Additive Manufacturing Techniques Research Articles

3D Bioprinting Strategies for Melatonin‐Loaded Polymers in Bone Tissue Engineering

AbstractBone pathologies are still among the most challenging issues for orthopedics. Over the past decade, different methods are developed for bone repair. In addition to advanced surgical and graft techniques, polymer‐based biomaterials, bioactive glass, chitosan, hydrogels, nanoparticles, and cell‐derived exosomes are used for bone healing strategies. Owing to their variation and promising advantages, most of these methods are not translated into clinical practice. Three dimensonal (3D) bioprinting is an additive manufacturing technique that has become a next‐generation biomaterial technique adapted for anatomic modeling, artificial tissue or organs, grafting, and bridging tissues. Polymer‐based biomaterials are mostly used for the controlled release of various drugs, therapeutic agents, mesenchymal stem cells, ions, and growth factors. Polymers are now among the most preferable materials for 3D bioprinting. Melatonin is a well‐known antioxidant with many osteoinductive properties and is one of the key hormones in the brain–bone axis. 3D bioprinted melatonin‐loaded polymers with unique lipophilic, anti‐inflammatory, antioxidant, and osteoinductive properties for filling large bone gaps following fractures or congenital bone deformities may be developed in the future. This study summarized the benefits of 3D bioprinted and polymeric materials integrated with melatonin for sustained release in bone regeneration approaches.

An anthropomorphic phantom for atrial transseptal puncture simulation training

BackgroundTransseptal puncture (TSP) is a critical prerequisite for left-sided cardiac interventions, such as atrial fibrillation (AF) ablation and left atrial appendage closure. Despite its routine nature, TSP can be technically demanding and carries a risk of complications. This study presents a novel, patient-specific, anthropomorphic phantom for TSP simulation training that can be used with X-ray fluoroscopy and ultrasound imaging.MethodsThe TSP phantom was developed using additive manufacturing techniques and features a replaceable fossa ovalis (FO) component to allow for multiple punctures without replacing the entire model. Four cardiologists and one cardiology trainee performed TSP on the simulator, and their performance was assessed using four metrics: global isotropy index, distance from the centroid, time taken to perform TSP, and a set of 5-point Likert scale questions to evaluate the clinicians’ perception of the phantom’s realism and utility.ResultsThe results demonstrate the simulator’s potential as a training tool for interventional cardiology, providing a realistic and controllable environment for clinicians to refine their TSP skills. Experienced cardiologists tended to cluster their puncture points closer to regions of the FO associated with higher global isotropy index scores, indicating a relationship between experience and optimal puncture localization. The questionnaire analysis revealed that participants generally agreed on the phantom’s realistic anatomical representation and ability to accurately visualize the TSP site under fluoroscopic guidance.ConclusionsThe TSP simulator can be incorporated into training programs, offering trainees the opportunity to improve tool handling, spatial coordination, and manual dexterity prior to performing the procedure on patients. Further studies with larger sample sizes and longitudinal assessments are needed to establish the simulator’s impact on TSP performance and patient outcomes.

Investigating enhanced electrical conductivity for antenna applications through dual metallization on 3D printed SLA substrates

The advancement of 3D printing (additive manufacturing) has gained interest in variety of applications, especially for antenna fabrication. The demand for cheap, reliable, and high-performance antenna fabrication methods is essential in order to cope with the demand of wireless communications industry. In this work, the focus was emphasized on enhancing the electrical conductivity of the 3D printed substrates fabricated by stereolithography (SLA) 3D printer. The 3D printed substrate went through a dual metallization approach, involving sputtering and electrodeposition techniques for the fabrication of conductive metal layers. The parameters for the sputtering were fixed for all the substrate while current density during electrodeposition process was varied at 25 %, 50 %, 75 % and 100 % from recommended value of current. The results showed that the current density during the electrodeposition determined the conductivity performance of the metal layers and established a significant correlation with the surface morphological. Three different frequencies comprised of 2.4 GHz, 3.5 GHz and 5.0 GHz were selected to simulate and fabricate a microstrip patch antenna using the optimized current density which was valued optimal at 75 % (52.5 mA). The percentage of accuracy between simulated and measured frequencies of antenna, portrayed that the measured values were slightly higher than the simulated approximately about 5.14 to 6.67 %. Therefore, the integration of additive manufacturing or 3D printing techniques for antenna could address the critical necessity for fast and economical solution in wireless systems.

An innovative multilayered material fabricated through additive manufacturing for structural applications: method and mechanical properties

Abstract Additive manufacturing (AM) is a cost-effective method for fabricating structurally sound components. Fused filament fabrication (FFF) is a popular AM technique known for its design flexibility, minimal material wastage, and recyclability. Poly lactic acid (PLA) is a thermoplastic widely used in aerospace, biomedical, and automobile industries. Wood-PLA, incorporating wood fillers into PLA, finds applications in several industries. This research explores multilayered materials (MLM) for enhanced performance in various sectors such as aircraft, energy, and biomedical. Mechanical properties of MLM were investigated under different load conditions (tensile, bend, compressive). Properties simulated through Finite Element Method (FEM) showed minimal error (less than 1 %). Microscopic analysis, aided by scanning electron microscope (SEM) fractography, reveals a brittle mode of failure in the specimens. This study provides valuable insights into the mechanical behaviour of MLM, offering potential applications in diverse industries.

Digital Light Process 3D Printing of Magnetically Aligned Liquid Crystalline Elastomer Free-forms.

Liquid crystalline elastomers (LCEs) are anisotropic soft materials capable of large dimensional changes when subjected to a stimulus. The magnitude and directionality of the stimuli-induced thermomechanical response is associated with the alignment of the LCE. Recent reports detail the preparation of LCEs by additive manufacturing (AM) techniques, predominately using direct ink write printing. Another AM technique, digital light process (DLP) 3D printing, has generated significant interest as it affords LCE free-forms with high fidelity and resolution. However, one challenge of printing LCEs using vat polymerization methods such as DLP is enforcing alignment. Here, we document the preparation of aligned, main-chain LCEs via DLP 3D printing using a 100 mT magnetic field. Systematic examination isolates the contribution of magnetic field strength, alignment time, and build layer thickness on the degree of orientation in 3D printed LCEs. Informed by this fundamental understanding, DLP is used to print complex LCE free-forms with through-thickness variation in both spatial orientations. The hierarchical variation in spatial orientation within LCE free-forms is used to produce objects that exhibit mechanical instabilities upon heating. DLP printing of aligned LCEs opens new opportunities to fabricate stimuli-responsive materials in form factors optimized for functional use in soft robotics and energy absorption.

Development of Additively Manufactured Embedded Ceramic Temperature Sensors via Vat Photopolymerization

Current additive manufacturing (AM) techniques and methods, such as liquid-crystal display (LCD) vat photopolymerization, offer a wide variety of surface-sensing solutions, but customizable internal sensing is both scarce in presence and narrow in scope. In this work, a fabrication process for novel customizable embedded ceramic temperature sensors is investigated. The fabrication techniques and materials are evaluated, followed by extensive characterization via spectral analysis and thermomechanical testing. The findings indicate that LCD-manufactured ceramic sensors exhibit promising sensing properties, including strong linear thermal sensitivity of 0.23% per °C, with an R2 of at least 0.97, and mechanical strength, with a hardness of 570 HV, making them suitable for adverse environmental conditions. This research not only advances the field of AM for sensor development but also highlights the potential of LCD technology in rapidly producing reliable and efficient ceramic temperature sensors.

Shrinkage and deformation of material extrusion 3D printed parts during sintering: Numerical simulation and experimental validation

Material extrusion 3D printing (ME3DP) combined with sintering is a low-cost additive manufacturing technique for fabricating components of difficult-to-print metals, such as copper, aluminum, and ceramics. However, the sintering process includes complex material science, such as volumetric shrinkage and free structural bending, to identify the relative density and deformation of a 3D printed sample. The prediction of the relative density and deformations during the sintering process provides information to the design engineer to optimize the design of the CAD model before sintering. In this study, a phenomenological model based on constitutive equations was developed to predict the density and structural deformation during the sintering process of pure copper components fabricated by ME3DP using metal injection molding feedstock. The densification rate was determined using shrinkage estimation with an isothermal stairway heating cycle in a vertical dilatometer. Furthermore, different sets of experiments were performed with a load on the probe with long isothermal heating cycles at 850, 900, 950, 1000, and 1050 °C in a vertical dilatometer to estimate the axial viscosity of the copper. The constitutive equations were solved using the solid mechanics module with user-defined creep in COMSOL Multiphysics by considering isotropic assumptions. Two types of geometries, cube and overhanging I section, were used to predict shrinkage and deformation during the sintering process. The developed model successfully predicted the relative density based on shrinkage and structural deformation owing to gravity during the sintering process.

Tensile strength of friction stir additive manufactured laminated AA 6061/TiC/GS composites

Abstract With the fast progress of industrial manufacturing, friction stir additive manufacturing has fascinated wide-ranging consideration in the industry due to high material consumption rate. Friction stir additive manufacturing (FSAM), a newly developed solid-phase additive manufacturing technique was employed to fabricate AA6061/TiC/GS composite. The process parameters like tool rotational speed, transverse speed, tool tilt angle and type of tools used in friction stir additive manufacturing were analyzed. Taguchi’s L16 orthogonal array and ANOVA method was used to find the optimum process parameters for the tensile strength. Development characteristics of stirred zone, recrystallization and mixing of reinforced particles will significantly improve the mechanical properties of the fabricated composites. Microstructural investigation and fractography was done by using optical microscopy and scanning electron microscopy (SEM). Corrosion, wear behavior and elemental analysis through EDS was also performed for the fabricated material. The maximum tensile strength of 385.74 MPa was attained under optimal parameters of the tool rotational speed 1,200 rpm, transverse speed 55 mm min−1, and tool tilt angle of 1° for scrolled tapered octagonal tool pin. The findings of the linear regression model showed a minor variance between model and experimental values. Prominent results of the experiment were compared by few other researcher’s findings working in similar area.

Neural Network Architectures and Magnetic Hysteresis: Overview and Comparisons

The development of innovative materials, based on the modern technologies and processes, is the key factor to improve the energetic sustainability and reduce the environmental impact of electrical equipment. In particular, the modeling of magnetic hysteresis is crucial for the design and construction of electrical and electronic devices. In recent years, additive manufacturing techniques are playing a decisive role in the project and production of magnetic elements and circuits for applications in various engineering fields. To this aim, the use of the deep learning paradigm, integrated with the most common models of the magnetic hysteresis process, has become increasingly present in recent years. The intent of this paper is to provide the features of a wide range of deep learning tools to be applied to magnetic hysteresis context and beyond. The possibilities of building neural networks in hybrid form are innumerable, so it is not plausible to illustrate them in a single paper, but in the present context, several neural networks used in the scientific literature, integrated with various hysteretic mathematical models, including the well-known Preisach model, are compared. It is shown that this hybrid approach not only improves the modeling of hysteresis by significantly reducing computational time and efforts, but also offers new perspectives for the analysis and prediction of the behavior of magnetic materials, with significant implications for the production of advanced devices.

Heat treatments-induced wear resistance of Inconel 718 superalloy fabricated via Laser based Powder Bed Fusion

Laser based Powder Bed Fusion (LPBF) stands out among Additive Manufacturing (AM) techniques for its ability to fabricate intricate geometries with high precision. However, LPBF produced parts, particularly Inconel 718 (IN718) superalloys, demand further exploration in microstructural and mechanical properties aspect. This study explores the effect of heat treatments on LPBF fabricated Inconel 718. Three distinct heat treatments involving diverse solutionizing temperatures and ageing steps were applied to the LPBFed IN718 alloy. As-printed samples showed columnar dendritic microstructure. The heat treatments led to precipitation of strengthening γ′′ and γ′ phases. A substantial increase in microhardness was observed after heat treatments. Wear tests revealed as-printed specimens suffered higher wear loss (∼889 μm) and coefficient of friction (COF) (∼0.627) attributed to Laves phase and low hardness of the matrix. However, heat-treated specimens exhibited substantially lower wear loss (∼217 μm) and COF (∼0.342), with HT2 condition demonstrating superior wear resistance attributed to a homogeneous microstructure.

Generalized SmartScan: An Intelligent LPBF Scan Sequence Optimization Approach for Reduced Residual Stress and Distortion in 3D Part Geometries

Abstract Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using an intelligent (i.e., model-based and optimization-driven) approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer; (3) providing the optimization in SmartScan with a balance of exploration and exploitation to make it less myopic; and (4) improving SmartScan’s computational efficiency via model order reduction using singular value decomposition. Sample 3D test artifacts are simulated and printed using SmartScan in comparison with common heuristic scan sequences. Reductions of up to 92% in temperature inhomogeneity, 86% in residual stress, 24% in maximum deformation and 50% in geometric inaccuracy were observed using SmartScan. An approach for using SmartScan for printing complex 3D parts in practice, by integrating it as a plug-in to a commercial slicing software, was also demonstrated experimentally, along with its benefits in significantly improving printed part quality.

Analysis of Geometrical Accuracy and Surface Quality of Threaded and Spline Connections Manufactured Using MEX, MJ and VAT Additive Technologies.

This paper presents the process of manufacturing mechanical joint components using additive manufacturing (AM) techniques such as Material Extrusion (Fused Deposition Modelling (FDM)), Material Jetting (PolyJet), and Vat Photopolymerization (VAT)/Stereolithography (SLA). Using the PolyJet technique and a photopolymer resin, spline and threaded joint components were produced. For comparative analysis, the threaded joint was also fabricated using FDM and SLA techniques. PLA material was used for the FDM technique, while photopolymer resin was utilized for the SLA process. The components produced underwent a surface analysis to evaluate the accuracy of the dimensions in relation to the nominal dimensions. For the spline connection components, the dimensional deviations recorded by a 3D scanner ranged from -0.11 to +0.18 mm for the shaft and up to 0.24 mm for the sleeve. Measurements of screw and nut diameters showed the highest accuracy for screws produced using the PolyJet technique, while the nuts exhibited the best accuracy when fabricated with the SLA method. The profile of the screw threads using a contour gauge revealed the most accurate thread profile on the screw manufactured with the PolyJet technique.

Effect of Printing Orientation on the Mechanical Properties of Low-Force Stereolithography-Manufactured Durable Resin

This study presents the results of fracture toughness tests conducted on specimens obtained by additive manufacturing techniques, specifically using low-force stereolithography. The samples were manufactured from a transparent 3D printing material for biocompatible applications, the so-called BioMed Durable Resin, which is a Formlabs-patented polymer material that simulates the strength and rigidity of polyethylene. The selected toughness tests in this context were performed following the ASTM D5045-99 guidelines. All tests were conducted under controlled laboratory conditions at 23 °C and 50% relative humidity, ensuring adherence to the standard and the replicability of the experimental results. To investigate the influence of printing plane orientation, specimens were produced at three printing orientation angles (0, 45, and 90 degrees). These angles were selected to provide a comprehensive evaluation of the anisotropy effects in the material. They cover both extreme orientations (0° and 90°) and include an intermediate value (45°), allowing us to assess variations in mechanical behavior across a representative range of printing orientations, consistent with prior research in the field. The experimental tests yielded data on the crack resistance and energy release rate for each angle of orientation. There are various implications of the findings, beyond materials engineering, for applications in biomedicine. Indeed, this same approach opens the door to new research methods for manufacturing certified biocompatible materials from such durable resins. Finally, complementary issues such as related medical applications have been slightly addressed for future work, since biomedicine innovation clusters can contribute to accelerating growth in this crucial field for productive sector activity and the local business environment.

Residual Stress Optimisation for Manufacturing of a Nozzle Guide Vane in Mar-M-509 by Laser Powder Bed Fusion

Abstract This paper delves into the potential of Additive Manufacturing (AM) technologies, focusing on the utilization of Laser Powder Bed Fusion (LPBF) to optimize the manufacturing process for Mar-M-509, a Cobalt-based superalloy, in aeroderivative industrial gas turbine nozzle guide vanes. While Mar-M-509 offers exceptional properties for high-temperature applications, the rapid cooling rates inherent in LPBF introduce significant residual stresses, leading to poor success rates below 50%. The study systematically addresses this challenge by proposing a comprehensive methodology to optimize LPBF parameters. By fine-tuning processing conditions, including elevating the powder bed and build chamber temperatures, the research achieved notable reductions in residual stresses by up to 55%. Computational simulations played a pivotal role in predicting deformations and thermal signatures, enabling proactive adjustments to process conditions, ultimately enhancing part quality and process reliability. Validation through successful printing with a yield exceeding 75% underscores the effectiveness of this approach. Moreover, the study suggests the broader applicability of these optimization strategies beyond Mar-M-509, paving the way for advancements in AM techniques across diverse materials and industrial sectors. This research not only presents a robust solution for mitigating residual stresses in LPBF-produced components but also showcases a proactive methodology that promises significant implications for additive manufacturing's future advancements and applicability.

A review of computational optimization of bone scaffold architecture: Methods, challenges, and perspectives

Abstract The design and optimization of bone scaffolds are critical for the success of bone tissue engineering (BTE) applications. This review paper provides a comprehensive analysis of computational optimization methods for bone scaffold architecture, focusing on the balance between mechanical stability, biological compatibility, and manufacturability. Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and various optimization algorithms have been discussed for their roles in simulating and refining scaffold designs. The integration of multiobjective optimization and topology optimization has been highlighted for developing scaffolds that meet the multifaceted requirements of BTE. Challenges such as the need for consideration of manufacturing constraints, and the incorporation of degradation and bone regeneration models into the optimization process have been identified. The review underscores the potential of advanced computational tools and additive manufacturing techniques in evolving the field of BTE, aiming to improve patient outcomes in bone tissue regeneration. The reliability of current optimization methods is examined, with suggestions for incorporating non-deterministic approaches and in vivo validations to enhance the practical application of optimized scaffolds. The review concludes with a call for further research into artificial intelligence-based methodologies to drive the next generation of scaffold design and optimization.

Identification of Uncertainty Cases in Robots with Focus on Additive Manufacturing Technology: A Mini Review

Despite more than three decades since the beginning of Additive Manufacturing (AM), many challenges and issues prevent the industrialization of this technology. In fact, productivity is related to repetitive production of the same part under the same fabrication conditions. Currently, it is difficult to guarantee this repetitive production due to uncertainty issues, which represents the main obstacle of AM industrialization. In this paper, the uncertainty issues can be divided into two levels. The first level is related to the used AM machine itself which can be considered as robot of 3 degrees of freedom (x, y and z). In addition to its movement in three directions, this robot (AM machine) extrudes melted materials. The second level is related to the associated robots with 3D printing machines. In addition to summarizing some previous works and reviews, this mini review has the objective to provide new ideas to develop new strategies to overcome some uncertainty issues to contribute to the industrialization of AM technology. Furthermore, it paves the way to establish a concurrent AM / robotics loop in order to use AM for robotics and robotics for AM. The different developments should lead to elaborating Industrialization Standard for AM (IS4AM) where the different findings and recommendations can be classified in logical ways to deal with different AM techniques and materials.

Optimization of Triply Periodic Minimal Surface Heat Exchanger to Achieve Compactness, High Efficiency, and Low-Pressure Drop

With advancements in additive manufacturing (AM) techniques, high-quality triply periodic minimal surface (TPMS) structures can now be produced. TPMS walled heat exchangers (HX) hold significant potential for industrial applications and are receiving increasing attention. This paper explores the impact of various TPMS design variables on flow and thermal performance to optimize TPMS heat exchangers for compactness, high efficiency, and low pressure drop. The design variables examined include the type of TPMS lattice, unit cell size, wall thickness, aspect ratio, TPMS orientation, and equivalent thickness. The study reveals that the flow and heat transfer performance of TPMS structures are significantly affected by these design variables. For the Gyroid, Diamond, and SplitP lattices, performance is nearly identical when the surface-to-volume ratio is kept constant. The average velocity of the fluid in the TPMS HX should be 0.3 m/s. The corresponding Re is between 300~800. Thin wall thickness, small equivalent thickness, and flat lattice configurations can significantly reduce pressure drop while maintaining the overall heat transfer coefficient. Additionally, the angle between the flow direction and TPMS orientation can increase pressure drop. Three aluminum heat exchangers were successfully printed using an AM machine, and testing results are comparable with theoretical prediction.

Effects of Build Direction and Heat Treatment on the Defect Characterization and Fatigue Properties of Laser Powder Bed Fusion Ti6Al4V

Laser powder bed fusion (LPBF) is one of the high-precision additive manufacturing techniques for producing complex 3D components. It is well known that defects appear in additive-manufactured parts, and they deeply affect the fatigue properties; even heat treatment is performed after printing. In order to meet the safe-life design requirements of additive-manufactured aircraft structures, the effects of build direction and heat treatment on defects and fatigue properties need to be quantified. Hence, Ti6Al4V alloy samples with different build directions were designed and printed by LPBF. X-ray computed tomography was used to quantitatively analyze the defect size, the sphericity, and the defect orientation. And their effects on fatigue properties were studied. An extended effective defect size and a defect-based fatigue anisotropy evaluation process are proposed to qualify the effects of the defect size, sphericity, and defect orientation. It is shown that the build direction can affect the porosity distribution and maximum defect size, while the annealing treatment can cause the coalescence of small defects and higher porosity. The defect orientation exhibited a fluctuating trend of 0°–90°–0°–90°–0° as the volume increased. The elongated lack of fusion defects related to the build direction was the main crack source and could lead to fatigue anisotropy of LPBF Ti6Al4V.

Thermal fluctuations on the corrosion behaviour of 17-4PH stainless steel alloys fabricated via material extrusion additive manufacturing technique

Herein, the influence of fluctuating thermal conditions on the corrosion behaviour of 17-4PH stainless steel alloys manufactured via fused filament fabrication is reported. The printed samples were sintered and then exposed to different temperature-fluctuating conditions to simulate the application environment of such alloys. The first set of samples (A) was studied as-sintered, the second set of samples (B) was aged at 480°C for 3 h followed by quenching in water, the third set (C) was exposed to conditions of B followed by aging at 360°C for 3 h and quenching in water and the final set of samples (D) was exposed to conditions of C followed by aging at 200°C for 3 h, quenching in water, aging at 400°C for 3 h, and finally quenching in water. The surface roughness evolved with the temperature conditions. The optical microscopy revealed that sample B had a fine and homogenous distribution of precipitates. Sample B had the highest microhardness values followed by C, D, and A in that order. XRD analysis revealed the presence of retained FCC austenitic phases within the microstructure whose peaks became stronger with the increased thermal fluctuations. The potentiodynamic polarisation studies revealed a distinct linear Tafel region on the cathodic region and a dual-slope inflection point on the anodic region of the polarisation curves. Sample D exhibited the highest corrosion rate whereas sample B revealed the lowest. As such, exposing fused filament fabricated 17-4 PH SS to fluctuating temperature conditions leads to degradation of mechanical strength and corrosion resistance.

Minimally invasive detection of buprenorphine using a carbon-coated 3D-printed microneedle array.

Amachine learning-assisted 3D-printed conducting microneedle-based electrochemical sensing platformwas developed for wireless, efficient, economical, and selective determination of buprenorphine. The developed microneedle array-based sensing platform used 3D printing and air spray coating technologies for rapid and scalable manufacturing of a conducting microneedle surface. Upon optimization and understanding of the electrode stability, redox behavior, and electrochemical characteristics of as-prepared conducting microneedle array, the developed electrochemical platform was investigated for monitoring different levels of buprenorphine in the artificial intestinal fluid and found to be highly sensitive and selective towards buprenorphine for a wide detection range from 2 to 140μM, with a low limit of detection of 0.129μM. Furthermore, to make the sensing platform user accessible, the experimentally recorded sensing data was used to train a machine learning model and develop a web application for the numerical demonstration of buprenorphine levels at the point of site. Finally, the proof-of-concept study demonstrated that by advancing our prevailing 3D printing and additive manufacturing techniques, a low-cost, user-accessible, and compelling wearable electrochemical sensor could be manufactured for minimally invasive determination of buprenorphine in interstitial fluid.