity was achieved by translation of skeletal gyroid unit cell (triply periodic minimal surface). A relative density of 96.7% was achieved for solid pure tungsten samples with optimized LPBF process conditions. As-built W gyroid samples had a 15–20% ultimate compressive strength (UCS) of the solid sample. After the infiltration with copper, the ductility of WCu composites increased drastically, i.e. the samples did not fracture at a strain of 35%. It was found that UCS, yield strength (YS), and thermal diffusivity were sensitive to gyroid unit cell size. The sample with the smallest cell size of 2 mm had superior YS of 626 MPa and thermal diffusivity of 76.4 mm2/s. The obtained results will shed light on the possibilities for further development of WCu manufacturing technology based on the LPBF method combined with subsequent infiltration.

Thermal stability of refined Al6(Fe, Mn) phase formed in laser powder bed fusion process

The addition of Mn in Al–Fe alloys stabilizes the Al6Fe metastable phase (orthorhombic structure, oC28) owing to the partial occupation of Fe sublattice sites by Mn atoms (formation of Al6(Fe, Mn) phase), thereby achieving superior high-temperature strength of Al–Fe–Mn ternary alloys that are manufactured via laser powder bed fusion (L-PBF) process. This study aimed to fundamentally understand the thermal stability of the refined Al6(Fe, Mn) phase formed in the L-PBF fabricated Al–2.5%Fe–2%Mn alloy in terms of a thermodynamic approach and the kinetics of morphological changes in the Al6(Fe, Mn) phase at elevated temperatures ranging from 200 to 500 ℃. The L-PBF processed samples showed a high hardness of approximately 125 HV due to the formation of numerous dispersoids of the Al6(Fe, Mn) phase with sizes of several tens of nanometers in the α-Al matrix containing concentrated solute elements of Fe and Mn. The hardness and microstructure were almost unchanged even after exposure to a high temperature of 200 ℃ for an extended period of 1000 h. Upon exposure to 300 ℃, nucleation and growth of the Al6(Fe, Mn) phase occurred locally, particularly at grain boundaries in the α-Al matrix. Such a local growth contributed to a reduction in hardness upon thermal exposure. Simultaneously, numerous nanoscale precipitates were formed in the α-Al matrix, resulting in a suppressed reduction in hardness. Contrary to the result of the thermodynamic calculations, the θ-Al13Fe4 phase was scarcely found even after long-term exposure to 500 ℃. The θ-phase formation was accompanied by the dissolution of the refined Al6Fe metastable phase for strengthening, which significantly reduced the hardness during thermal exposure. The suppressed θ-phase formation could be associated with the thermodynamically stable Al6(Fe, Mn) phase developed during the L-PBF process, which predominantly contributed to the high microstructural stability of the L-PBF fabricated Al–Fe–Mn alloy at elevated temperatures.