Curve-Based Infill Pattern Optimization for 3D Printed Polymeric Scaffolds for Trabecular Bone Applications

Additive manufacturing technology, specifically material extrusion, offers great potential for scaffold manufacturing in tissue engineering. This study presents a novel methodology for the design and optimization of 3D printed polymeric scaffolds to enhance cell viability, thereby promoting improved cell proliferation for tissue engineering applications. Different infill patterns, including gyroid, parallel sinusoidal, and symmetric sinusoidal, were evaluated to determine their impact on cell proliferation and tissue regeneration. To overcome the limitations of existing slicer software, a novel open-source software called FullControl GCode Designer was utilized, enabling the creation of customized infill patterns without restrictions. VOLCO software was employed to generate voxelized 3D models of the scaffolds, simulating the material extrusion process. Finite element analysis was conducted using Abaqus software to evaluate the mechanical properties of the different designs. Additionally, new scripts were developed to evaluate the interconnectivity and pore size of the voxelized models. A factorial design of experiments and a genetic algorithm (combined with Kriging metamodels) were applied to identify the optimal configuration based on optimization criteria (keeping the mechanical stiffness and pore size within the recommended values for trabecular bone and maximizing the surface and interconnectivity). Biological testing was conducted on polylactic acid scaffolds to preliminarily validate the effectiveness of the modeling and optimization methodologies in this regard. The results demonstrated the agreement between the optimization methodology and the biological test since the optimum in both cases was a symmetric sinusoidal pattern design with a configuration resulting in a structure with 53.08% porosity and an equivalent pore size of 584 µm. Therefore, this outcome validates the proposed methodologies, emphasizing the role of pore surface area and interconnectivity in supporting cell proliferation. Overall, this research contributes to the advancement of AM technology in tissue engineering and paves the way for further optimization studies in scaffold design.

Authors

Institutions

Publication Details

Journal
Materials
Published
2025-08-29
DOI
https://doi.org/10.3390/ma18174055
Primary Topic
Bone Tissue Engineering Materials
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Curve-Based Infill Pattern Optimization for 3D Printed Polymeric Scaffolds for Trabecular Bone Applications

Ricardo Donate, Rubén Paz, Mario Monzón, Gisela Vega et al.
Materials
Bone Tissue Engineering Materials
article

Curve-Based Infill Pattern Optimization for 3D Printed Polymeric Scaffolds for Trabecular Bone Applications

Ricardo Donate, Rubén Paz, Mario Monzón, Gisela Vega, Andrew Gleadall
article en

Abstract

Additive manufacturing technology, specifically material extrusion, offers great potential for scaffold manufacturing in tissue engineering. This study presents a novel methodology for the design and optimization of 3D printed polymeric scaffolds to enhance cell viability, thereby promoting improved cell proliferation for tissue engineering applications. Different infill patterns, including gyroid, parallel sinusoidal, and symmetric sinusoidal, were evaluated to determine their impact on cell proliferation and tissue regeneration. To overcome the limitations of existing slicer software, a novel open-source software called FullControl GCode Designer was utilized, enabling the creation of customized infill patterns without restrictions. VOLCO software was employed to generate voxelized 3D models of the scaffolds, simulating the material extrusion process. Finite element analysis was conducted using Abaqus software to evaluate the mechanical properties of the different designs. Additionally, new scripts were developed to evaluate the interconnectivity and pore size of the voxelized models. A factorial design of experiments and a genetic algorithm (combined with Kriging metamodels) were applied to identify the optimal configuration based on optimization criteria (keeping the mechanical stiffness and pore size within the recommended values for trabecular bone and maximizing the surface and interconnectivity). Biological testing was conducted on polylactic acid scaffolds to preliminarily validate the effectiveness of the modeling and optimization methodologies in this regard. The results demonstrated the agreement between the optimization methodology and the biological test since the optimum in both cases was a symmetric sinusoidal pattern design with a configuration resulting in a structure with 53.08% porosity and an equivalent pore size of 584 µm. Therefore, this outcome validates the proposed methodologies, emphasizing the role of pore surface area and interconnectivity in supporting cell proliferation. Overall, this research contributes to the advancement of AM technology in tissue engineering and paves the way for further optimization studies in scaffold design.

MaterialsVol. 18(17)
Universidad de Las Palmas de Gran Canaria (ES), Loughborough University (GB)
European Commission, Ministerio de Ciencia e Innovación, Universidad de Las Palmas de Gran Canaria, Horizon 2020 Framework Programme, Agencia Estatal de Investigación
Openalex Percentile: Top 79%
Bone Tissue Engineering Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.