Additive Manufacturing Applications Research Articles

Excipients in Pharmaceutical Additive Manufacturing: A Comprehensive Exploration of Polymeric Material Selection for Enhanced 3D Printing.

This review provides a comprehensive overview of additive manufacturing (AM) or 3D-printing (3DP) applications in the pharmaceutical industry, with a particular focus on the critical role of polymer selection. By providing insights into how material properties influence the 3DP process and the quality of the final product, this review aims to contribute to a better understanding of the interplay between polymers and pharmaceutical 3DP. As 3DP technologies are increasingly integrated into pharmaceutical sciences, this review contributes insights into the nuanced process of polymer selection, serving mainly as a foundational guide for researchers and formulators new to the subject seeking to harness the full potential of pharmaceutical 3DP by understanding the physicochemical properties, roles, and functions of used polymers in 3D-printed dosage forms and medical devices.

Wire Based Directed Energy Deposition of JBK-75

Applications and adoption of metal additive manufacturing (AM) are increasing for fabrication of low volume, complex components with novel materials, as well as replacement parts. While the use of powder bed fusion-based processes have been widely used to build complex components with fine feature resolution, there is a volume limitation. Expanding the application of metal AM will rely on other processes that remove this build size constraint. These processes are referred to as Directed Energy Deposition (DED) and can use either powder or wire feedstock. Wire based DED provides the highest deposition rates which shortens the fabrication time making it attractive for fabrication of large parts replacing traditional wrought billets or castings. In this study, an iron-based austenitic superalloy (JBK-75) was deposited using an arc-based, wire-fed (AW)-DED process. The material was metallographically characterized and quasi-static mechanical properties were obtained. The resulting microstructure and mechanical properties are compared with conventional wrought and cast forms of JBK-75 subjected to the same heat treatments. As compared to wrought material, the AW-DED grain size was larger after the heat treatment, although the strengths were similar. Improved homogenization was observed after heat treatment in the AW-DED specimens as compared to the cast specimens.

Efficient bead-on-plate weld model for parameter estimation towards effective wire arc additive manufacturing simulation

AbstractDespite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a bead-on-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.

Technological Advances in Mechanical Recycling Innovations and Corresponding Impacts on the Circular Economy of Plastics

The impact of plastic pollution on the world and its inhabitants is yet to be fully measured. Significant quantities of microplastics and nanoplastics have been found in human organs, and many diseases have been traced to their presence. Even human placentas have been found to contain microplastics. This study examines the recycling landscape, advanced reprocessing techniques, and technical challenges in this industry. It points out the top recyclable types of plastics (such as high-density polyethylene, polyethylene terephthalate, and thermoplastic elastomers) by analyzing their different recycling capacities globally. It highlights the most advisable recycling techniques by identifying those most successful, least environmentally damaging, and easiest. Mechanical recycling is arguably the easiest and most common recycling technique. This study examines mechanical reprocessing technologies for construction materials, composite boards, additive manufacturing, and other applications. It also points out prevailing setbacks of these approaches and analyzes different solutions. Promising recycling processes are suggested for further investigation.

Failure of 3D-printed composite continuous carbon fibre hexagonal frames

This study presents an approach to enhancing and expanding the structural performance of composite materials by tailoring their geometry. We explored the potential of continuous carbon fibre composite additive printing to create complaint frames based on hexagonal cell design with the aim to better understand and control their mechanical performance. Our investigation examines the failure behaviour of these frames under remote tensile loading. By experimenting with various geometries and aspect ratios at the frame sites, we gained insight into different failure loads and modes. To predict these results, we developed a computational model based on multiscale homogenisation and the Hashin damage criterion, which showed a high degree of precision compared to our experimental results. The findings validate the effectiveness of our computational model, but also highlight the practical applications of additive manufacturing of composites. This research aims to contribute to the advancement of structural design and material optimisation by engineering of composite materials for specific applications, emphasising the integration of their intrinsic strength and lightweight properties with material efficiency and compliance achieved through geometric design considerations.

Large‐Area, High‐Numerical‐Aperture, Freeform Metasurfaces

AbstractNanophotonic devices are optical platforms capable of unprecedented wavefront control. To push the limits of experimental device performance, scalable design methodologies that combine the simplicity and fabricability of conventional design paradigms with the extended capabilities of freeform optimization are required. A novel gradient‐based design framework for large‐area freeform metasurfaces is introduced in which nonlocal interactions between simply shaped nanostructures, placed on an irregular lattice, are tailored to produce high‐order hybridized modes that support customizable large‐angle scattering profiles. Utilizing this approach, multifunctional super‐dispersive metalenses are designed and experimentally demonstrated. The approach to high‐numerical‐aperture radial metalenses capable of diffraction limited focusing and the generation of donut‐shaped point spread functions is also extended. It is anticipated that these concepts will have utility in super‐resolution microscopy, particle trapping, additive manufacturing, and metrology applications that require ultra‐high numerical apertures.

New insights into the mechanism of ultrasonic atomization for the production of metal powders in additive manufacturing

Ultrasonic atomization is one of the promising technologies for producing metal powders for additive manufacturing, where precise control of particle size and morphology is essential. In this study, we coupled an ultrasonic transducer with a carbon fiber plate and atomized liquid droplets and films under different vibration amplitudes. Water, glycerol, and pure aluminum melt were used to study the atomization mechanism and the resulting droplet/powder characteristics, respectively. High-speed optical and ultrafast synchrotron X-ray imaging were used to study in situ the ultrasonic atomization dynamics, including pulsation and clustering of cavities inside the liquid layer/films, development of capillary waves, and formation of liquid droplets. For the first time, we observed and captured the occurrence of cavitation during the atomization of resting drops, films and impact droplets. The inertial cavitation events interfered with the capillary waves across the interphase boundary, puncturing and breaking the boundary to produce atomized mist. The in situ observation revealed the intricate dynamics of ultrasonic atomization and underscored the pivotal role of cavitation events throughout the entire atomization process. We also conducted experiments on ultrasonic atomization of liquid aluminum, producing particles of perfectly spherical shape. The particle size tended to decrease with reduced vibration amplitude Our work has demonstrated the important processing strategies on how to tailor the particle size while ensuring consistent particle shape and morphology, which is the key processing capability for producing high quality powders for additive manufacturing applications.

A practical algorithm for the design of multiple-sized porous scaffolds with triply periodic structures

In this study, we present a practical volume-merging method for generating multiple-sized porous structures that exhibit geometries with triply periodic minimal surface (TPMS) lattice structures. The proposed method consists of three stages: (1) designing the physical models with a signed distance field, (2) performing a merging operation for the porous scaffolds, and (3) assembling different units into a composite structure. The significant advantages of the proposed algorithm can be summarized as follows: Our method is independent of the model shape; the designed structures maintain a smooth surface with a constant mean curvature, and the mathematical computational complexity is low. We can join two different-sized triply periodic minimal surface lattices in the radial direction, where the transition region is obtained by smooth interpolation between the two lattice structures with different cell sizes or types. However, constructing large-sized models is only conceptually possible due to computational cost and memory storage constraints. To overcome these limitations, we present a practical method that can efficiently assemble large-scaled models at a low computational cost. The proposed method is based on a Boolean union operation of basic units of TPMS. Thus, it is simple to generate large-scale three-dimensional multiple-sized porous volumes based on our proposed method, which can be applied to many applications in mechanical and electrical engineering. The produced multi-scale compound scaffolds have smooth surfaces without fractures, making them suitable for straightforward application in additive manufacturing. Several numerical tests are conducted to validate the efficiency of the proposed algorithm.

Deep Gaussian process for enhanced Bayesian optimization and its application in additive manufacturing

ABSTARCT Engineering design problems typically require optimizing a quality measure by finding the right combination of controllable input parameters. In Additive Manufacturing (AM), the output characteristics of the process can often be non-stationary functions of the process parameters. Bayesian Optimization (BO) is a methodology to optimize such “black-box” functions, i.e., the input–output relationship is unknown and expensive to compute. Optimization tasks involving “black-box” functions widely use BO with Gaussian Process (GP) regression surrogate model. Using GPs with standard kernels is insufficient for modeling non-stationary functions, while GPs with non-stationary kernels are typically over-parameterized. On the other hand, a Deep Gaussian Process (DGP) can overcome GPs’ shortcomings by considering a composition of multiple GPs. Inference in a DGP is challenging due to its structure resulting in a non-Gaussian posterior, and using DGP as a surrogate model for BO is not straightforward. Stochastic Imputation (SI)-based inference is promising in speed and accuracy for BO. This work proposes a bootstrap aggregation-based procedure to effectively utilize the SI-based inference for BO with a DGP surrogate model. The proposed BO algorithm DGP-SI-BO is faster and empirically better than the state-of-the-art BO method in optimizing non-stationary functions. Several analytical test functions and a case study in metal AM simulation demonstrate the applicability of the proposed method.

Metal Additive Manufacturing (MAM) Applications in Production of Vehicle Parts and Components—A Review

In this article, the significance of additive manufacturing techniques in the production of vehicle parts over the past several years is highlighted. It indicates the industries and scientific sectors in which these production techniques have been applied. The primary manufacturing methods are presented based on the materials used, including both metals and non-metals. The authors place their primary focus on additive manufacturing techniques employing metals and their alloys. Within this context, they categorize these methods into three main groups: L-PBF (laser-powder bed fusion), sheet lamination, and DED (directed energy deposition) techniques. In the subsequent stages of work on this article, specific examples of vehicle components produced using metal additive manufacturing (MAM) methods are mentioned.

Recent Advances in Preceramic Polysilazane Precursors in Additive Manufacturing

Si3N4/SiCN ceramics have been extensively explored for applications in the aerospace, mechanical engineering, and biomedical fields. Recently, there has been significant focus on the additive manufacturing (AM) of polymer-derived ceramic (PDC) technology for fabricating Si3N4/SiCN ceramics. The chemical structure and composition of the preceramic polymer precursors have a crucial influence on the performance of ceramic products. In this paper, recent advances in the use of polysilazane and polycarbosilazane precursors in AM are reviewed and an outlook for future development is presented. The findings of this study could spark inspiration and reflection regarding AM applications and synthetic technology. It is believed that the development of PDCs in ceramic fabrication will become more versatile and application-oriented and provide more freedom in the design of high-performance ceramics.

TECHNOLOGY OF ADDITIVE MANUFACTURING: A COMPREHENSIVE REVIEW

The process of additive manufacturing (AM), commonly known as 3D printing, is a method of constructing a component by progressively adding material in layers using digital 3D design information. As part of 'Industry 4.0,' many industrial technologies are rapidly increasing to thrive in the twenty-first century. This study goes over seven different types of additive manufacturing in great detail. These technologies make it possible to make complex, high-value parts quickly and in small quantities without using as much energy or material or making as many tools as subtractive manufacturing does. Besides, AM also possesses some particular challenges, like post-processing, material unavailability, software issues, etc. The application of AM is expanding rapidly from micro to macro-scale sectors. 3D printing technology will change industrial operations in the following years. Eventually, the elected technology will be closely related to the proposed function.

Effect of raster angle on the fracture properties of additively manufactured ABS via essential work of fracture

AbstractThe increasing application of additive manufacturing (AM) technology across various sectors has sparked significant interest in characterizing 3D‐printed components. An essential aspect of achieving fracture‐resistant designs is gaining a comprehensive understanding of the fracture behavior exhibited by these components. While most studies have focused on linear‐elastic fracture mechanics (LEFM), there is a lack of comprehensive studies on the post‐yield fracture behavior (PYFM) of 3D‐printed components. As a result, this study aims to fill this gap by investigating the impact of raster angle, a critical parameter influencing fracture properties and often leading to premature failures, on the fracture properties of fused deposition modeling (FDM) 3D printed acrylonitrile butadiene styrene (ABS) using essential work of fracture (EWF). Outcomes showed that by changing lay‐ups from [90]5 to [0]5, the value of we or elastic work increased by nearly 306%. Further, the maximum and minimum values of the plastic work (βwp) were for [45/−45/45/−45/45] and [90]5 lay‐ups, in order. By changing lay‐ups from [90]5 to [45/−45/45/−45/45], the value of βwp increased by approximately 216%. In addition, the fractured surfaces of tested samples are also analyzed to provide insights into the dominant failure mechanisms for different raster angles.

Modulation of characteristic zones in NiTi alloys fabricated via wire arc additive manufacturing

The application of additive manufacturing (AM) is gradually extending to different industrial sectors. Most additively manufactured metallic components typically exhibit an inherent columnar grain structure, the control of which has been a challenging issue. In this study, the microstructures of the characteristic zones (heat-affected zone and transition zone) were controlled by adjusting the deposition strategy and arc mode during wire arc additive manufacturing (WAAM) of NiTi alloy. Compared to the sample fabricated by cold metal transfer (CMT) mode, the oscillating (O) sample shows a higher tensile strength of 793.6 MPa, while the pulsed (P) sample shows a better elongation of 5.8%. The high strength of the O samples is mainly due to the significantly lower aspect ratio of its columnar grains, while fine equiaxed grain structure in the transition zone of the P samples is responsible for the better plasticity. Different microstructures in the characteristic zones can be tailored by combining the forced melt flow, pulse frequency and undercooling, which provides vast freedom for the associated mechanical properties control. Our work provides a new strategy to regulate the microstructure and thus mechanical properties of additively manufactured NiTi alloys.

Additive Manufacturing Applications in Biosensors Technologies.

Three-dimensional (3D) printing technology, also known as additive manufacturing (AM), has emerged as an attractive state-of-the-art tool for precisely fabricating functional materials with complex geometries, championing several advancements in tissue engineering, regenerative medicine, and therapeutics. However, this technology has an untapped potential for biotechnological applications, such as sensor and biosensor development. By exploring these avenues, the scope of 3D printing technology can be expanded and pave the way for groundbreaking innovations in the biotechnology field. Indeed, new printing materials and printers would offer new possibilities for seamlessly incorporating biological functionalities within the growing 3D scaffolds. Herein, we review the additive manufacturing applications in biosensor technologies with a particular emphasis on extrusion-based 3D printing modalities. We highlight the application of natural, synthetic, and composite biomaterials as 3D-printed soft hydrogels. Emphasis is placed on the approach by which the sensing molecules are introduced during the fabrication process. Finally, future perspectives are provided.

Thermal Plasma Spheroidization and Characterization of Stainless Steel Powders Using Direct Current Plasma Technology

The production of spherical powders has recently registered a boost due to the need to fabricate new printing materials for Additive Manufacturing applications, from polymers and resins to metals and ceramics. Among these materials, stainless steels powders play a leading role, since they are widely used in industry and everyday life; indeed, micron-sized spherical stainless steel powders have specific characteristics and are considered as one of the best candidates for Additive Manufacturing systems and for application in a wide range of sectors. In this paper, stainless steel 316 L powders were used to explore and identify the best process parameters of a thermal plasma process able to produce spherical powders for Additive Manufacturing applications. X-ray Diffraction, Scanning Electron Microscopy, Particle Size Distribution and Flowability analysis were performed to characterize reagents and products. Powders with a high circularity (>0.8) and improved flowability (<30 s/50 g) were successfully obtained. The collected results were compared with data available from the literature to identify the potential use of the spherical produced powders.

Harnessing disulfide and transesterification bond exchange reactions for recyclable and reprocessable 3D-printed vitrimers

Two new vitrimeric materials have been studied for potential additive manufacturing applications such as 3D-printing. A monomer containing disulfide bonds and β-hydroxyesters was easily synthesized from two low-cost and commercially available reagents. Another disulfide-containing monomer was synthesized for comparison purposes. Materials were prepared through a UV-light radical polymerization of methacrylates. The addition of two reactive diluents such as poly(ethylene glycol) methyl ether methacrylate (PEGMA) and ethylene glycol phenyl ether methacrylate (EGPMA) was necessary to achieve a suitable viscosity for the curing as well as for their printability. The curing process was controlled by FTIR. Thermomechanical properties were investigated by means of DMTA analysis revealing near-ambient Tg values. Stress relaxation tests revealed that both materials were capable to relax the 63% of the initial stress in less than 10 min at 110 °C. The recyclability of the materials was achieved, and the mechanical and thermomechanical properties of the recycled samples were compared to the virgin ones revealing a great recovery of the initial properties. Finally, Digital Light Processing (DLP) technique was used to print complex structures with high resolution highlighting the great potential of these vitrimeric materials in 3D printing.

Investigating the impact of infill patterns on shape memory effect in material extrusion

Extensive research has been conducted on Shape Memory Polymers (SMPs) for their potential application in additive manufacturing. The Shape Memory Effect (SME), a key attribute of SMPs, enables 3D-printed objects to alter their shape in response to external stimuli. Several methods for programming SMEs have been explored, such as modifying printing parameters like infill patterns or density. However, incorporating SMPs as substitutes for conventional functional components has been challenging due to grafting difficulties and the limited reliability of SMEs. In this research, the influence of internal structures on SMEs is examined by comparing the full shape recovery period. This investigation has revealed the impact of different infill structures on SMEs and uncovered a complex shape recovery pattern termed multi-phased SME. This occurs when straight infill structures are nearly parallel along the length of a cuboid specimen that has been programmed to form a 90° curve. This finding enhances the creation of complex shape recovery behaviours by simply modifying printing parameters and is applicable to a variety of SMPs.

Challenges with application of additive manufacturing in energy sector

Additive manufacturing (AM) is treated as a significant contributor to sustainability due to lower energy consumption, less material usage and reduced number of wastes generated when comparing with traditional manufacturing technologies. Currently there is a lot of commercial applications of such new technology in number of industry segments. However, such sector as high voltage engineering still struggles with number of challenges when considering additive manufacturing. In products working in high voltage environment, very often, in addition to mechanical loads there are demanding conditions, as elevated temperature and presence of insulation oil or gas. This requires a special approach to printing quality of the printed structures without internal voids and in case of metals, with improved electrical conductivity. In the paper, few examples of additive manufacturing applications in area of power products have been presented, including printed transformer insulation, printed copper, and application of AM for spare parts. For each case, the main challenges have been discussed.

An Ontology-based Knowledge Modeling towards Eco-Design for Additive Manufacturing

Owing to the unique technological merits of additive manufacturing (AM), design for AM, particularly eco-design for AM, has been gaining attention in improving the sustainable performance of AM-fabricated (AMed) parts. The main challenge in harvesting potential sustainability benefits is how to capture the impact of design on sustainable performance. Though several existing studies adopted quantitative evaluation on AM sustainability and investigated the relationships between design information and sustainability information of AMed part, the sustainability information is still unavailable in the design phase. This hardly guides eco-design for AM in practice. To support the increasing industrial applications of AM, this paper illustrates related knowledge, that is, material-process-structure-ecoProperty (MPSeP) relationships to connect design and sustainability information in eco-design for AM. An ontology-based method is proposed to model the MPSeP relationships of the AMed part in a structured way. An example of an AMed hydraulic valve body was used to demonstrate the MPSeP modeling process. It is discussed that how the constructed model effectively assists AM designers through providing eco-design recommendation, and enables design software tools to perform sustainability analysis towards eco-design for AM.