Additive Summer School (Certificate Program) 2026

Abstract: Mg alloys are promising for clinical implementation of high-strength, biodegradable implants for e.g. bone fixation. This keynote will highlight recent progress in additive manufacturing of such alloys, including tailoring Mg alloy compositions and process parameters to enhance printability, mechanical integrity, and corrosion performance, while addressing challenges such as vaporization, defect formation, and phase instability. Emerging strategies for achieving predictable degradation, improved biocompatibility, and clinically relevant implant architectures will be discussed. Indeed, while additive manufacturing of Mg alloys through Powder Bed Fusion with Laser Beam (PBF‑LB) allows for high-resolution geometries and to some extent microstructural contral, the degradation behavior of printed parts still needs significant improvement.

Abstract: Microfluidic cavitation and jetting enable ultrafast, highly focused liquid microjets that can interact with soft matter at the mesoscale in ways unattainable with conventional tools. In this keynote, I will discuss how confined cavitation in microfluidic systems can be precisely tuned to control jet formation, dynamics, and penetration into soft substrates, including skin, thereby creating an inertial platform for minimally invasive bioengineering and medical applications. I will highlight how these phenomena bridge fundamental fluid dynamics with practical technologies for needle-free drug delivery and advanced mesoscale processing in medicine and biotechnology.

Abstract: As the field of minimally invasive surgery shifts toward the micro-scale, the gap between digital robotic design and clinical validation has become a primary bottleneck. Traditional benchtop testing often relies on simplified synthetic models or inconsistent porcine tissue, neither of which fully captures the nuanced haptic and structural complexities of human anatomy. This keynote explores the frontier of Bio-Digital Convergence, focusing on the development of high-fidelity, 3D-printed multi-material phantoms as a definitive validation platform for surgical micro-robotics.We present a collaborative framework for translating patient-specific imaging data into sophisticated physical models that mimic the heterogeneous mechanical properties of biological tissue. By utilizing advanced multi-material additive manufacturing, we have engineered phantoms that simulate varying physical properties—ranging from rigid bone structures to compliant vascular networks—within a single integrated print.

Key highlights of the presentation include:

• Development Methodology: A review of the end-to-end workflow, from MRI/CT segmentation to the selection of photopolymers that replicate tissue-specific viscoelasticity.
• Micro-Robotic Applicability: Data-driven results on how these phantoms enable the assessment of micro-robotic navigation, stability, and tool-tissue interaction across diverse surgical approaches.
• Validation & Outcomes: An analysis of surgical applicability achieved within 3D-printed environments, demonstrating the efficacy of these models in de-risking micro-robotic interventions before human trials.

By converging additive manufacturing with robotic engineering, we can create a "digital twin" of the surgical theater, providing a repeatable, ethical, and highly accurate environment for the next generation of precision medicine.

Abstract: 3D bioprinting offers a promising approach to fabricate customized scaffolds for tissue engineering and in vitro models [1]. One approach being investigated to improve bioinks for 3D bioprinting is the use of composite bioinks which incorporate ion releasing bioreactive (nano)particles. In this context, research at the FAU Institute of Biomaterials in Erlangen has focused on hydrogels based on alginate dialdehyde-gelatin (ADA-GEL) incorporating ion-releasing bioactive glass (BG) nanoparticles which can be designed to improve printability, mechanical properties, degradation behaviour and biological performance of the 3D bioprinted constructs. In this presentation we will describe the synthesis of ADA via oxidation of alginate [2], and the fabrication of mesoporous BG nanoparticles (MBGNs) via evaporation-induced self-assembly [3] and microemulsion-assisted [4] sol-gel methods. It will be shown that differences in particle size, surface area, and porosity of MBGNs influence the extent of ion release and the gelation of the inks. Different biologically active ions investigated are Cu, Zn, Mg, B, Li, and Ce. Ibn some cases, released ions acted as in situ crosslinking agents, leading to tunable gelation behavior and a defined processing window. With optimized printing parameters, the composite inks produced continuous filaments and three-dimensional structures with shape fidelity. Bioprinting studies were conducted using NIH/3T3 fibroblasts and C2C12 myoblasts [5] in order to establish the functionalities provided by the incorporated ion releasing MBGNs. Local ion release in the hydrogel can lead to significant effects on cellular response indicating potential advantages of utilizing biologically active ions as signaling agents instead of organic molecules or growth factors. For example, incorporating 0.1% w/v MBGNs in cell-laden constructs led to enhanced metabolic activity, highlighting the beneficial role of ion-releasing particles. This work demonstrated that ADA-GEL based composite hydrogels with ion-releasing particles provide reliable printability, tunable properties, and improved cellular responses, supporting their potential as an ionic medicine strategy for bioprinting applications. The work is funded by German Research Foundation, CRC/SFB225 B03.

[1] S. Heid, A.R. Boccaccini, Acta Biomater. 113 (2020) 1–22.
[2] B. Sarker et al., J. Mater. Chem. B 2 (2014) 1470–1482. 
[3] K. Zheng, et al., Journal of the American Ceramic Society 98 (2015) 30–38.
[4] K. Zheng, A.R. Boccaccini, Adv. Colloid Interface Sci. 249 (2017) 363–373.
[5] H. H. Lu, et al., Biomaterials Advances 172 (2025) 214233.
 

Abstract: t.b.a.

Abstract: Additive Manufacturing is transforming the medical implant industry from highly individualized, labor-intensive production toward scalable, industrialized manufacturing. This presentation explores how recent advances in metal 3D printing technology, workflow automation, and process reliability are enabling both patient-specific implants and serial implant manufacturing to reach new levels of efficiency, quality, and economic viability.

For patient-specific implants, the focus shifts from artisanal production to scalable customization. Automated scan-to-print workflows, combined with first-time-right printing strategies, significantly reduce engineering effort, shorten lead times, and improve reproducibility. At the point of care, simplified manufacturing approaches—including support-free printing and robust process automation—reduce operational complexity and make personalized implant production more accessible and reliable within clinical environments.

Beyond customization, AM is increasingly becoming a competitive solution for serial manufacturing of implants. The technology enables simplified supply chains, lower inventory requirements, and greater responsiveness to fluctuating market demand through digital production and reduced lead times. At the same time, advances in printer productivity, process stability, and lower-cost platforms and materials, such as EOS Onyx and next-generation titanium processes and powder, are driving down cost per part. These developments position additive manufacturing as a price-competitive alternative to conventional manufacturing methods such as casting, while maintaining the design freedom and agility unique to AM.

The presentation highlights how the convergence of automation, process maturity, and economic scalability is moving the implant industry from individualization toward true industrialization through additive manufacturing.
 

Abstract: The first step in all medical 3D modelling is image segmentation. Image segmentation is the identification and separation of objects of interest. This keynote will address the current state of image segmentation, key limitations, and future directions in image segmentation and 3D modelling. Despite the progress in image segmentation achieved with convolutional neural networks, major challenges still exist. Processing full-resolution CT image volumes is not possible on desktop graphics cards, and networks struggle in situations with large anatomical variability. These limitations restrict scalability and broader clinical adoption. A novel hybrid segmentation framework will be presented that addresses these limitations. The method combines a low-resolution convolutional neural network with random-walk image segmentation. This allows the use of global context while still achieving high precision, and enables the method to run on standard desktop graphics cards. 3D printed models are increasingly used clinically for anatomical visualization, surgical planning, and patient-specific guides. These applications have clear, proven clinical value, but they represent only a fraction of what is possible. In many applications, physical 3D printed models may not be required, as virtual reality could provide the necessary spatial understanding for surgical planning. Augmented reality is emerging as a powerful tool for intraoperative guidance. A central challenge, however, remains the accurate registration of digital 3D models to patient anatomy, particularly in soft tissue. Robotic surgery is an exciting new frontier. Current robotic surgery systems mainly act as extensions of the surgeon’s hands, but the next generation will aim for greater autonomy, including tasks such as drilling or cutting. These tasks will depend on detailed and accurate 3D models, increasing the demands on image segmentation methods. By advancing image segmentation, we can unlock new opportunities for 3D printing and 3D modelling, ranging from novel immersive visualization techniques to robotic systems, pushing the field beyond its current boundaries.

Abstract: Additive manufacturing (AM) of superelastic Nitinol represents a promising field of research, as its freeform capabilities and potential for customization may enable the development of a new generation of medical implants and devices. However, the use of additive processes for fabricating Nitinol components presents several challenges due to the functional nature of NiTi as a material. Processes such as laser powder bed fusion (LPBF) can lead to preferential evaporation of nickel or oxidation of titanium. These effects are particularly critical because the material is highly sensitive to compositional variations; even a loss of 0.1 at.% Ni can shift transformation temperatures by approximately 10 °C. Furthermore, if oxygen levels exceeding 500 ppm, oxide formation can significantly reduce fatigue life and lead to premature failure. Therefore, it is essential to use high-purity feedstock powders with tightly controlled chemical composition. In this work, we present our experience and approach to the preparation and processing of NiTi powders for LPBF. Powders produced via electrode induction melting gas atomization (EIGA) and vacuum induction melting gas atomization (VIGA) are characterized, and both technologies are evaluated in terms of their suitability for AM processing. Key aspects of these processes are discussed. In the second part of the study, multiple powder batches were prepared in-house using EIGA. These powders were characterized through microscopy, chemical analysis, differential scanning calorimetry (DSC) to determine transformation temperatures, and X-ray diffraction (XRD) to verify phase composition. Results from fabricated parts are presented in the as-built condition and after heat treatment, and are compared with the transformation behavior of the original powders. The parts were manufactured via LPBF, their functional properties were evaluated and compared to previously reported results. Finally, key considerations for the application of AM-processed NiTi in the medical field are discussed.