Abstract
Collagen-based scaffolds have been widely used in tissue engineering. The alignment of collagen fibers and the degree of crosslinking in engineering tissue scaffolds significantly affect cell activity and scaffold stability. Changes in microarchitecture and crosslinking degree also impact the mechanical properties of collagen scaffolds. A clear understanding of the effects of collagen alignment and crosslinking degrees can help properly control these critical parameters for fabricating collagen scaffolds with desired mechanical properties. In this study, combined uniaxial mechanical testing and finite element method (FEM) were used to quantify the effects of fiber alignment and crosslinking degree on the mechanical properties of collagen threads. We have fabricated electrochemically aligned collagen (ELAC) and compared it with randomly distributed collagen at varying crosslinking degrees, which depend on genipin concentrations of 0.1% or 2% for crosslinking durations of 1, 4, and 24 h. Our results indicate that aligned collagen fibers and higher crosslinking degree contribute to a larger Young's modulus. Specifically, aligned fiber structure, compared to random collagen, significantly increases Young's modulus by 112.7% at a 25% crosslinking degree (0.1% (4 h), i.e., 0.1% genipin concentration with a crosslinking duration of 4 h). Moreover, the ELAC Young's modulus increased by 90.3% as the crosslinking degree doubled by changing the genipin concentration from 0.1% to 2% with the same 4 h crosslinking duration. Furthermore, verified computational models can predict mechanical properties based on specific crosslinking degrees and fiber alignments, which facilitate the controlled fabrication of collagen threads. This combined experimental and computational approach provides a systematic understanding of the interplay among fiber alignment, crosslinking parameters, and mechanical performance of collagen scaffolds. This work will enable the precise fabrication of collagen threads for desired tissue engineering performance, potentially advancing tissue engineering applications.