Cuartero, J. | Search bioRxiv

bioRxiv2025

Regression-guided computational design of auxetic scaffolds for soft tissue applications

The mechanical performance of tissue-engineered scaffolds plays a critical role in their effectiveness for regenerative medicine applications. Auxetic metamaterials, characterized by a negative Poissons ratio, offer enhanced conformability and tunable mechanical behavior, making them promising candidates for scaffold design. This study presents a computational framework combining finite element method (FEM) simulations with regression-based predictive modeling to optimize auxetic scaffold architectures. A design of experiments (DOE) strategy enabled the training of FEM-accurate regression models capable of predicting mechanical responses from scaffold microstructural parameters. Sensitivity analysis guided the development of robust optimization strategies for identifying optimal geometries. Validation of the predictive framework was performed using experimentally derived, skin-representative mechanical properties from published literature, demonstrating strong agreement with FEM results. To facilitate broader use, we developed a software tool integrating this pipeline. It includes a manual mode for direct input of design and geometry parameters, and a predictive mode that returns optimized scaffold designs based on target properties. This integrated methodology supports robust, customizable scaffold design, advancing patient-specific approaches in soft tissue engineering.

bioengineering↗

bioRxiv2025

Rational Design and Modeling of Auxetic Fiber Scaffolds for Soft Tissue Engineering via Melt Electrowriting

BackgroundThe development of regenerative biomaterial scaffolds with mechanical properties tailored to native soft tissues remains a challenge in tissue engineering. Mechanical metamaterials with auxetic architectures have taken enormous flight over the past years, as they offer improved control over mechanical function and performance through spatially defined material architecture. However, despite their potential, auxetic scaffold designs are often developed empirically, and the relationship between scaffold microarchitecture, mechanical function, and manufacturability remains poorly defined, limiting their applicability in tissue engineering. In this study, we present a computational framework for the rational design of auxetic fiber scaffolds manufactured using Melt Electro-writing (MEW) for soft tissue engineering. To address the challenge of tailoring scaffold mechanical properties to native tissue, we integrated finite element method (FEM) modeling with experimental validation to predict the mechanical behavior of the scaffolds. MethodThe micro-fibrous scaffolds with customizable auxetic re-entrant structures were designed using Python scripts for generating G-code used in fabrication and for model definition in FEM modeling, respectively. Four distinct auxetic structures - HCELL, SREG, SINV, and STRI - were selected for this study to cover the wide range of mechanical properties of soft tissue, and their geometry parameters were adjusted to reduce the pore size while considering printing resolution. FEM modeling was employed to predict the mechanical behavior of the scaffolds. To validate the predictions, the scaffolds were manufactured via MEW and characterized mechanically under biaxial tensile loading. Results and conclusionMEW manufacturing enabled the production of auxetic fiber scaffolds with sub-millimeter pore resolution, while rational design allowed to correct fabrication discrepancies and improve printed design fidelity. Experimental biaxial characterization of the scaffolds revealed design-dependent, biphasic, non-linear mechanical response, and the developed FEM model was capable of not only accurately simulating the observed mechanical response but also accounting for variations introduced by MEW during fabrication. Additionally, auxetic scaffolds supported fibroblast viability over 7 days, confirming biocompatibility as a first step toward soft tissue engineering. The good alignment between numerical predictions and experimental results highlights the value of FEM modeling as a powerful computational tool for guiding the design and optimization of auxetic scaffolds with tailored mechanical performance for specific soft tissue requirements. The presented methodology offers a significant advancement in the development of functional biomaterials for biomedical applications.

bioengineering↗