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At least 253 records · Page 14

A scalable framework for efficient coupling of thermal and microstructural simulations in additive manufacturing

Predicting microstructure evolution in metal additive manufacturing (AM) is important for process optimization, but spatiotemporal scale disparities between thermal transport and microstructure evolution create significant challenges for efficient data transfer between simulation codes. To address this, we present Stork, a scalable framework for coupling thermal and microstructural simulations. Stork uses a sparse data representation to identify and store active solidification sub-volumes, enabling highly parallel quad-linear interpolation from coarse thermal grids to fine microstructure grids without large intermediate storage. We demonstrate the framework by coupling the semi-analytic heat transfer code 3DThesis with the time-parallel cellular automata code Toucan. This approach achieves over two orders of magnitude reduction in data generation time and file size compared to prior workflows. Numerical studies show that quad-linear interpolation preserves grain morphology and crystallographic texture in laser powder bed fusion (LPBF) simulations for coarsening ratios up to 16. Overall, Stork provides a scalable pathway for high-throughput, component-scale AM simulations on modern high-performance computing systems.

36 MATERIALS SCIENCE↗

Influence of carbon nanotubes on microstructure and corrosion performance of additively manufactured 316L stainless steel

For this study, laser powder bed fusion (LPBF) was performed on feedstock-modified 316L stainless steel powder with 1 and 2 vol% carbon nanotubes (CNT). The corrosion resistance was evaluated following cyclic potentiodynamic polarization tests conducted in 0.6 M NaCl at room temperature, 35 and 50 °C, and immersion tests in 6 % FeCl 3 . The CNT addition has increased the pitting potential and decreased number of pits formed during immersion in FeCl 3 solution, which could be attributed to Mn-Si-O nano inclusions refinement and segregation of chromium around the inclusions. The observed corrosion behavior was correlated with the altered microstructure due to CNT addition.

36 MATERIALS SCIENCE↗

Revealing mechanisms of processing defect mitigation in laser powder bed fusion via shaped beams using high-speed X-ray imaging

The laser powder bed fusion (LPBF) process utilizing a focused Gaussian-shaped beam faces challenges, including pore formation, melt pool fluctuation and liquid spattering. While beam shaping technology has been explored as a potential approach for defect mitigation, the beam-matter interaction dynamics during melting with shaped beams remain unclear. Here, we report the direct observation of ring-shaped beam-matter interaction dynamics, including pore formation, melt pool fluctuation and liquid spattering, and unveil defect mitigation mechanisms in ring-shaped beam laser powder bed fusion process. Here, we find that, by spatially manipulating incident laser rays, the ring-shaped beam controls keyhole morphology, thereby managing the distribution of the reflected rays. This manipulation can effectively eliminate the formation of an unstable cavity at the keyhole tip, stabilizing the keyhole and mitigating keyhole pores. This enhanced keyhole stability effectively reduces the melt pool fluctuation, the formation of liquid breakup induced spatters and liquid droplet colliding induced large spatters in the laser powder bed fusion process. Additionally, the high-energy forefront of the ring-shaped beam effectively melts the powder bed, reducing agglomeration liquid spatter in the laser powder bed fusion process. The discovered defect mitigation mechanisms may guide the design of beam shaping strategies for simultaneously increasing the quality and productivity of metal additive manufacturing.

Beam shaping↗

Sensitivity of additively manufactured AA7075 to variation in feedstock composition and print parameters

Here we developed a combined finite element and CALPHAD based model of the Laser Powder Bed Fusion (LPBF) process for AA7075 alloy that considers the effect of feedstock composition and print parameters. A single-pass of a laser on a layer of AA7075 alloy powder has been considered. Sensitivity of temperature evolution and melt pool geometry to variation in the stoichiometry of the feedstock powder and laser source characteristics have been studied. Our results indicate that deviation (up to 10%) of the feedstock composition from the AA7075 raises the maximum temperature and increases melt pool size. Excess Cu content shows the largest melt pool width and depth among all the cases. The peak temperature is higher than the standard feedstock composition in all cases, except when the Cu concentration is reduced. Increasing the scan power also results in a higher peak temperature and a larger melt pool size. Furthermore, the temperature's rise time increases by lowering the scan speed.

42 ENGINEERING↗

On the melt pool dynamic of voxel-controlled metal matrix composites via hybrid additive manufacturing: Laser powder bed fusion and ink-jetting

In this study, the effect of the addition of reinforcement nanoparticles to the 316L matrix by adopting ex-situ and in-situ method (drop on demand jetting) to produce 316L/Al 2 O 3 nanocomposite was investigated. In the ex-situ method, the Al 2 O 3 nanoparticles (NPs) were lightly mixed with 316L powder and processed by laser powder bed fusion. In the in-situ method, an ethanol-based ink containing Al 13 nanoclusters (NCs) was added to 316L powder and then processed by laser. Both ex-situ and in-situ method produced nanocomposites with Al-Si-Mn-O-enriched precipitations within the 316L matrix. The addition of NPs/NCs to the 316L matrix, altered the geometrical characteristic of the single-track melt pools. At the same laser power, with increasing the amount of Al 2 O 3 NPs and Al 13 NCs the melt pool deepened due to reduced thermal conductivity and prolonged liquid presence. Further, as a result, 316L/1 wt% Al 13 NCs deposited single track showed larger grains in comparison to 316L single track. At a high laser power of 150W, the Marangoni flow and the buoyancy force caused the nanoparticles to agglomerate and float to the top surface of tracks; therefore, the wt% fraction of precipitation was drastically reduced due to the loss of Al. The 316L/Al 2 O 3 NPs and 316L/Al 13 NCs exhibited the microhardness of 285 ± 13 HV and 293 ± 7 HV, respectively, higher than the deposited 316L single track, 265 ± 15 HV. Lastly, a hybrid LPBF+ink-jet printer was adopted to selectively change the composition of different zones by adding Al 13 NCs ink to 316L and producing a voxel-controlled metal matrix composite.

316L↗

The development of an augmented machine learning approach for the additive manufacturing of thermoelectric materials

Through the integration of machine learning (ML) techniques alongside additive manufacturing (AM) experimentation, we demonstrate an iterative process to rapidly predict laser-material interactions and melt pool geometries throughout the build parameter space for a bismuth telluride thermoelectric (TE) material. In doing so, we determined process parameters that created crack-free, highly dense (>99 %) n-type bismuth telluride (Bi 2 Te 2.7 Se 0.3 ) parts through laser powder bed fusion (LPBF). Furthermore, the ML-assisted understanding of the processing space allowed for the identification of build parameters that successfully yielded geometrically enhanced Bi 2 Te 2.7 Se 0.3 parts with reduced build times and no increase in experimental effort.

36 MATERIALS SCIENCE↗

Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared imaging thermal feature porosity probability maps

We report that local thermal history can significantly vary in parts during metal Additive Manufacturing (AM), leading to local defects. However, the sequential layer-by-layer nature of AM facilitates in-situ part voxelmetric observations that can be used to detect and correct these defects for part qualification and quality control. The challenge is to relate this local radiometric data with local defect information to estimate process error likelihood in future builds. This paper uses a Short-Wave Infrared (SWIR) camera to record the temperature history for parts manufactured with Laser Powder Bed Fusion (LPBF) processes. The porosity from a cylindrical specimen is measured by ex-situ micro-computed tomography (μCT). Specimen data from the SWIR camera, combined with the μCT data, are used to generate thermal feature-based porosity probability maps. The porosity predictions made by various SWIR thermal feature-porosity probability maps of a specimen with a complex geometry are scored against the true porosity obtained via μCT. The receiver operating characteristic curves constructed from the predictions for the complex sample demonstrate the porosity probability mapping methodology’s potential for in-situ based porosity detection.

36 MATERIALS SCIENCE↗

Binder-jetted AISI M2 tool steel during hot isostatic pressing: Densification and carbide transformation

Binder jetting (BJ) enables fabrication of complex components from high-alloy steels such as AISI M2; however, residual porosity after sintering limits mechanical performance. This study investigates the coupled effects of binder chemistry, sintering conditions, cooling rate, and subsequent hot isostatic pressing (HIP) on densification, microstructure, and mechanical response in binder-jetted M2 tool steel. HIP increased relative density from ∼93 to 95% to >99% and improved compressive strength by ∼40-70%. Densification was governed by initial pore morphology, where closed porosity was effectively eliminated, while interconnected porosity limited full consolidation. Microstructural analysis (XRD, EBSD, SEM) shows that HIP promotes dissolution of metastable carbides and redistribution of alloying elements (W, Mo, V), transforming heterogeneous carbide networks into finer and more uniformly distributed M 2 C, MC, and M 6 C phases through diffusion-assisted homogenization. Among the investigated conditions, the FluidFuse binder combined with sintering at 1270 °C for 60 min and furnace cooling produced the most balanced response, achieving ∼99.7% density, ∼855 HV hardness, ∼4130 MPa compressive strength, and ∼24% strain. In contrast, higher sintering temperatures promoted carbide coarsening, reducing ductility despite high density. HIP reduces microstructural heterogeneity and drives the system toward a near-equilibrium state with reduced sensitivity to prior processing history. A comparative assessment with conventional and additive manufacturing routes (LPBF, DED, EBM, FFF) shows that the BJ-HIP approach achieves competitive densification and mechanical performance. These findings provide a mechanistic basis for controlling densification and microstructure in high-alloy steels processed via BJAM.

AISI M2 tool steel↗

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗

Fracture characteristics and heat treatment of laser powder bed fusion additively manufactured GRCop-84 copper

Laser Powder Bed Fusion (LPBF) of Glenn Research Copper 84 (GRCop-84), a Cr 2 Nb (8 at. % Cr, 4 at. % Nb) precipitation hardened alloy, produces a fully dense high conductivity alloy with a yield strength of 500 MPa and ultimate tensile strength (UTS) of 740 MPa, superior to other competing copper alloys, and 20% elongation at fracture for material stressed perpendicular to the build direction. The high thermal stability of the Cr 2 Nb precipitate in the copper matrix reduces coarsening and maintains a 300 MPa yield, 520 MPa UTS and 26% elongation after a 900 °C, 5-h heat treatment, while a 3 h 450 °C heat treatment increases yield to 810 MPa, UTS to 970 MPa with 9% elongation at fracture, for samples stressed perpendicular to the build direction. Tensile strength anisotropy based on print direction was attributed to internal stress and columnar grain formation. Void nucleation during tensile fracture was initiated by brittle fracture of precipitate particles within the copper matrix. Fracture cusps contain matching precipitate fragment geometry on opposing sides located near the cusp center in at least 80% of fracture cusps. An optimal precipitate size of 100 nm is predicted for maximum tensile strength from precipitates on fracture surfaces, while tensile testing with varying heat treatments shows maximum strength with 100 nm and smaller precipitates. Cr2Nb precipitates are shown to transition between polycrystalline and monocrystalline structures at high temperature.

36 MATERIALS SCIENCE↗

Spall damage mechanisms in laser powder bed fabricated stainless steel 316L

This paper reports on spall damage mechanisms in laser powder bed fusion (LPBF) fabricated stainless steel 316L (SS316L) subjected to uniaxial, strain plate-impact loading and explores failure evolution with increasing impact velocity and peak pressure. Analysis of velocimetry profiles reveals a heterogeneous failure response with several different failure mechanisms activated during impact and resulting spall. The analysis is supported by optical microscopy and electron backscattered diffraction (EBSD) observation of soft recovered impacted samples, which show evidence of localized nano-twinning, twin growth, severe grain rotation, and grain refinement along the spall plane, in addition to pore nucleation, coalescence, and growth. Furthermore, the observed failure mechanisms, including crack formation and propagation along high angle grain boundaries (HAGBs), are not consistently indicative of ductile fracture typical of wrought stainless steel.

36 MATERIALS SCIENCE↗

Laser powder bed fusion of oxide dispersion-strengthened IN718 alloys: A complementary study on microstructure and mechanical properties

In this study, two new grades of oxide dispersion strengthened (ODS) Inconel 718 (IN718) alloys were designed by the thermochemical CALPHAD method and produced by laser powder bed fusion (LPBF) technique. Alloys designated as IN718-YF and IN718-YFH, that consist Y 2 O 3 –FeO and Y 2 O 3 –FeO–Hf, respectively, were fabricated with >99.9 % densification using optimized process parameters. CALPHAD calculations were highly consistent with experimental findings, highlighting the formation of Al-containing Y–Ti–O and Y–Hf–O nano-oxides in both alloy types. Texture analyzes revealed no significant texture development in as-built (AB) or heat-treated (HT) alloys. Heat treatment was applied at 1050 °C for 1 h to enhance nano-oxide density. Further, the nano-oxide number density remained similar in IN718-YF while it decreased in IN718-YFH alloy as a result of carbide formation after the heat treatment. Besides, formation of secondary γ' particles was observed in the IN718-YFH/HT alloy. Even though the yield strengths of IN718-YF and IN718-YFH alloys in both AB and HT conditions were similar, the ductility of IN718-YFH was ~50 % less in almost all conditions compared to the ductility of IN718-YF. This has been shown to be as a result of irregular shaped micron-sized Y-Hf-O oxides, martensite formation in AB condition, increased amount of carbides and existence of secondary γ' particles in HT condition in IN718-YFH. High density of stacking faults (SF) forming at the interface of the nano-oxides have been detected in IN718-YF alloys. Besides dislocation/nanoparticle interactions, SFs which are responsible for the delocalization of the deformation improve the ductility of IN718-YF alloys. Overall, high temperature mechanical tests exhibit that both alloys have higher strength with improved ductility compared to the standard IN718 alloys, indicating the contribution of the nano-oxides.

36 MATERIALS SCIENCE↗

Carbon nanotube (CNT) reinforced 316L stainless steel composites made by laser powder bed fusion: Microstructure and wear response

Carbon nanotube (CNT) reinforced 316L stainless steel (SS) composites were fabricated by laser powder bed fusion (LPBF) additive manufacturing (AM). This study focuses on microstructure evolution, hardness, and wear behavior. The wear behavior for AM 316L SS and 1 wt% CNT/316L SS was studied by a dry sliding test under normal loads of 10, 15, and 25 N. The addition of CNT to 316L SS led to the change of solidification mode from cellular/columnar to dendritic growth, producing grain refinement. Nanoscale dendrites were observed. Although TEM characterization confirmed the existence of CNT in cell interior, most CNT were damaged, resulting in carbon material segregation along cellular/dendritic boundaries. The wear rate was found dramatically decreased due to the improved hardness. Compared to the adhesive and abrasive wear in AM 316L SS, the wear mechanism of CNT/316L composite was adhesion and oxidative wear. Furthermore, enhanced cellular/dendritic boundary strengthening by carbon segregation was the main strengthening mechanism of CNT/316L composite.

36 MATERIALS SCIENCE↗

Controlling process instability for defect lean metal additive manufacturing

The process instabilities intrinsic to the localized laser-powder bed interaction cause the formation of various defects in laser powder bed fusion (LPBF) additive manufacturing process. Particularly, the stochastic formation of large spatters leads to unpredictable defects in the as-printed parts. Here we report the elimination of large spatters through controlling laser-powder bed interaction instabilities by using nanoparticles. The elimination of large spatters results in 3D printing of defect lean sample with good consistency and enhanced properties. We reveal that two mechanisms work synergistically to eliminate all types of large spatters: (1) nanoparticle-enabled control of molten pool fluctuation eliminates the liquid breakup induced large spatters; (2) nanoparticle-enabled control of the liquid droplet coalescence eliminates liquid droplet colliding induced large spatters. The nanoparticle-enabled simultaneous stabilization of molten pool fluctuation and prevention of liquid droplet coalescence discovered here provide a potential way to achieve defect lean metal additive manufacturing.

36 MATERIALS SCIENCE↗

Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing

Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting component fatigue life. However, some keyhole porosity formation mechanisms, e.g., keyhole fluctuation, collapse and bubble growth and shrinkage, remain unclear. Using synchrotron X-ray imaging we reveal keyhole and bubble behaviour, quantifying their formation dynamics. The findings support the hypotheses that: (i) keyhole porosity can initiate not only in unstable, but also in the transition keyhole regimes created by high laser power-velocity conditions, causing fast radial keyhole fluctuations (2.5-10 kHz); (ii) transition regime collapse tends to occur part way up the rear-wall; and (iii) immediately after keyhole collapse, bubbles undergo rapid growth due to pressure equilibration, then shrink due to metal-vapour condensation. Concurrent with condensation, hydrogen diffusion into the bubble slows the shrinkage and stabilises the bubble size. The keyhole fluctuation and bubble evolution mechanisms revealed here may guide the development of control systems for minimising porosity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Laser-based ultrasound interrogation of surface and sub-surface features in advanced manufacturing materials

Abstract Structures formed by advanced manufacturing methods increasingly require nondestructive characterization to enable efficient fabrication and to ensure performance targets are met. This is especially important for aerospace, military, and high precision applications. Surface acoustic waves (SAW) generated by laser-based ultrasound can detect surface and sub-surface defects relevant for a broad range of advanced manufacturing processes, including laser powder bed fusion (LPBF). In particular, an all-optical SAW generation and detection configuration can effectively interrogate laser melt lines. Here we report on scattered acoustic energy from melt lines, voids, and surface features. Sub-surface voids are also characterized using X-ray Computed Tomography (CT). High resolution CT results are presented and compared with SAW measurements. Finite difference simulations inform experimental measurements and analysis.

36 MATERIALS SCIENCE↗

Texture evolution during processing and post-processing of maraging steel fabricated by laser powder bed fusion

Abstract In this study, the evolution of solidification texture during LPBF of Ti-free grade 300 maraging steel, and its effect on texture development during subsequent post-fabrication heat treatments was characterized using Electron Backscatter Diffraction (EBSD). It was found that in the as-fabricated state, no texture was observed in the room temperature martensitic phase. However, the reconstructed parent austenite phase displayed a Cube texture with a minor fraction of Rotated Goss texture. During subsequent aging treatments involving two different routes, namely direct aging of the as-fabricated samples, and conventional solution treatment + aging of the as-fabricated samples, significant changes in the texture components of parent austenite were observed, whereas no changes in texture were observed in the room temperature martensitic phase. During direct aging, it was found that with an increase in the aging temperature up to 520 °C, the texture components of the parent austenite changed from Cube/Rotated Goss to Brass, whereas during the conventional solution treatment and aging cycle, interestingly a change in texture component to rotated copper was observed. The transitions in texture components have been discussed using the concepts of recrystallization and twinning in austenite during annealing and/or aging, and strain energy release maximization (SERM) theory. Furthermore, the importance of these preferred orientations on the mechanical properties was quantified using transformation potential diagrams.

36 MATERIALS SCIENCE↗

Property-Graded Stainless Steel 316L by Selective Laser Melting: Characterization & Design

Abstract The purpose of this research work is to characterize and inform the design of (mechanical) property-graded bulk structures made from a single metallic alloy via a laser powder bed fusion (LPBF) process, with an end goal of creating repeatable/reproducible functionally-graded additively manufactured (FGAM) parts. This paper specifically investigates the manufacture of stainless steel (SS) 316L structures via a pulsed selective laser melting (SLM) process, and the underlying causes of property variations (within a functionally-acceptable range) through various material characterization techniques. For this, a design of experiments spanning the volumetric energy density (VED) based process parameter design space was utilized to investigate the range of functionally-acceptable physical/mechanical properties achievable in SS 316L. Five sample conditions (made via different process parameter combinations) were down-selected for in-depth microstructure analysis and mechanical/physical property characterization; these were suitably selected to impart a wide and controllable property range (209–318 HV hardness, 90–99.9% relative density, and 154–211 GPa modulus). It was observed that property variations resulted from combinations of porosity types/amounts, martensitic phase fractions, and grain sizes. Based on these findings, property-graded standard test specimens were designed and manufactured for further investigation—tensile specimens having a monotonic hardness change along its gauge length, four-point bending specimens with varying elastic moduli as a function of the distance from the neutral axis, and Moore’s rotating beam fatigue specimens with moduli variations based on the distance from the center. Altogether, this work lays the foundation for understanding and designing the local and global mechanical performance of FGAM bulk structures.

Engineering↗