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Description
This work presents a computational framework for the optimization of extrusion-based bioprinting processes, with particular emphasis on standard and coaxial bioprinting technologies. Extrusion-based bioprinting is widely used for the fabrication of biomimetic structures containing living cells, thanks to its ability to process a broad range of biomaterials and bio-inks. However, the quality of the printed constructs strongly depends on the complex rheological behavior of the bio-inks, which directly affects printability, cell viability, and shape fidelity. In particular, coaxial bioprinting introduces additional challenges related to fluid–fluid interactions and interface stability, making process optimization particularly difficult.
The study addresses the problem from a dual perspective, considering both the flow inside the extruder and the dynamics of the material after extrusion. Inside the nozzle, a reduced-order predictive model is developed to correlate key process parameters — including nozzle diameter, extrusion pressure, and flow rate — with the stresses acting on embedded cells and the resulting cell viability. The framework is further translated into practical graphical tools to support rapid process design and parameter selection.
Outside the nozzle, the extrusion process is formulated as a viscoelastic free-surface flow problem, extended to coaxial bioprinting through a multiphase approach. An Arbitrary Lagrangian–Eulerian (ALE) finite element framework is implemented to capture phenomena such as die swell, filament evolution, and interfacial stresses between core and shell fluids.
Numerical simulations are used to investigate the influence of rheological and viscoelastic parameters on printing resolution and stress distribution in both standard and coaxial configurations, providing predictive tools for the design and optimization of advanced bioprinting processes.
References
1. Chirianni, F., Vairo, G., Marino, M. (2024). Development of process design tools for extrusion-based bioprinting: From numerical simulations to nomograms through reduced-order modeling. Computer Methods in Applied Mechanics and Engineering, 419, 116685.
2. Chirianni, F., Vairo, G., Marino, M. (2024). Influence of extruder geometry and bio-ink type in extrusion-based bioprinting via an in silico design tool. Meccanica, 59(8), 1285-1299.