Directed Energy Deposition Additive Manufacturing Research Articles

Laser Directed Energy Deposition Additive Manufacturing of Al7075 alloy: Process Development, Microstructure, and Porosity

7xxx series aluminum alloys are priority materials adopted in aerospace because of their lightweight property and excellent mechanical performance. The combination of lightweight material and additive manufacturing techniques can significantly promote lightweight design in many industries. This study developed the optimal process for manufacturing Al7075 alloy by laser-aided directed energy deposition and revealed the material properties of the as-deposited Al7075 specimens. Firstly, single-track experiments were conducted by varying laser power, printing speed, and powder delivery rate in broad ranges. Results indicated that the printing speed and powder delivery rate impact the surface finish and shape of single-track beads considerably. Block specimens printed with the optimal parameters selected from the single-track experiments present crack-free quality and have a high relative density of up to 99.89%. Second phases with rich Cu, Mg, and Zn elements along the inter-dendritic regions and grain boundaries were observed from the microstructure inspection. The composition of zinc in the deposited samples is lower than usual, which leads to a relatively low microhardness.

Grain refinement of Inconel 625 during wire-based directed energy deposition additive manufacturing by in-situ added TiB2 particles: Process development, microstructure evolution and mechanical characterization

In this study, a novel method for enhancing the quality of components fabricated by wire and arc additive manufacturing (WAAM) was developed. This approach employs an innovative mechanism featuring an actuator that dispenses a solution containing refinement particles (TiB2 inoculants), in conjunction with a soldering flux that vaporizes prior to reaching the electric arc. This leaves the particles to adhere to the welding wire or be carried by the shielding gas. By implementing this device, TiB2 particles were successfully incorporated into the molten pool during the WAAM process of Inconel 625 at levels of 0.31 and 0.56 wt%. Microstructural analysis reveals a significant reduction in the size of interdendritic segregation regions when TiB2 particles are introduced. Electron backscatter diffraction analysis further reveals the transformation of columnar grains into equiaxed grains. The average grain area decreased from 1823 μm2 in the as-built sample to 583 μm2 in the sample with a TiB2 content of 0.56 wt%. In addition, an improvement in the Inconel 625 fabricated by WAAM mechanical strength was observed due to the use of TiB2 inoculants, which was primarily attributed to the effect of the grain size refinement.

Application of Linear Mixed-Effects Model, Principal Component Analysis, and Clustering to Direct Energy Deposition Fabricated Parts Using FEM Simulation Data.

The purpose of this study is to investigate the effects of toolpath patterns, geometry types, and layering effects on the mechanical properties of parts manufactured by direct energy deposition (DED) additive manufacturing using data analysis and machine learning methods. A total of twelve case studies were conducted, involving four distinct geometries, each paired with three different toolpath patterns based on finite element method (FEM) simulations. These simulations focused on residual stresses, strains, and maximum principal stresses at various nodes. A comprehensive analysis was performed using a linear mixed-effects (LME) model, principal component analysis (PCA), and self-organizing map (SOM) clustering. The LME model quantified the contributions of geometry, toolpath, and layer number to mechanical properties, while PCA identified key variables with high variance. SOM clustering was used to classify the data, revealing patterns related to stress and strain distributions across different geometries and toolpaths. In conclusion, LME, PCA, and SOM offer valuable insights into the final mechanical properties of DED-fabricated parts.

Controlling microstructure and B2 ordering kinetics in Fe–Al system through additive manufacturing

Multi-material fabrication between steel and aluminum is challenging because of the formation of several intermetallic phases. Embrittling B2 ordered intermetallics form in the steel rich side and are stable till about 60% of Al dilution in steel. In this work by using multi-length scale characterization coupled with integrated computational process and thermokinetic modeling, we show that the ordered B2 intermetallics in the steel rich side of the Fe–Al system forms via a nucleation and growth mechanism. The extent of B2 ordered intermetallics can be controlled by modifying the directed energy deposition-additive manufacturing (DED-AM) process parameters. Our findings lay the foundation for enabling fabrication of crack-free functionally graded compositions between the two alloys.

Process mapping and anomaly detection in laser wire directed energy deposition additive manufacturing using in-situ imaging and process-aware machine learning

This work concerns the laser wire directed energy deposition (LW-DED) additive manufacturing process. The objectives were two-fold: (1) process mapping – demarcating the process states as a function of the processing parameters; and (2) process monitoring – detecting process anomalies (instabilities) using data acquired from an in-situ meltpool imaging sensor. The LW-DED process enables high-throughput, near-net shape manufacturing. Without rigorous parameter control, however, LW-DED often introduces defects due to stochastic process drifts. To enhance scalability and reliability, it is essential to understand how LW-DED parameters affect processing regimes, and detect deleterious process drifts. In this work, single-track experiments were conducted over 128 combinations of laser power, scanning velocity, and linear mass density. Four process states were observed via high-speed imaging and delineated as stable, dripping, stubbing, and incomplete melting regimes. Physically intuitive meltpool features were used to train simple machine learning models for classifying the process state into one of the four regimes. The approach was benchmarked against computationally intense, black-box deep machine learning models that directly use as-received meltpool images. Using only six intuitive meltpool morphology and intensity signatures, the approach classified the LW-DED process state with statistical fidelity approaching 90 % (F1-score) compared to F1-score 87 % for deep learning models.

A membrane finite element for fast simulation of overlapping beads geometry during direct energy deposition additive manufacturing

A membrane finite element for fast simulation of overlapping beads geometry during direct energy deposition additive manufacturing

Cost Modelling for Powder Bed Fusion and Directed Energy Deposition Additive Manufacturing

Cost Modelling for Powder Bed Fusion and Directed Energy Deposition Additive Manufacturing

Dynamics of pore formation and evolution during multi-layer directed energy deposition additive manufacturing via in-situ synchrotron X-ray imaging: A case study on high-entropy Cantor alloy

Blown-powder directed energy deposition (DED) additive manufacturing is impeded for novel alloys processing by perceivable and detrimental porosity. During multi-layer depositions, however, mechanisms of pore formation and evolution remain elusive for developing pore mitigation strategies. Here, conduction-mode multi-layer DED process of an exemplary high-entropy Cantor alloy have been investigated in-situ by high-energy high-speed synchrotron X-ray imaging. Three new pore formation mechanisms are unveiled when depositing first layer and successive layers: gas pore induced by high-velocity powder injection into melt pool, pore generated from swirl shear of turbulent melt flow, and pore trapped by surface wave. Three pore formation mechanisms are reconfirmed: pore inheritance from feedstock powder, pore generation when laser remelting defect-sensitive locations of existing pore from previous layer or unmelted powder attached on the melt pool surface, and pore formation as cooling of melt pool. A unique mechanism for pore elimination is proposed: a counter-Marangoni melt flow is experimentally found in the stable melt pool and contributes to the prolonged pore lifetime at tens of milliseconds scale; pores are prone to coalesce into larger sizes in laser interaction zone and the adjacent location with circulation zone; coalesced larger pores driven by combined effect of Marangoni and buoyant forces easily get eliminated from melt pool. The results of pore formation and evolution dynamics revealed in Cantor alloy provide quantified experimental data for high-fidelity computational modeling and in-depth insights of porosity control for high-entropy alloy printing down to melt pool scale.

Capturing Local Temperature Evolution During Additive Manufacturing Through Fourier Neural Operators

Abstract High-fidelity, data-driven models that can quickly simulate thermal behavior during additive manufacturing (AM) are crucial for improving the performance of AM technologies in multiple areas, such as part design, process planning, monitoring, and control. However, complexities of part geometries make it challenging for current models to maintain high accuracy across a wide range of geometries. In addition, many models report a low mean-square error (MSE) across the entire domain of a part. However, in each time-step, most areas of the domain do not experience significant changes in temperature, except for the regions near recent depositions. Therefore, the MSE-based fidelity measurement of the models may be overestimated. This article presents a data-driven model that uses the Fourier neural operator to capture the local temperature evolution during the AM process. Besides MSE, the model is also evaluated using the R2 metric, which places great weight on the regions where the temperature changes significantly than MSE. The model was trained and tested on numerical simulations based on the discontinuous Galerkin finite element method for the direct energy deposition AM process. The results shows that the model maintains 0.983−0.999 R2 over geometries not included in the training data, which is higher than convolutional neural networks and graph convolutional neural networks we implemented, the two widely used architectures in data-driven predictive modeling.

Origins of twin boundaries in additive manufactured stainless steels

316L and 304L stainless steels and a compositional gradient of both are fabricated using the same processing parameters via laser directed energy deposition additive manufacturing. In those alloys, the increase in chromium-to-nickel ratio is accompanied with grain refinement and formation of a high density of twin boundaries, i.e. Σ3 boundaries. By means of electron microscopy, crystallographic and thermodynamic calculations, we demonstrate that two mechanisms arising from the ferrite-to-austenite solidification mode are at the origin of twin boundary formation and grain refinement: (1) inter-variant boundaries emerging from the encounter of pairs of austenite grains formed from a common ferrite orientation with Kurdjumov–Sachs orientation relationship; (2) icosahedral short-range-ordering-induced (ISRO) nucleation of twin-related γ grains directly from the solidifying liquid. These findings define new routes to achieve grain boundary engineering in a single step in FeCrNi alloys, by tailoring the solidification pathway during the AM process, enabling the design of functionally graded materials with site-specific properties.

Microstructure, microhardness, tensile and fatigue investigation on laser shock peened Ti6Al4V manufactured by high layer thickness directed energy deposition additive manufacturing

Thin layer thickness in additive manufacturing (AM) has always been a hindering factor leading to long completion times. Increasing layer thickness is accompanied by a higher tendency of surface cracks and inferior mechanical properties. These can be improved with laser shock peening (LSP). Emphasizing on the high layer thickness, this paper elucidates the high-layer thickness laser directed energy deposition (LDED) AM and the effects of LSP on the fabricated parts. Primary focus was given to the investigation of surface microcracks, microstructures, tensile and fatigue properties. Ti6Al4V bulk sample was prepared using the LDED process. Tensile, fatigue, and other samples were extracted to investigate the above-mentioned properties using different characterization tools such as optical microscope, scanning electron microscope, Vickers microhardness tester, and universal testing machine. Results showed proper depositions without major defects despite the high-layer thickness. Micro-cracks were limited to the surface only, and typical Widmanstätten patterns with parallel α lath and mixed α+β microstructures are observed. Yield strength (YS) varied from 730 MPa to 940 MPa, while ultimate tensile strength (UTS) ranged from 799.5 MPa to 953.75 MPa. Even though laser peening significantly improved micro-hardness by 49.81 % on average, not all fatigue samples observed enhanced fatigue life. A maximum improvement of 40.34 % in fatigue performance was observed in the LDED+LSPed samples. The strain hardening, plastic deformation, and grain refinement during the LSP process contributed to the enhanced mechanical properties. Some samples’ reduced fatigue life may be due to the anisotropic nature of additively manufactured parts, internal defects, and surface cracks on the specific samples. Considering high layer thickness, vertical orientation of samples, and as-prepared samples, our research shows a promising high layer thickness additive manufacturing process. The current research can be used as a base for further study on other properties and characteristics.

Microstructural evolution and tensile properties of direct energy deposited Ti-4Al-5Co-0.25Si alloy during heat treatment

Additive manufacturing (AM) stands as an advanced manufacturing process, successfully utilized for the fabrication of high-value titanium components. However, these components have yet to find widespread use in industrial applications due to their inadequate performance when compared to conventionally processed parts. Consequently, there is a pressing demand to develop new alloys and microstructural control strategies to overcome this limitation. Here, we have designed a cost-effective Ti-4Al-5Co-0.25Si alloy for use in laser-based direct energy deposition additive manufacturing. The selection of solute elements has resulted in both solute strengthening and grain refinement. Additionally, the implementation of a heat-treatment schedule has allowed for control over the phase constituents and their stability. The as-fabricated alloy exhibits a prior-β grain size of ∼50 μm, α plate thickness of ∼0.6 μm, and tensile strength of 1145 MPa. Subsequent heat treatment induces the formation of subgrains, discontinuous grain boundary α and metastable β phases, and ultrafine martensitic features ranging from 40 to 100 nm. Moreover, this heat treatment improved the tensile strength of the alloy to 1500 MPa while maintaining an elongation of ∼5%. Importantly, the proposed hierarchical structured alloy offers an economical alternative, outperforming commercially available titanium alloys. This study presents a new direction for further research into alloy and microstructural design, aiming at the development of low-cost, high-performance titanium alloys suitable for additive manufacturing.

Solidification behavior and texture of 316L austenitic stainless steel by laser wire directed energy deposition

The solidification behavior and crystallographic texture of 316L austenitic stainless steel builds fabricated via laser-wire directed energy deposition additive manufacturing (AM) were investigated. Shielding gas set-up and build type (single-track vs. multi-track) were varied, which led to changes in the solidification conditions and the final build compositions. Primary δ-ferrite solidification is predicted based on equilibrium thermodynamic predictions of the bulk feedstock composition. However, the increased solidification velocity of the AM process promotes a solidification mode transition from primary δ-ferrite to primary austenite. Skeletal δ-ferrite and lathy δ-ferrite associated with primary δ-ferrite solidification and interdendritic δ-ferrite associated with primary austenite solidification were observed among the laser-wire directed energy deposition walls. Skeletal and interdendritic δ-ferrite exhibited a (001)δ // (001)γ parallel relationship with austenite and a {001} solidification texture aligned with the build direction for both austenite and δ-ferrite. Lathy δ-ferrite exhibited a Kurdjumov-Sachs orientation relationship, (101)δ//(11¯1)γ, with austenite due to austenite nucleation in the solid-state. It is shown that the solidification behavior of AM 316L is accurately represented by as-built composition data and a dendrite growth model, which combined, encompasses the compositional and solidification condition impacts on the solidification pathway.

Microstructure and elastocaloric effect of NiTi shape memory alloy in-situ synthesized by laser directed energy deposition additive manufacturing

The NiTi SMAs were successfully in-situ synthesized by LDED additive manufacturing, and the microstructural evolution and elastocaloric effect of the NiTi SMAs along parallel and perpendicular to the build direction (BD) were investigated. The NiTi SMAs at room temperature consisted of B2 austenite, B19’ martensite and the precipitation phase Ti2Ni, which was diffusely distributed within the B2 grains and at grain boundaries. Grain morphology that crosses the molten pool boundary and elongates along the thermal gradient is found in the plane parallel to the BD direction. NiTi SMAs loaded perpendicular to the BD direction have less energy loss and fewer stress mechanical training times to obtain fully recoverable stress-strain behavior, which shows better stress-strain response behavior than that loaded parallel to the BD direction. The maximum strain and adiabatic temperature changes follow a monotonically increasing trend from the maximum stress when the compressive stress was applied along parallel and perpendicular to the BD direction and rapidly removed. When the 900 MPa stress was removed, the adiabatic temperature changes reached −5.2 K and −5.9 K, respectively. The degradation of the elastocaloric effect of loading parallel to the BD direction reaches 15% after 100 stress-strain cycles (800 MPa). In contrast, the degradation of loading perpendicular to the BD direction is negligible. This work provides a new idea to realize the preparation of NiTi SMAs and to study the elastocaloric effect of NiTi SMAs.

Towards a self-healing aluminum metal matrix composite: Design, fabrication, and demonstration

This paper presents a novel approach to designing and synthesizing a self-healing aluminum-based metal matrix composite (MMC) at the macro-scale. The composite comprises an Al 5083 matrix embedded with low melting point particles (LMPPs) that act as healing agents. A two-step electroless micro-encapsulation process is developed to create LMMPs with a diffusion and thermal barrier designed to protect the Zn-8Al core with a Co-P shell. The MMC is fabricated using spark plasma sintering. Following controlled total fracture under tension, external compressive force is applied during heat treatment to heal the fracture effectively. The evolution of phases and interfaces is characterized using electron microscopy, and transient liquid phase bonding (TLPB) is identified as the fracture-healing mechanism, facilitated in areas with sufficiently high Zn concentration to fill the crack. The design can be expanded to incorporate other matrix and LMMP materials, mechanical crack volume reduction by integrating shape memory alloy (SMA) reinforcement during MMC synthesis, and processing of the self-healing MMC using Directed Energy Deposition additive manufacturing.

Improving the fatigue property of 316L stainless steel through direct energy deposition technology

In this study, to improve the fatigue strength of coarse grain 316L stainless steel, the hard 17-4ph martensitic stainless steel was deposited on the surface of hot rolled 316L based on direct energy deposition (DED) additive manufacturing technology. The 17-4ph deposition and 316L substrate are well connected without any cracking phenomenon which lays the foundation of good mechanical properties. The 17-4ph deposition presents a gradient structure, its fraction of body centered cubic (BCC) phase gradually increases from 0 vol% of substrate to 99.3 vol% of top surface, and its grain size gradually decreases from 53.2 μm near the substrate to 5.1 μm of the top surface, leading to the hardness of deposition gradually increases from 187 Hv to 436 Hv. The fatigue property of 17-4ph coated 316L is significantly improved. Specifically, the fatigue strength in high cycle fatigue (HCF) regime (at the fatigue life of 2 × 106 cycles) is 64 % higher than coarse-grained 316L, while the increment in low cycle fatigue (LCF) regime (at the fatigue life of 104 cycles) is up to 100 %. The improvement in LCF regime of 17-4ph coated 316L is higher than that of HCF regime, which is exactly opposite to the improvement in HCF and LCF regime of samples fabricated by traditional surface strengthening processes. Based on advanced characterization techniques, the potential strengthening mechanism in 17-4ph coated 316L was studied. It is expected that this study can provide reference for the application of additive manufacturing technology in the field of surface strengthening.

Coaxial color channel focus evaluation to estimate standoff height in directed energy deposition additive manufacturing

Coaxial color channel focus evaluation to estimate standoff height in directed energy deposition additive manufacturing

Influence of ultrasonic parameters on microstructural refinement and defect elimination in ultrasound-assisted laser-based metal additive manufacturing

Acoustic cavitation, streaming, and energy absorption during solidification in ultrasound-assisted direct energy deposition additive manufacturing (DED-AM) have been reported to drive microstructural refinement, defect elimination, and mechanical property improvement. However, the influence of individual ultrasonic parameters such as frequency, amplitude, intensity, and sonication duration remains unknown. This is mainly because of challenges in real-time quantification of the influence of ultrasound on the rapid solidification and microstructural development processes encountered in ultrasound-assisted AM. High temperature and opaque molten metal confined within micro-length scale melt pools further challenge the characterization of ultrasound’s influence on microstructural development. Building upon our recent in situ observation of acoustic cavitation and streaming in sonicated laser-generated melt pools, this talk will highlight our efforts to correlate vibration frequency, amplitude, and intensity with grain size and texture of Al7075 alloy fabricated using ultrasound-assisted DED-AM. DED additively manufactured Al7075 is susceptible to solidification cracking. Therefore, this presentation will also showcase the influence of ultrasonic parameters on cracking suppression and defect elimination. In addition, the effect of sonication duration on microstructure will also be elaborated. Lastly, the presentation will showcase our future work toward upscaling ultrasound-assisted AM to large parts with complex geometries.

Unraveling microstructure and mechanical response of an additively manufactured refractory TiVHfNbMo high-entropy alloy

Refractory high-entropy alloys (RHEAs) have attracted considerable interest due to their elevated melting points and exceptional softening resistance. Nevertheless, the ambient-temperature brittleness and inadequate high-temperature oxidation resistance commonly restrict the processability of RHEAs. Direct energy deposition (DED) additive manufacturing technology is ideal for fabricating refractory alloys due to design flexibility and oxygen-free environment. In this work, a novel Ti41V27Hf13Nb13Mo6 RHEA was successfully manufactured by DED, and a comprehensive investigation was conducted to explore the microstructure evolution and mechanical response during tension. The as-deposited RHEAs exhibit a grain-size graded microstructure with a body-centred-cubic (BCC) matrix and precipitates. Increasing laser energy density suppressed the grain boundary precipitation, effectively enhancing the ambient-temperature tensile ductility to ∼11.3%. The optimized specimens achieved an unprecedented yield strength of ∼1.2 GPa among the DEDed RHEAs, which can be attributed to a significant solid solution strengthening from the volume misfit of 5.03%. We revealed that dislocation interactions maintained the working hardening capacity. Moreover, in-situ characterization indicated that slip transfer, grain rotation, and kinking accommodated the plastic deformation. Crack nucleation was caused by slip inhibition at grain boundaries and dislocation pile-ups at intragranular precipitates. The kink band formation relieved stress concentration induced by intragranular precipitates and promoted a ductile fracture. These exceptional outcomes provide opportunities for additive manufacturing RHEAs and greatly advance understanding of their strengthening and deformation mechanisms.

Additively manufactured Ni-20Cr to V functionally graded material: Computational predictions and experimental verification of phase formations

A database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.