Enhancing 3D Printing of Gelatin/Siloxane-Based Cellular Scaffolds Using a Computational Model

In recent years, extrusion-based 3D printing has been explored for the fabrication of hydrogel-based structures. This work presents an evaluation of the printability of a gelatin/siloxane hybrid material under defined extrusion conditions by combining rheological characterization, finite-element-based flow simulation in SolidWorks, and image-based analysis of printed meshes. Rheological tests revealed a working region around 50 Pa shear stress, with a maximum viscosity of 3 × 10⁵ Pa·s, a minimum viscosity of 0.089 Pa·s, and a shear rate of 15 s−1. Initial printing conditions using a 27G nozzle, 180 kPa pressure, 32 °C temperature, and 30 mm/s velocity produced mesh images with 54.5% similarity to the CAD target. A FEM-guided parameter set and a binary convolutional neural network trained on microscope images were then used as complementary screening tools to compare printed meshes under the tested conditions. Prints obtained with a 25G nozzle, 170 kPa pressure, 32 °C temperature, and 25 mm/s velocity reached 92.35% image-derived similarity to the CAD target, while the highest similarity observed among the evaluated mesh images was 94.13%. These results support the use of the proposed workflow as a comparative screening strategy for planar printability and CAD similarity in this gelatin/siloxane system. However, the similarity values reported here are derived from 2D image-based metrics and should not be interpreted as direct evidence of full 3D fidelity, generalized process optimization, material superiority, or biological performance.