Additive Manufacturing Techniques Research Articles

The strengthening mechanism of mechanical and tribological properties of TiC-reinforced 316L matrix composites fabricated by selective laser melting

Selective laser melting (SLM) has been proved to be a promising additive manufacturing technique to fabricate high-performance metal matrix composites (MMCs) with unique microstructures. In this study, TiC-reinforced 316 L MMCs were successfully prepared by SLM. The effects of TiC addition on the microstructure evolution, mechanical properties and tribological behavior were systematically investigated to study the strengthening mechanism. The TiC/316 L MMCs fabricated by SLM exhibited a high relative density of over 99.6% and were close to full density. The TiC particles are effectively bonded with the 316 L matrix, serving as a means of dispersion strengthening. In addition, the grains were significantly refined, and the dislocation density was greatly enhanced with the addition of TiC particles, which reinforce the strength of the material. Tensile tests show that the tensile strength of TiC/316 L MMCs increased by 49.9% from 707 to 1060 MPa and yield strength increased by 44.2% from 543 to 783 MPa with 4 wt% TiC. Besides, the tribological behavior of TiC/316 L MMCs was much superior to the pure 316 L. The findings provide a new perspective on ceramic particles reinforced stainless steel MMCs with tailored microstructure and excellence performance.

A Review on Process Parameter Optimization in Material Extrusion Additive Manufacturing using Thermoplastic

Material extrusion is one of the most commonly used additive manufacturing techniques which utilizes thermoplastics as the building material. The quality and performance of parts produced via material extrusion depends highly on the process parameters selected. This paper reviews the work done by various researchers on optimizing key process parameters like extrusion temperature, layer thickness, infill percentage, infill pattern etc. in material extrusion 3D printing using thermoplastics like PLA, ABS and nylon. The effects of these parameters on properties like surface roughness, dimensional accuracy, mechanical strength are discussed. Statistical tools like Taguchi method and response surface methodology that have been applied for parameter optimization are also reviewed. The review highlights the need for further process optimization studies considering part design, build orientation and post processing to unleash the full potential of material extrusion 3D printing..

Cold metal transfer-based wire arc additive manufacturing of pure copper with ultra high tensile strength

Copper is used in various heating and cooling applications by exploiting its excellent thermal and electrical conductivities. Powder- and laser-based additive manufacturing (AM) of pure copper is challenging as it encounters porosity because of its low absorptivity. The present research reports the feasibility of cold metal transfer-based wire arc additive manufacturing (CMT-WAAM) for the manufacturing of pure copper thin wall. The microstructure of the deposit is examined at three distinct locations. The mechanical properties (including ultimate tensile strength, yield strength, elongation and hardness) are examined in both scanning direction (SD) and build direction (BD). The thermal and electrical properties of the deposit are also measured. The deposited thin wall is reported to be firm and straight without any bulging and collapsing. The CMT-WAAM fabricated pure Cu samples exhibit superior tensile strength (310 ± 12 MPa in SD and 265 ± 9 in BD) than all other AM techniques. The thermal and electrical conductivities of the built copper wall are comparable to the previously reported conductivities of pure copper fabricated by other AM routes.

Manufacturing via Plasma Metal Deposition of Hastelloy C-22 Specimens Made from Particles with Different Granulometries

Additive manufacturing techniques offer significant advantages for creating complex components efficiently, saving both time and materials. This makes them particularly appealing for producing parts from intricate alloys, such as Hastelloy C-22. One such technique, plasma metal deposition, uses plasma on powdered material to build up layers. The novelty of this work is to analyze and determine whether there is a correlation between the particle size and the final behaviour of specimens produced via additive manufacturing. To achieve this, four powders with an identical chemical composition but different granulometries were employed. Additionally, some of the samples underwent thermal treatment (progressive heating at 10 °C/min until 1120 °C, maintained for 20 min, followed by rapid air cooling). Four walls were constructed, and after mechanical, tribological, and microstructural characterization, it was determined that the influence of the thermal treatment remained consistent, regardless of particle size. It was observed that the particle size slightly affected the final properties: the finer the powder, the lower the ultimate tensile strength values. Furthermore, it was evident that the thermal treatment substantially affected the microstructure and wear behavior of all the specimens, regardless of their initial particle size.

The Use of Additive Manufacturing Techniques in the Development of Polymeric Molds: A Review.

The continuous growth of additive manufacturing in worldwide industrial and research fields is driven by its main feature which allows the customization of items according to the customers' requirements and limitations. There is an expanding competitiveness in the product development sector as well as applicative research that serves special-use domains. Besides the direct use of additive manufacturing in the production of final products, 3D printing is a viable solution that can help manufacturers and researchers produce their support tooling devices (such as molds and dies) more efficiently, in terms of design complexity and flexibility, timeframe, costs, and material consumption reduction as well as functionality and quality enhancements. The compatibility of the features of 3D printing of molds with the requirements of low-volume production and individual-use customized items development makes this class of techniques extremely attractive to a multitude of areas. This review paper presents a synthesis of the use of 3D-printed polymeric molds in the main applications where molds exhibit a major role, from industrially oriented ones (injection, casting, thermoforming, vacuum forming, composite fabrication) to research or single-use oriented ones (tissue engineering, biomedicine, soft lithography), with an emphasis on the benefits of using 3D-printed polymeric molds, compared to traditional tooling.

Stiffness, strength, anisotropy, and buckling of lattices derived from TPMS and Platonic and Archimedean solids

Lattice metamaterials have gained considerable attention due to their distinctive topological structures and multifunctional properties. In this work, the effect of topology, loading conditions, and relative density on the effective mechanical properties of various novel lattice architectures is investigated numerically and experimentally. Thirteen strut-based lattices derived from triply periodic minimal surfaces (five lattices) as well as Platonic (three lattices) and Archimedean (five lattices) solids are considered for the first time, and their anisotropic mechanical properties, including uniaxial, shear, and bulk moduli and strengths as well as their total stiffness, buckling strengths, Poisson’s ratio, and anisotropy are investigated as a function of a wide range of relative densities (0.1% to 37%). Finite element analysis is employed to capture the full effective behavior of these lattices using periodic boundary conditions. Bifurcation analysis is performed to predict the threshold relative density governing their buckling vs yielding deformation behavior. Selected lattice structures of various relative densities are 3D printed using polymer selective laser sintering additive manufacturing technique and tested under quasi-static uniaxial compression where the experimental and numerical results are compared. The numerical results indicate that the deformation behavior can be altered between stretching and bending dominated mode of deformation as function of loading. Archimedean lattices are shown to outperform a wide range of strut-based lattices. This work opens the doors for more investigations of the multifunctional properties of these novel types of lattices and their engineering applications. Furthermore, the generated comprehensive data are useful in optimizing latticed structures using topology optimization techniques.

Topology optimization of gyroid structure-based metal hydride reactor for high-performance hydrogen storage

Numerous engineering applications stand to gain substantial advantages by mitigating structural weight. While methods for optimizing continuous solids and discrete frame structures have long been available, the advent of additive manufacturing techniques has ushered in the potential for intricate geometries. In contrast, the hydrogen fuel sector confronts a pivotal challenge: the need to develop efficient hydrogen storage systems. Solid-state compounds like metal hydrides (MH) present a compelling solution among various hydrogen storage technologies thanks to their inherent safety attributes and superior hydrogen volumetric density. Nonetheless, the limitation of MH lies in its gravimetric density, impeding its application in mobility contexts. A transformative strategy addresses this limitation by seamlessly integrating the reactor tank into the vehicle's frame and chassis. This study introduces a pioneering concept—an optimally designed MH container incorporating a gyroid structure. Subsequently, this innovative design underwent rigorous analysis, employing finite element analysis (FEA) and computational fluid dynamics, assessing mechanical properties, heat transfer capabilities, and the efficiency of hydrogen charging into the MH within the structure. Using topology optimization of solid isotropic material with penalization method, a 17 % increase in the chamber volume and a concurrent reduction of the material by nearly 50 %. This profound transformation positively impacted the reactor's volumetric and gravimetric density. Despite a measurable reduction in strength, the optimized structure demonstrated resilience, successfully withstanding prescribed mechanical shear loads. Furthermore, the structure exhibited impressive rigidity, with displacement below 0.2 mm, rendering it suitable and highly competent for integration into assembly components like vehicle frames or chassis. Notably, the optimized structure exhibited a promising enhancement in hydrogen charging rate.

Ultrafine-grained stainless steel with wear-resistant nanoborides decorating grain boundaries produced by laser powder bed fusion

Stainless steel composites combine corrosion resistance and toughness of the metallic matrix with wear resistance granted by hard reinforcing nanoparticles. Given their near-net-shape manufacturing characteristics, additive manufacturing techniques are attractive to produce these hard and wear-resistant classes of materials with low machinability. In this work, from a SAF 2205 duplex stainless steel with boron addition, laser powder bed fusion (LBPF) was employed to produce an ultrafine-grained (∼1 µm), dense (porosity ∼0.1 %), and crack-free ferritic-induced matrix composite with Cr2B-nanoborides reinforcing the grain boundaries (GBs) without formation of Cr-depleted regions. The composite showed significant higher hardness (up to 456 HV0.5) and wear resistance (4.4 x 10−5 mm3 N−1 m−1) in sliding condition compared to a hot-rolled (225 HV0.5 and 2.9 x 10−3 mm3 N−1 m−1) and a LPBF-produced SAF 2205 (314 HV0.5 and 3.3 x 10−4 mm3 N−1 m−1).

Wear Behavior Assessment of New Wire-Arc Additively Manufactured Surfaces on AA6061 and AA5086 Alloys through Multi-Walled Carbon Nanotubes and Ni Particles Inducement

This study investigates the new surface development on AA6061 and AA5086 alloys considering the wire-arc additive manufacturing technique as a direct energy deposition (DED) process of wire. Two different quantities of MWCNTs, i.e., 0.01 (low) and 0.02 (high) g, with a constant nickel (Ni) weight (0.2 g) were pre-placed in the created square patterns. ER4043 filler was used as a wire for additive deposition, and an arc was generated through a tungsten inert gas (TIG) welding source. Furthermore, hardness and pin-on-disk wear-testing methods were employed to measure the changes at the surfaces with the abovementioned inducements. This work was designed to illustrate the hardness and the offered wear resistance in terms of mass loss of the AA6061 and AA5086 aluminum alloys with the function of nano-inducements. Two sliding distance values of 500 m and 600 m were selected for the wear analysis of mass loss from tracks. A maximum increase in hardness for AA6061 and AA5086 alloys was observed in the experiments, with average values of 70.76 HRB and 74.86 HRB, respectively, at a high mass content of MWCNTs. Moreover, the tribological performance of the modified surfaces improved with the addition of MWCNTs with Ni particles in a broader sense; the modified surfaces performed exceptionally well for AA5086 compared to AA6061 with 0.02 and 0.01 g additions, respectively. The system reported a maximum of 38.46% improvement in mass loss for the AA5086 alloy with 0.02 g of MWCNTs. Moreover, the morphological analysis of the developed wear tracks and the mechanism involved was carried out using scanning electron microscope (SEM) images.

Microstructural evolution, mechanical properties and tribological behavior of SiC reinforced 316L matrix composites fabricated by additive manufacturing

Selective laser melting (SLM) has been proved to be a promising additive manufacturing technique for production of high-performance metal matrix composites (MMCs) with unique microstructures. In this study, the SiC- reinforced 316L MMCs were prepared by SLM and the effects of SiC addition on the densification, microstructure evolution, mechanical properties and tribological behavior were systematically investigated. The SiC/316L MMCs fabricated by SLM were close to full density with high relative density over than 99.7%. The grains were significantly refined, and dislocation density was greatly enhanced with the addition of SiC particles. Tensile tests show that tensile strength of the specimens increased by 81.8% from 707 to 1285 MPa and yield strength increased by 72.7% from 543 to 938 MPa with the addition of SiC. In addition, the tribological behavior of MMCs with SiC addition are much superior to the pure 316L. The underlying strengthening mechanisms are discussed. The findings provide a new perspective on ceramic particles reinforced stainless steel MMCs with unique microstructure and excellence performance.

Xolography for the Production of Polymeric Multimaterials

AbstractThree‐dimensional (3D) printed multimaterials have quickly grown in interest as researchers aim to mimic the material chemistry and geometric complexity of natural materials. While some exceptional multimaterial 3D printing systems have been developed, there is still a shortfall in the scope and production of these materials. More recently, the introduction of xolography as a single‐step, auxiliary‐free additive manufacturing approach has enabled rapid production of materials with geometries inaccessible via other additive manufacturing techniques. However, previous systems required resins with high transparency for effective material formation, and multimaterial formation has not been demonstrated. In this work, reversible deactivation radical polymerization is used and resin composition, viscosity, and processing parameters are explored to develop new resins capable of application to visible light‐mediated xolography. After optimization, non‐transparent resins containing thiocarbonylthio species are applied to xolography to manufacture geometrically complex, auxiliary‐free materials. The resulting 3D printed polymer network materials can be functionalized via the embedded thiocarbonylthio moieties to impart new functionality to the printed materials. Finally, the unique 3D printing capabilities of xolography are demonstrated to manufacture multimaterials featuring chemically disparate domains with high 3D‐spatial control. This two‐step overprinting approach is operationally simple and provides a new avenue for manufacturing polymeric multimaterials via 3D printing.

High entropy alloys amenable for laser powder bed fusion: A thermodynamics guided machine learning search

Although there is considerable research interest in high-entropy alloys (HEAs), only a small fraction of the potential compositional space was explored hitherto. While additive manufacturing techniques such as the laser powder bed fusion (LPBF) can be gainfully employed to accelerate discovery of new HEAs with promising properties, the printability of such alloys could restrict such an exploration. Keeping this in view, a machine learning (ML) based alloy design strategy, which takes thermodynamic parameters such as the liquid temperature range (LR), liquid viscosity (LV), average expansion (AE) during the solidification of the alloy, and shear/bulk moduli ratio (G/B) of solidified alloy into account, is developed for assessing the printability of HEAs using LPBF. First, a printability evaluation chart that has six different printing capacity regions is obtained by considering LR, LV, AE, G, and B. Then, ML is utilized to predict the candidate chemical compositions within them that are amenable to LPBF. On this basis, an alloy with the composition Co7.5Cr7.5Nb7.5Ni10.0Ti67.5 (at%) was identified, and its process window range and printability were validated through experiments. The range of thermodynamic parameters suitable for the manufacturability was determined as LV >5.5 mPa•s, LR >1600 ℃, AE <25%, and G/B <0.5. The effects of thermodynamic parameters on the printing process window was systematically investigated. Furthermore, Shapley Additive exPlanations (SHAP) algorithm was utilized to evaluate the influence of various elements on the thermodynamic parameters, which could, in turn, guide the chemical composition design so as to achieve HEAs with good printability. This work provides the thermodynamic parameter index for LPBF and offers opportunities to use ML for accelerating the design of HEAs that are amenable to LPBF.

Interpretable machine learning approach for exploring process-structure-property relationships in metal additive manufacturing

Process-structure-property (PSP) relationships are critical to the optimization of manufacturing processes, but establishing these relationships typically involves time- and cost- consuming experiments, especially for additive manufacturing (AM) due to the large number of process parameters involved. In this study, we develop a novel and interpretable machine learning approach for predicting, optimizing, and expanding the process window of laser powder bed fusion (LPBF) while simultaneously establishing PSP relationships, using AlSi10Mg as an example. Our iterative, error-targeted method substantially decreases the amount of experimentation required. Gaussian process regression (GPR) was employed as the predictive model, incorporating multiple input variables (e.g., process parameters, relative density, melt pool morphology, cellular structure, and grain structure), for predicting three mechanical properties (i.e., yield strength, ultimate tensile strength, and % elongation). A comparison of model predictions and experimental data outside the training scope reveals that the prediction accuracy can be improved with higher dimensional inputs and further enhanced by a multi-output model that accounts for correlations between the different mechanical properties. Additionally, the GPR kernel’s hyperparameter for each input enables feature selection and model interpretability. The proposed approach can assist with finding the most critical variables affecting mechanical performance, establishing the PSP relationships of AM fabricated alloys, and providing guidance for tailoring the final properties. The methodology presented in this study can be applied to various AM techniques and materials to broaden the process window to achieve previously unattainable mechanical properties, as well as to gain a deeper understanding of the PSP relationships.

Optimized analytical approach for the detection of process-induced defects using acoustic emission during directed energy deposition process

Directed energy deposition (DED), an advanced additive manufacturing (AM) technique, facilitates the production of complex metallic and metal matrix composite structures. The DED process has continuously improved and offers numerous advantages for depositing high-quality coatings with excellent wear and corrosion resistance onto metallic surfaces. The dynamic nature of the process, however, introduces a significant risk of process-induced defects in manufactured parts. This study presents an optimized analytical approach using acoustic emission (AE) based defect detection technique to identify and quantify process-induced cracks during the DED process. The developed signal processing technique enabled the identification of actual AE events associated with cracking, distinguishing them from other disturbances. Experimental validation was conducted using manufactured parts that were longitudinally sectioned to determine the relationship of the crack location with the recorded acoustic signal. The demonstrated correlation of acoustic signatures with cracking illustrates the robustness of the AE technique to identify the process-induced cracking for quality assurance during the DED process.

Mechanical properties of additively manufactured polymeric composites using sheet lamination technique and fused deposition modeling: A review

AbstractNowadays, it is possible to produce products with complex geometries, thanks to the experts who have continuously explored the advancements in additive manufacturing (AM) techniques. This review helps readers understand the opportunities and difficulties associated with developing parts for various industries, including aerospace, tooling, electronics, and biomedicine. The present work describes the landscape of polymeric composites using laminated object manufacturing (LOM) and fused deposition modeling (FDM). This paper discusses recent publications in the realm of AM related to composite fabrication, materials, techniques, functionality, and future scope. The effects of nanofiller reinforcement on the mechanical properties of composites have been thoroughly investigated. Furthermore, FDM process parameters such as layer thickness, infill speed, nozzle temperature, and raster angle have also been considered. Finally, the challenges and potential applications of LOM and FDM of additively manufactured composites have been summarized.

3D Non-Newtonian deposition flow and thermal simulations to evaluate the scale-up potential for material extrusion of single walled ABS parts with overhang

Material extrusion (MEX) is one of the most widely used additive manufacturing (AM) techniques for polymeric materials. In the present work, 3D simulations using Ansys Polyflow are employed to address two MEX challenges: (i) avoiding sub-optimal thermal control in the deposited part, with a too low temperature leading to a weak bond between individual strands and a too high temperature resulting in too much deformation, so that a dimensionally accurate part with the same mechanical properties of the bulk material can be printed; (ii) applicability for larger nozzle diameters away from the original application of a sub 1 mm size and going to 10 mm or more, implying a higher industrial relevance. Focus is on the scale-up potential for a single walled acrylonitrile butadiene styrene (ABS) part with an overhanging structure (e.g. 30 or 45°) and strand aspect ratios between 2 and 4, considering up to 4 layers in the simulations. The small scale results are experimentally validated, showcasing the relevance of accurate 3D deposition simulations at other scales with more difficult validation procedures. It is shown that upscaling of the MEX process changes the cooling mechanism from conduction to convection driven. It is further demonstrated how simulations can be used to predict the failure of a print at a given scale and how the printing speed can be adapted to avoid such failure.

Effect of AlN content on microstructure and properties of SiAlON ceramics prepared via vat photopolymerization

To date, the application of additive manufacturing techniques in fabricating SiAlON ceramics with intricate geometries has been limited. This investigation demonstrates the synthesis of SiAlON ceramics by integrating silicon nitride (Si3N4) powders with variable proportions of aluminum nitride (AlN) utilizing the vat photopolymerization (VPP) approach. The effects of AlN content on the properties of SiAlON ceramic slurries, green bodies, and sintered parts were systematically investigated. Notably, the slurry's viscosity decreases progressively with an increase in AlN, aligning with VPP printing prerequisites. Additionally, the curing depth of the slurry enhanced proportionally with AlN augmentation, elevating from 21 μm to 44 μm at an energy exposure of 800 mJ/cm2, with the pivotal addition being 15 vol% AlN, where optimal properties were achieved. The zeniths of flexural strength, bulk density, relative density, and thermal conductivity were recorded at 385.66 ± 22.63 MPa, 3.34 ± 0.09 g/cm3, 96.22 ± 2.55 %, and 37.4 ± 0.31 W m−1 K−1, respectively. The fabrication of SiAlON ceramics with complex configurations was successfully realized, heralding a novel methodology for future SiAlON ceramic production.

Manufacturing of Brake Pads and Brake Shoes Through Additive Manufacturing with Boron Carbide (B4C) and Molybdenum Disulfide (MoS2) as Additives

Abstract: An essential component of car performance and safety is the production of brake shoes and pads. This study investigates how to improve these components by incorporating innovative materials using additive manufacturing techniques. Because of their special qualities, molybdenum disulfide (MoS2) and boron carbide (B4C) are used as additives. MoS2, which is well-known for its solid lubricating qualities, seeks to improve the frictional properties, while B4C, which is recognized for its extraordinary hardness, is added to increase wear resistance. Brake component performance can be maximized by precisely controlling the material composition and complex designs through the use of additive manufacturing. The combination of B4C and MoS2 provides a well-rounded solution by tackling the wear and friction issues that are essential for efficient braking. In order to obtain increased frictional stability, decreased wear rates, and greater durability, this study looks into the best ratios and distribution of these additives. This study seeks to contribute to the development of next generation brake systems, ensuring improved safety, efficiency, and lifetime in automotive applications by utilizing modern manufacturing techniques and combining B4C and MoS2. The results are anticipated to have an impact on the production of high-performance components with customized material qualities in the automobile industry as well as the larger field of additive manufacturing.

Mechanical investigation of compositing by resin filling in lattice structures manufactured with fused deposition modelling

Fused Deposition Modeling (FDM) is a widely used polymer additive manufacturing technique for polymer part manufacturing and prototyping. However, manufacturing speed, mechanical properties, and high costs, limit its suitability for industrial applications. In this study, researchers blended polyester and polyurethane resins with lattice structures to achieve a remarkable 70% reduction in production time and a 75% decrease in manufacturing costs. They explored five lattice structure geometries relevant to common literature applications. Lattice structures were manufactured using PA, PLA, PA-CF, and TPU filaments. The composite samples underwent comprehensive analysis, including SEM microscopic inspections, density measurements, and compression tests. Parameters such as density, yield strength, compressive strength, specific stress, modulus of elasticity, and toughness were evaluated. The findings revealed that polyester-based composites exhibited a remarkable 131% enhancement in mechanical properties, with toughness values increasing up to 12-fold. The results revealed significant mechanical advantages that the developed composites can offer in applications.

Influence of Spatter on Porosity, Microstructure, and Corrosion of Additively Manufactured Stainless Steel Printed Using Different Island Size

Specimens of 316 L stainless steel were printed using laser powder bed fusion (LPBF), a popular metal additive manufacturing (AM) technique, with varying island sizes. Not many researchers have considered the impact of spatter while optimizing LPBF printing parameters. In this research, the influence of spatter was considered while also investigating the effect of varied island size on the microstructure, surface roughness, microhardness, and corrosion resistance of LPBF-316 L. No correlation was observed between surface roughness or microhardness and minor variations in island size. However, a correlation was drawn between varied island sizes and porosity in LPBF-316 L. The specimens associated with larger island sizes showed significantly enhanced corrosion resistance due to fewer manufacturing defects and reduced porosity, attributed to the minimal influence of the spatter. Based on analysis, the LPBF parameters were revised, which lead to superior corrosion resistance of LPBF-316 L, attributed to high density and reduced porosity.