Probing Ink-Powder Interactions during 3D Binder Jet Printing Using Time-Resolved X-ray Imaging

Enhancing Quality Control: Image-Based Quantification of Carbides and Defect Remediation in Binder Jetting Additive Manufacturing

While binder jetting (BJ) additive manufacturing (AM) holds considerable promise for industrial applications, defects often compromise part quality. This study addresses these challenges by investigating binding mechanisms and analyzing common defects, proposing tailored solutions to mitigate them. Emphasizing defect identification for effective quality control in BJ-AM, this research offers strategies for in-process rectification and post-process evaluation to elevate part quality. It shows how to successfully process metallic parts with complex geometries while maintaining consistent material properties. Furthermore, the paper explores the microstructure of AISI M2 tool steel, utilizing advanced image processing techniques like digital image analysis and SEM images to evaluate carbide distribution. The results show that M2 tool steel has a high proportion of M6C carbides, with furnace-cooled samples ranging from ~2.4% to 7.1% and MC carbides from ~0.4% to 9.4%. M6C carbides ranged from ~2.6% to 3.8% in air-cooled samples, while water-cooled samples peaked at ~8.52%. Sintering conditions also affected shrinkage, with furnace-cooled samples showing the lowest rates (1.7 ± 0.4% to 5 ± 0.4%) and water-cooled samples showing the highest (2 ± 0.4% to 14.1 ± 0.4%). The study recommends real-time defect detection systems with autonomous corrective capabilities to improve the quality and performance of BJ-AM components.

Comprehensive functional outcome analysis and importance of bone remodelling on personalized cranioplasty treatment using Poly(methyl methacrylate) bone flaps

Cranioplasty involves the surgical reconstruction of cranial defects arising as a result of various factors, including decompressive craniectomy, cranial malformations, and brain injury due to road traffic accidents. Most of the modern decompressive craniectomies (DC) warrant a future cranioplasty surgery within 6-36 months. The conventional process of capturing the defect impression and polymethyl methacrylate (PMMA) flap fabrication results in a misfit or misalignment at the site of implantation. Equally, the intra-operative graft preparation is arduous and can result in a longer surgical time, which may compromise the functional and aesthetic outcomes. As part of a multicentric pilot clinical study, we recently conducted a cohort study on ten human subjects during 2019-2022, following the human ethics committee approvals from the participating institutes. In the current study, an important aspect of measuring the extent of bone remodelling during the time gap between decompressive craniectomy and cranioplasty was successfully evaluated. The sterilised PMMA bone flaps were implanted at the defect area during the cranioplasty surgery using titanium mini plates and screws. The mean surgery time was 90 ± 20 min, comparable to the other clinical studies on cranioplasty. No signs of intra-operative and post-operative complications, such as cerebrospinal fluid leakage, hematoma, or local and systemic infection, were clinically recorded. Importantly, aesthetic outcomes were excellent for all the patients, except in a few clinical cases, wherein the PMMA bone flap was to be carefully customized due to the remodelling of the native skull bone. The extent of physiological remodelling was evaluated by superimposing the pre-operative and post-operative CT scan data after converting the defect morphology into a 3D model. This study further establishes the safety and efficacy of a technologically better approach to fabricate patient-specific acrylic bone flaps with improved surgical outcomes. More importantly, the study outcome further demonstrates the strategy to address bone remodelling during the patient-specific implant design.

Removal of Stair-Step Effects in Binder Jetting Additive Manufacturing Using Grayscale and Dithering-Based Droplet Distribution

Binder jetting is a layer-based additive manufacturing process for three-dimensional parts in which a print head selectively deposits binder onto a thin layer of powder. After the deposition of the binder, a new layer of powder is applied. This process repeats to create three-dimensional parts. The binder jetting principle can be adapted to many different materials. Its advantages are the high productivity and the high degree of freedom of design without the need for support structures. In this work, the combination of binder jetting and casting is utilized to fabricate metal parts. However, the achieved properties of binder jetting parts limit the potential of this technology, specifically regarding surface quality. The most apparent surface phenomenon is the so-called stair-step effect. It is considered an inherent feature of the process and only treatable by post-processing. This paper presents a method to remove the stair-step effect entirely in a binder jetting process. The result is achieved by controlling the binder saturation of the individual voxel volumes by either over or underfilling them. The saturation is controlled by droplet size variation as well as dithering, creating a controlled migration of the binder between powder particles. This work applies the approach to silica sand particle material with an organic binder for casting molds and cores. The results prove the effectiveness of this approach and outline a field of research not identified previously.

Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Conventional approaches to developing biomaterials and implants require intuitive tailoring of manufacturing protocols and biocompatibility assessment. This leads to longer development cycles, and high costs. To meet existing and unmet clinical needs, it is critical to accelerate the production of implantable biomaterials, implants and biomedical devices. Building on the Materials Genome Initiative, we define the concept 'biomaterialomics' as the integration of multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools throughout the entire pipeline of biomaterials development. The Data Science-driven approach is envisioned to bring together on a single platform, the computational tools, databases, experimental methods, machine learning, and advanced manufacturing (e.g., 3D printing) to develop the fourth-generation biomaterials and implants, whose clinical performance will be predicted using 'digital twins'. While analysing the key elements of the concept of 'biomaterialomics', significant emphasis has been put forward to effectively utilize high-throughput biocompatibility data together with multiscale physics-based models, E-platform/online databases of clinical studies, data science approaches, including metadata management, AI/ Machine Learning (ML) algorithms and uncertainty predictions. Such integrated formulation will allow one to adopt cross-disciplinary approaches to establish processing-structure-property (PSP) linkages. A few published studies from the lead author's research group serve as representative examples to illustrate the formulation and relevance of the 'Biomaterialomics' approaches for three emerging research themes, i.e. patient-specific implants, additive manufacturing, and bioelectronic medicine. The increased adaptability of AI/ML tools in biomaterials science along with the training of the next generation researchers in data science are strongly recommended. STATEMENT OF SIGNIFICANCE: This leading opinion review paper emphasizes the need to integrate the concepts and algorithms of the data science with biomaterials science. Also, this paper emphasizes the need to establish a mathematically rigorous cross-disciplinary framework that will allow a systematic quantitative exploration and curation of critical biomaterials knowledge needed to drive objectively the innovation efforts within a suitable uncertainty quantification framework, as embodied in 'biomaterialomics' concept, which integrates multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools, like machine learning. The formulation of this approach has been demonstrated for patient-specific implants, additive manufacturing, and bioelectronic medicine.

Physicochemical Limitations of Capillary Models Applied to High-Concentration Polymer Solutions

Advances in binder jet printing (BJP) require the development of new binder-powder systems, for example, to increase compatibility with better performance metal alloys or to increase the strength of parts using stronger binders. The dynamics of binder absorption are principally understood through capillary models. However, validation of these models in BJP has focused on variation of powder properties. Using a design-of-experiments approach and an optical observation method to track absorption of droplets, this study tests the influence of fluid properties on absorption time against the predictions of capillary models. Properties specific to polymeric binders, such as molecular weight and entanglement state, are also considered. Capillary models are found to be generally accurate in predicting absorption time in dilute systems; however, these predictions are not accurate for highly concentrated binder solutions. The effect of polymer entanglement becomes prevalent as the solution concentration increases, which can also potentially occur as a result of increased evaporation due to powder bed heating. Specifically, concentrated solutions close to the onset of entanglement will absorb much more slowly than predicted. Future models of BJP systems must account for the possibility of polymer entanglement throughout the absorption process. Improved models will provide a more accurate understanding of the flow and solidification of the binder in the powder, allowing faster development of new binders for improved performance in printing.

X-ray Imaging of Alloy Solidification: Crystal Formation, Growth, Instability and Defects

Synchrotron and laboratory-based X-ray imaging techniques have been increasingly used for in situ investigations of alloy solidification and other metal processes. Several reviews have been published in recent years that have focused on the development of in situ X-ray imaging techniques for metal solidification studies. Instead, this work provides a comprehensive review of knowledge provided by in situ X-ray imaging for improved understanding of solidification theories and emerging metal processing technologies. We first review insights related to crystal nucleation and growth mechanisms gained by in situ X-ray imaging, including solute suppressed nucleation theory of α-Al and intermetallic compound crystals, dendritic growth of α-Al and the twin plane re-entrant growth mechanism of faceted Fe-rich intermetallics. Second, we discuss the contribution of in situ X-ray studies in understanding microstructural instability, including dendrite fragmentation induced by solute-driven, dendrite root re-melting, instability of a planar solid/liquid interface, the cellular-to-dendritic transition and the columnar-to-equiaxed transition. Third, we review investigations of defect formation mechanisms during near-equilibrium solidification, including porosity and hot tear formation, and the associated liquid metal flow. Then, we discuss how X-ray imaging is being applied to the understanding and development of emerging metal processes that operate further from equilibrium, such as additive manufacturing. Finally, the outlook for future research opportunities and challenges is presented.

A laboratory-scale binder jet additive manufacturing testbed for process exploration and material development

Binder jet additive manufacturing (BJAM) is capable of fabricating complex three-dimensional components from a variety of material classes. Understanding the fundamentals of BJAM, including spreading of thin layers of powder, powder-binder interactions, and post-processing is critical to develop robust process parameters for BJAM. Toward meeting these needs, this work presents the design, fabrication, and qualification of a testbed for modular, mechanized, BJAM. The testbed seeks to replicate the operating conditions of commercial AM equipment and features fully programmable motion control including powder spreading using a precision roller mechanism, powder supply via a vibrating hopper, and gantry positioning of an inkjet printhead. The inkjet deposition system allows for the use of variable nozzle diameters, the exploration of novel binder compositions, and full control of jetting parameters. Validation of the accuracy and repeatability of the machine and its subsystems, as well as the fabrication of exemplary stainless steel components, are described. The precision engineered testbed can therefore enable the study of the BJAM process, exploration of novel binder compositions, and processing of custom powders to further scientific research and industrial applicability of BJAM.

Absorption and Spreading of a Liquid Droplet Over a Thick Porous Substrate

Spreading over porous substrates occurs in several processes including printing, cleaning, coating, and manufacturing of ceramic structures. For small drops, viscous and capillary forces are ultimately the predominant forces. The process typically undergoes three phases: a first stage in which the droplet spreads, a second phase in which the area of contact with the solid substrate nearly remains constant, and a third stage in which the droplet retracts with its volume reaching zero finally. The objective of the investigation is to find the dynamics of spreading and absorption of the droplet using fundamentals while making relevant approximations to account for both radial and vertical dynamics. The proposed model requires minimal computational work. The results are compared with the published experimental data for the perfect wetting case, and are found to be in good agreement with detailed published experimental data for both droplet dynamics and dynamics of penetration in the porous substrate.