Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing.

In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well-curated datasets, thereby unveiling latent knowledge crucial for informed decision-making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM-printed parts. This review delves into the challenges and opportunities emerging at the intersection of these two dynamic fields. It provides a comprehensive analysis of the publication landscape for ML-related research in the field of AM, explores common ML applications in AM research (such as quality control, process optimization, design optimization, microstructure analysis, and material formulation), and concludes by presenting an outlook that underscores the utilization of advanced ML models, the development of emerging sensors, and ML applications in emerging AM-related fields. Notably, ML has garnered increased attention in AM due to its superior performance across various AM-related applications. It is envisioned that the integration of ML into AM processes will significantly enhance 3D printing capabilities across diverse AM-related research areas.

Understanding droplet jetting on varying substrate for biological applications.

In the inkjet printing process, the droplet experience two phases, namely the jetting and the impacting phases. In this review article, we aim to understand the physics of a jetted ink, which begins during the droplet formation process. Following which, we highlight the different impacts during which the droplet lands on varying substrates such as solid, liquid, and less commonly known viscoelastic material. Next, the article states important process-specific considerations in determining the success of inkjet bioprinted constructs. Techniques to reduce cell deformation throughout the inkjet printing process are highlighted. Modifying postimpact events, such as spreading, evaporation, and absorption, improves cell viability of printed droplet. Last, applications that leverage on the advantage of pixelation in inkjet printing technology have been shown for drug screening and cell-material interaction studies. It is noteworthy that inkjet bioprinting technology has been integrated with other processing technologies to improve the structural integrity and biofunctionality of bioprinted construct.

Anomaly Detection in Fused Filament Fabrication Using Machine Learning.

Fused filament fabrication (FFF) has been widely used in various industries, and the adoption of technology is growing significantly. However, the FFF process has several disadvantages like inconsistent part quality and print repeatability. The occurrence of manufacturing-induced defects often leads to these shortcomings. This study aims to develop and implement an on-site monitoring system, which consists of a camera attached to the print head and the laptop that processes the video feed, for the extrusion-based 3D printers incorporating computer vision and object detection models to detect defects and make corrections in real-time. Image data from two classes of defects were collected to train the model. Various YOLO architectures were evaluated to study the ability to detect and classify printing anomalies such as under-extrusion and over-extrusion. Four of the trained models, YOLOv3 and YOLOv4 with "Tiny" variation, achieved a mean average precision score of >80% using the AP50 metric. Subsequently, two of the models (YOLOv3-Tiny 100 and 300 epochs) were optimized using Open Neural Network Exchange (ONNX) model conversion and ONNX Runtime to improve the inference speed. A classification accuracy rate of 89.8% and an inference speed of 70 frames per second were obtained. Before implementing the on-site monitoring system, a correction algorithm was developed to perform simple corrective actions based on defect classification. The G-codes of the corrective actions were sent to the printers during the printing process. This implementation successfully demonstrated real-time monitoring and autonomous correction during the FFF 3D printing process. This implementation will pave the way for an on-site monitoring and correction system through closed-loop feedback from other additive manufacturing (AM) processes.

The Design and Development of Instrumented Toys for the Assessment of Infant Cognitive Flexibility.

The first years of an infant's life represent a sensitive period for neurodevelopment where one can see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction. Besides being extremely time-consuming, video annotation is known to be rater-dependent and subjective. To address these issues, starting from existing cognitive flexibility research protocols, we developed a set of instrumented toys to serve as a new type of task instrumentation and data collection tool suitable for infant use. A commercially available device comprising a barometer and an inertial measurement unit (IMU) embedded in a 3D-printed lattice structure was used to detect when and how the infant interacts with the toy. The data collected using the instrumented toys provided a rich dataset that described the sequence of toy interaction and individual toy interaction patterns, from which EF-relevant aspects of infant cognition can be inferred. Such a tool could provide an objective, reliable, and scalable method of collecting early developmental data in socially interactive contexts.

Machine Learning for Bioelectronics on Wearable and Implantable Devices: Challenges and Potential.

Bioelectronics presents a promising future in the field of embedded and implantable electronics, providing a range of functional applications, from personal health monitoring to bioactuators. However, due to the intrinsic difficulties present in producing and optimizing bioelectronics, recent research has focused on utilizing machine learning (ML) to reliably mitigate such issues and aid in process development. This review focuses on the recent developments of integrating ML into bioelectronics, aiding in a multitude of areas, such as material development, fabrication process optimization, and system integration. First, discussing how ML has aided in the material development by identifying complex relationships between process input parameters and desired outputs, such as product design. Second, examine the advancements in ML to accurately optimize fabrication precision and stability for various 3D printing technologies. Third, provide an overview of how ML can greatly assist in the analysis of complex, nonlinear relationships in data obtained from bioelectronics. Lastly, a summary of the challenges present with utilizing ML with bioelectronics and any other developments in this field. Such advancements in the field of bioelectronics and ML could hopefully build a strong foundation for this research field, promoting smart optimization together with effective use of ML to further enhance the effectiveness of such applications. Impact statement The article serves to give insight about the use of the machine learning (ML) techniques in the field of bioelectronics, since bioelectronics and ML are two distinct fields. This article allows bioelectronics researcher to get to know the latest advancement in the ML field. On the other hand, the article provides an insight to the ML researchers about how ML techniques can be useful in bioelectronics applications.

Students' learning experiences of three-dimensional printed models and plastinated specimens: a qualitative analysis.

BACKGROUND: Traditional cadaveric dissection is declining whilst plastinated and three-dimensional printed (3DP) models are increasingly popular as substitutes to the conventional anatomy teaching and learning methods. It is unclear about the pros and cons of these new tools and how they impact students' learning experiences of anatomy including humanistic values such as respect, care and empathy.  METHODS: Ninety-six students' views were sought immediately after a randomized cross-over study. Pragmatic design was used to investigate the learning experiences of using plastinated and 3DP models of cardiac (in Phase 1, n = 63) and neck (in Phase 2, n = 33) anatomy. Inductive thematic analysis was conducted based on 278 free text comments (related to strengths, weaknesses, things to improve), and focus group (n = 8) transcriptions in full verbatim about learning anatomy with these tools. RESULTS: Four themes were found: perceived authenticity, basic understanding versus complexity, attitudes towards respect and care, and multimodality and guidance. CONCLUSIONS: Overall, students perceived plastinated specimens as more real and authentic, thus perceived more respect and care than 3DP models; whereas 3DP models were easy to use and prefered for learning basic anatomy.

Improving printability of hydrogel-based bio-inks for thermal inkjet bioprinting applications via saponification and heat treatment processes.

Material jetting bioprinting is a highly promising three-dimensional (3D) bioprinting technique that facilitates drop-on-demand (DOD) deposition of biomaterials and cells at pre-defined positions with high precision and resolution. A major challenge that hinders the prevalent use of the material jetting bioprinting technique is due to its limited range of printable hydrogel-based bio-inks. As a proof-of-concept, further modifications were made to gelatin methacrylate (GelMA), a gold-standard bio-ink, to improve its printability in a thermal inkjet bioprinter (HP Inc. D300e Digital Dispenser). A two-step modification process comprising saponification and heat treatment was performed; the GelMA bio-ink was first modified via a saponification process under highly alkali conditions to obtain saponified GelMA (SP-GelMA), followed by heat treatment via an autoclaving process to obtain heat-treated SP-GelMA (HSP-GelMA). The bio-ink modification process was optimized by evaluating the material properties of the GelMA bio-inks via rheological characterization, the bio-ink crosslinking test, nuclear magnetic resonance (NMR) spectroscopy and the material swelling ratio after different numbers of heat treatment cycles (0, 1, 2 and 3 cycles). Lastly, size-exclusion chromatography with multi-angle light scattering (SEC-MALS) was performed to determine the effect of heat treatment on the molecular weight of the bio-inks. In this work, the 4% H2SP-GelMA bio-inks (after 2 heat treatment cycles) demonstrated good printability and biocompatibility (in terms of cell viability and proliferation profile). Furthermore, thermal inkjet bioprinting of the modified hydrogel-based bio-ink (a two-step modification process comprising saponification and heat treatment) via direct/indirect cell patterning is a facile approach for potential fundamental cell-cell and cell-material interaction studies.

Recent Progress in Research of Additive Manufacturing for Polymers.

Additive manufacturing (AM) methods have grown and evolved rapidly in recent years [...].

Use of Fumed Silica Nanostructured Additives in Selective Laser Melting and Fabrication of Steel Matrix Nanocomposites.

The advancement of additive manufacturing (AM) for metal matrix nanocomposites (MMNCs) is gaining enormous attention due to their potential improvement of physical and mechanical performance. When using nanostructured additives as reinforcements in 3D printed metal composites and with the aid of selective laser melting (SLM), the mechanical properties of the composites can be tailored. The nanostructured additive AEROSIL® fumed silica is both cost-effective and beneficial in the production of MMNCs using SLM. In this study, both hydrophobic and hydrophilic fumed silicas were shown to successfully achieve homogenous blends with commercial 316L stainless steel powder. The powder blends, which exhibited better flow, were then used to fabricate samples using SLM. The samples' microstructure demonstrated that smaller grains were present in the composites, resulting in improvements in mechanical properties by grain refinement compared to those of 316L stainless steel samples.

Controlling Droplet Impact Velocity and Droplet Volume: Key Factors to Achieving High Cell Viability in Sub-Nanoliter Droplet-based Bioprinting.

Three-dimensional (3D) bioprinting systems serve as advanced manufacturing platform for the precise deposition of cells and biomaterials at pre-defined positions. Among the various bioprinting techniques, the drop-on-demand jetting approach facilitates deposition of pico/nanoliter droplets of cells and materials for study of cell-cell and cell-matrix interactions. Despite advances in the bioprinting systems, there is a poor understanding of how the viability of primary human cells within sub-nanoliter droplets is affected during the printing process. In this work, a thermal inkjet system is utilized to dispense sub-nanoliter cell-laden droplets, and two key factors - droplet impact velocity and droplet volume - are identified to have significant effect on the viability and proliferation of printed cells. An increase in the cell concentration results in slower impact velocity, which leads to higher viability of the printed cells and improves the printing outcome by mitigating droplet splashing. Furthermore, a minimum droplet volume of 20 nL per spot helps to mitigate evaporation-induced cell damage and maintain high viability of the printed cells within a printing duration of 2 min. Hence, controlling the droplet impact velocity and droplet volume in sub-nanoliter bioprinting is critical for viability and proliferation of printed human primary cells.

Preliminary Investigation on the Geometric Accuracy of 3D Printed Dental Implant Using a Monkey Maxilla Incisor Model.

Additive manufacturing has proven to be a viable alternative to conventional manufacturing methodologies for metallic implants due to its capability to customize and fabricate novel and complex geometries. Specific to its use in dental applications, various groups have reported successful outcomes for customized root-analog dental implants in preclinical and clinical studies. However, geometrical accuracy of the fabricated samples has never been analyzed. In this article, we studied the geometric accuracy of a 3D printed titanium dental implant design against the tooth root of the monkey maxilla incisor. Monkey maxillas were scanned using cone-beam computed tomography, then segmentation of the incisor tooth roots was performed before the fabrication of titanium dental implants using a laser powder bed fusion (PBF) process. Our results showed 68.70% ± 5.63 accuracy of the 3D printed dental implant compared to the actual tooth (n = 8), where main regions of inaccuracies were found at the tooth apex. The laser PBF fabrication process of the dental implants showed a relatively high level of accuracy of 90.59% ± 4.75 accuracy (n = 8). Our eventual goal is to develop an accurate workflow methodology to support the fabrication of patient-specific 3D-printed titanium dental implants that mimic patients' tooth anatomy and fit precisely within the socket upon tooth extraction. This is essential for promoting primary stability and osseointegration of dental implants in the longer term.

Emerging Materials for Additive Manufacturing.

Additive manufacturing (AM) has grown and evolved rapidly in recent years [...].

Tissue engineering and 3D printing of bioartificial pancreas for regenerative medicine in diabetes.

Diabetes is a severe chronic disease worldwide. In various types of diabetes, the pancreatic beta cells fail to secrete sufficient insulin, at some point, to regulate blood glucose levels. Therefore, the replacement of dysfunctional pancreas, islets of Langerhans, or even the insulin-secreting beta cells facilitates physiological regulation of blood glucose levels. However, the current lack of sufficient donor human islets for cell replacement therapy precludes a routine and absolute cure for most of the existing diabetes cases globally. It is envisioned that tissue engineering of a bioartificial pancreas will revolutionize regenerative medicine and the treatment of diabetes. In this review, we discuss the anatomy and physiology of the pancreas, and identify the clinical considerations for engineering a bioartificial pancreas. Subsequently, we dissect the bioengineering problem based on the design of the device, the biomaterial used, and the cells involved. Last but not least, we highlight current tissue engineering challenges and explore potential directions for future work.

Fabrication and Characterization of 3D Bioprinted Triple-layered Human Alveolar Lung Models.

The global prevalence of respiratory diseases caused by infectious pathogens has resulted in an increased demand for realistic in-vitro alveolar lung models to serve as suitable disease models. This demand has resulted in the fabrication of numerous two-dimensional (2D) and three-dimensional (3D) in-vitro alveolar lung models. The ability to fabricate these 3D in-vitro alveolar lung models in an automated manner with high repeatability and reliability is important for potential scalable production. In this study, we reported the fabrication of human triple-layered alveolar lung models comprising of human lung epithelial cells, human endothelial cells, and human lung fibroblasts using the drop-on-demand (DOD) 3D bioprinting technique. The polyvinylpyrrolidone-based bio-inks and the use of a 300 mm nozzle diameter improved the repeatability of the bioprinting process by achieving consistent cell output over time using different human alveolar lung cells. The 3D bioprinted human triple-layered alveolar lung models were able to maintain cell viability with relative similar proliferation profile over time as compared to non-printed cells. This DOD 3D bioprinting platform offers an attractive tool for highly repeatable and scalable fabrication of 3D in-vitro human alveolar lung models.

Process-Structure-Properties in Polymer Additive Manufacturing.

Additive manufacturing (AM) methods have grown and evolved rapidly in recent years [...].

High-Resolution Novel Indirect Bioprinting of Low-Viscosity Cell-Laden Hydrogels via Model-Support Bioink Interaction.

Bioprinting of unmodified soft extracellular matrix into complex 3D structures has remained challenging to fabricate. Herein, we established a novel process for the printing of low-viscosity hydrogel by using a unique support technique to retain the structural integrity of the support structure. We demonstrated that this process of printing could be used for different types of hydrogel, ranging from fast crosslinking gelatin methacrylate to slow crosslinking collagen type I. In addition, we evaluated the biocompatibility of the process by observing the effects of the cytotoxicity of L929 and the functionality of the human umbilical vein endothelium primary cells after printing. The results show that the bioprinted construct provided excellent biocompatibility as well as supported cell growth and differentiation. Thus, this is a novel technique that can be potentially used to enhance the resolution of the extrusion-based bioprinter.

Bioprinting of Collagen: Considerations, Potentials, and Applications.

Collagen is the most abundant extracellular matrix protein that is widely used in tissue engineering (TE). There is little research done on printing pure collagen. To understand the bottlenecks in printing pure collagen, it is imperative to understand collagen from a bottom-up approach. Here it is aimed to provide a comprehensive overview of collagen printing, where collagen assembly in vivo and the various sources of collagen available for TE application are first understood. Next, the current printing technologies and strategy for printing collagen-based materials are highlighted. Considerations and key challenges faced in collagen printing are identified. Finally, the key research areas that would enhance the functionality of printed collagen are presented.

3D Printed Silicone Meniscus Implants: Influence of the 3D Printing Process on Properties of Silicone Implants.

Osteoarthritis of the knee with meniscal pathologies is a severe meniscal pathology suffered by the aging population worldwide. However, conventional meniscal substitutes are not 3D-printable and lack the customizability of 3D printed implants and are not mechanically robust enough for human implantation. Similarly, 3D printed hydrogel scaffolds suffer from drawbacks of being mechanically weak and as a result patients are unable to execute immediate post-surgical weight-bearing ambulation and rehabilitation. To solve this problem, we have developed a 3D silicone meniscus implant which is (1) cytocompatible, (2) resistant to cyclic loading and mechanically similar to native meniscus, and (3) directly 3D printable. The main focus of this study is to determine whether the purity, composition, structure, dimensions and mechanical properties of silicone implants are affected by the use of a custom-made in-house 3D-printer. We have used the phosphate buffer saline (PBS) absorption test, Fourier transform infrared (FTIR) spectroscopy, surface profilometry, thermo-gravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM) to effectively assess and compare material properties between molded and 3D printed silicone samples.

Engineering macroscale cell alignment through coordinated toolpath design using support-assisted 3D bioprinting.

Aligned cells provide direction-dependent mechanical properties that influence biological and mechanical function in native tissues. Alignment techniques such as casting and uniaxial stretching cannot fully replicate the complex fibre orientation of native tissue such as the heart. In this study, bioprinting is used to direct the orientation of cell alignment. A 0°-90° grid structure was printed to assess the robustness of the support-assisted bioprinting technique. The variation in the angles of the grid pattern is designed to mimic the differences in fibril orientation of native tissues, where angles of cell alignment vary across the different layers. Through bioprinting of a cell-hydrogel mixture, C2C12 cells displayed directed alignment along the longitudinal axis of printed struts. Cell alignment is induced through firstly establishing structurally stable constructs (i.e. distinct 0°-90° structures) and secondly, allowing cells to dynamically remodel the bioprinted construct. Herein reports a method of inducing a macroscale level of controlled cell alignment with angle variation. This was not achievable both in terms of methods (i.e. conventional alignment techniques such as stretching and electrical stimulation) and magnitude (i.e. hydrogel features with less than 100 µm features).

Laser powder bed fusion of titanium-tantalum alloys: Compositions and designs for biomedical applications.

In this study, laser powder bed fusion (L-PBF), also known as selective laser melting (SLM), was used to fabricate samples of titanium-tantalum (TiTa) alloys with 0, 10, 30 and 50 wt% of tantalum using in-situ alloying. As-fabricated samples comprised of randomly-dispersed pure tantalum particles in a titanium-tantalum matrix. Porosity and unmelted tantalum particles of the samples were revealed using an optical microscope (OM). The microstructure of the alloys were determined by combination of field emission scanning electron microscopy (FE-SEM), electron back scatter diffraction (EBSD) and X-ray diffraction (XRD). The mechanical properties of the alloys were investigated with tensile and Vickers hardness tests. To ascertain the suitability of these alloys as biomaterials, Ti50Ta scaffolds with 60% porosity were characterized biologically. This study further shows that porous TiTa scaffolds fabricated using L-PBF are biocompatible with comparable biological results and manufacturability as Ti6Al4V and commercially pure titanium, based on the results obtained from cell culture with human osteosarcoma cell line SAOS-2.